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06/08/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
Required AI Engineer & Architect
The Role:
As AI Architect in the ACoE, you are the technical backbone of our internal agentic transformation. You will design and build the reference architectures, standards, and shared infrastructure that enable hundreds of AI agents to run reliably, safely, and at scale - across R&D, Sales, Customer Revenue, HR, Finance, and Marketing.
This is a hands-on, highly visible role. You will split your time between deep technical work (designing agent orchestration patterns, building cross-company automations, evaluating platforms) and enabling others (code reviews, technical mentorship of citizen developers, setting standards). You will report directly to the ACoE Lead and work closely with the CTO, BI, and Platform teams.
Key Responsibilities
Architecture & Standards:
Define and maintain our reference architectures for agent orchestration, tool permissions, memory models, inter-agent communication, and data boundaries
Establish technical standards for agentic development - prompt engineering patterns, evaluation harnesses, testing frameworks, and shared agent templates
Drive tooling standardization across in partnership with the CTO and CFO, and lead the annual vendor/platform review
Build & Enable:
Develop and maintain selected cross-company agentic solutions and automation workflows
Build and maintain the shared infrastructure: monitoring integrations, KPI dashboards, the agent registry, and the ACoE knowledge base
Conduct technical reviews and code reviews for agents before production deployment
Serve as technical SME for citizen developers across all business units - unblocking, guiding, and reviewing their work
Governance Support:
Define and implement the pre-deployment evaluation harness and model card standards
Support the AI Governance Officer (initially the ACoE Lead) with technical input on risk classification, incident response, and rollback planning
Contribute to quarterly ethics audits for high-risk agents
Innovation:
Track the rapidly evolving agentic AI ecosystem and bring relevant insights and tools back
Co-author external technical content (whitepapers, conference presentations) to establish our technical thought leadership.
Requirements:
5+ years of experience in system architecture or enterprise platform engineering, with Proven experience designing and implementing technical governance frameworks in a large-scale or regulated environment.
At least 2 years working with AI/ML systems in production
Hands-on experience building LLM-powered applications or autonomous agents
Solid understanding of agentic patterns: tool use, RAG, memory models, multi-agent orchestration, HITL design
Experience with prompt engineering, evaluation frameworks, and LLM observability/monitoring
Ability to translate business requirements into scalable technical architectures - and then actually build them
Clear communicator who can work across technical and non-technical stakeholders
Experience with Claude Code / Cowork, Base44, or other Anthropic/OpenAI tooling
Nice to Have:
Background in ITSM, enterprise SaaS, or platform engineering
Experience building internal developer tools or enabling non-developer builders
Familiarity with AI governance frameworks (NIST AI RMF, ISO 42001, IMDA).
This position is open to all candidates.
 
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20/07/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for an experienced Applied AI/ML Scientist with expertise in building agentic systems and autonomous agents to join one of our R&D. You will be at the core of transforming our supply chain solutions into a fully agentic platform, designing and building agents that autonomously generate analytical pipelines, orchestrate multi-step reasoning, and resolve complex logistics challenges for our customers.
You will combine strong machine learning and deep learning expertise with the ability to architect and implement production-grade agentic systems, working closely with engineering, product, and domain experts to push the boundaries of what autonomous AI can do in supply chain.
Responsibilities:
Design and build autonomous agentic systems that generate, configure, and execute analytical pipelines to solve supply chain challenges end-to-end
Architect multi-agent workflows with planning, tool use, memory, and feedback loops, enabling agents to reason, adapt, and improve over time
Develop and integrate ML and deep learning models (e.g., predictive models, anomaly detection, demand forecasting) as core capabilities within agentic pipelines
Research and apply state-of-the-art techniques in agentic AI, LLM orchestration, and multi-agent systems to production use cases
Translate complex logistics and supply chain challenges into agent-based problem formulations, collaborating closely with product and domain experts
Define and implement rigorous evaluation frameworks for agent performance: correctness, reliability, robustness, and edge-case handling
Collaborate with software engineers to productize agentic solutions - including testing, monitoring, versioning, and iterative improvement
Contribute to team practices: reproducible code, experiment tracking, documentation, and knowledge sharing
Requirements:
4+ years of experience in applied data science or ML in a product environment, with demonstrated experience building agentic systems or autonomous agents
MSc in Computer Science, Data Science, Mathematics, Statistics, Engineering, or a related field (or equivalent practical experience)
Proven track record designing and implementing multi-step agentic pipelines, including LLM-based agents, tool use, planning loops, and memory mechanisms
Hands-on experience with agentic frameworks such as LangChain, LangGraph, AutoGen, or equivalent
Strong Python coding skills; familiar with Spark for large-scale, distributed data processing
Experience with LLM APIs (e.g., OpenAI, Anthropic, Bedrock, open-source models) and prompt engineering for agentic use cases
Experience performing rigorous model evaluation (baselines, cross-validation, error analysis) and defining evaluation strategies for agent behavior
Strong communication and collaboration skills; able to work across engineering, product, and supply chain domain experts and iterate fast
Nice to Have (Advantages):
Experience with multi-agent architectures, agent-to-agent communication protocols, and agent orchestration at scale
Experience with cloud platforms (AWS, GCP, Azure) and MLOps practices (CI/CD for ML, model monitoring, drift detection)
Familiarity with containerization and production engineering practices (Docker, Kubernetes)
This position is open to all candidates.
 
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10/08/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
Required AI Data Engineer
About the role:
We're building the intelligence layer that lets everyone ask hard questions of our data and get trustworthy answers - in plain language, in seconds. As AI Data Engineer, you own the semantic and AI-native surface of our Snowflake platform: the governed semantic layer that defines "what a metric means," the Cortex Agents that let business users query it conversationally, and the infrastructure that keeps all of it fast, reliable, and ready to scale.
This is a builder-owner role. You'll ship the semantic models, wire up the agents, and set the standard for how analysts across the company work with data. You'll also lead the Data Analyst guild - the connective tissue that keeps our hub-and-spoke analytics model coherent as it grows.
If you're excited by the space where data engineering, LLM tooling, and analytics governance meet, this role sits right in the middle of it.
What youll Own:
Snowflake semantic layer - Own the semantic layer end-to-end as the single source of truth for metrics; design semantic models, enforce naming standards, and ensure consistent metric definitions across dashboards and AI agents.
Cortex Agents - Design and deploy conversational AI agents using Cortex Analyst and Cortex Search; tune for accuracy and safety, expose through multiple surfaces (Snowflake Intelligence, Streamlit, MCP), and build evaluation harnesses to maintain quality at scale.
Data craft (Analytics guild) - Co-lead the technical track of the Analytics guild; set SQL and modeling standards, run technical enablement and code reviews, and serve as the technical authority for analysts.
Scaling data infrastructure - Improve performance, reliability, cost efficiency, and governance across the dbt/Airflow/Airbyte/Snowflake stack as data volume and query load grow; optimize warehouse sizing, medallion layers, and ingestion pipelines.
What you'll do day to day:
Model and maintain semantic views that power both dashboards and AI agents, keeping definitions versioned, tested, and certified.
Build, evaluate, and iterate on Cortex Agents - including retrieval quality, guardrails, and observability.
Extend and optimize dbt models, Airflow DAGs, and Airbyte connectors across bronze/silver/gold layers.
Partner with GTM, Finance, CS, and Product stakeholders to translate business questions into governed, reusable data assets.
Run the Data Analyst guild: standards, reviews, enablement, and tooling.
Own data quality, lineage, and cost monitoring across the Snowflake platform.
Expose data and agents through Streamlit apps, BI tools (Omni), and MCP servers for internal AI workflows.
Requirements:
5+ years of experience in data engineering roles in B2B SaaS companies
Strong SQL and hands-on data engineering experience building production pipelines (dbt strongly preferred; orchestration with Airflow or similar).
Deep, practical Snowflake experience - warehouse management, performance tuning, cost control, and data modeling.
Experience building or maintaining a semantic / metrics layer, and a strong point of view on metric governance.
Hands-on work with LLM-powered data applications - RAG, text-to-SQL, agent orchestration, or similar. Snowflake Cortex (Analyst, Search, Agents) is a big plus.
A builder mindset paired with the judgment to set standards others follow.
Nice to have:
Experience leading a guild, chapter, or community of practice - or otherwise driving standards without direct authority.
Familiarity with reverse-ETL, streaming ingestion (Airbyte or similar), and BI tooling on a semantic layer (Omni, ThoughtSpot).
Exposure to GTM / RevOps data (CRM, product usage, call intelligence) and the ambiguity that comes with it.
Experience with MCP, Streamlit, or embedding AI into internal tooling.
This position is open to all candidates.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for a Senior Data Architect to help define and evolve the data architecture of our SaaS platform and core products. You will work closely with product, delivery, and engineering squads to design scalable, reliable data systems, set technical direction for how data is ingested, modeled, stored, and served, and guide teams in making high-quality architectural decisions that balance delivery speed with long-term sustainability.
This is a hands-on, senior technical leadership role: you will spend most of your time shaping data architectures with teams, reviewing data models, pipelines and critical code, and driving shared standards and patterns across the organization, all in an advanced agentic environment.
Responsibilities:
Define and evolve the data architecture for key domains (ingestion, ELT/ETL, data modeling, storage, APIs, integration, observability, governance, and security), including owning the lakehouse/medallion architecture (bronze/silver/gold) and the data flows that move data across layers at scale.
Translate business and product requirements into pragmatic data designs, data contracts, and architecture roadmaps; create and maintain architecture artefacts (data flow/lineage diagrams, ADRs, reference implementations, modeling guidelines).
Evaluate design options and technology choices, articulate trade-offs, and lead decision-making with stakeholders; push forward the agentic mindset and implementation across the data platform.
Partner with squad leads and senior engineers to design data solutions, break down complex problems, and keep implementations aligned with the target architecture; participate in design/tech reviews to ensure NFRs (performance, scalability, data quality, resilience, security, operability) are addressed early.
Provide hands-on support where it matters most: spike and prototype critical data flows, review complex PRs, and help debug tricky production data and pipeline issues.
Collaborate with Product to shape technical feasibility, sequencing, and scope for data-driven roadmap items; communicate complex technical topics in simple language to non-technical stakeholders.
Define and promote data architecture principles, modeling conventions, coding standards, and reusable patterns (shared transformations, libraries, datasets, services) to reduce duplication and technical debt; drive adoption of shared platform capabilities (observability, CI/CD, orchestration, governance, DevOps tooling) across squads.
Ensure data architectures are observable, operable, and resilient by design; partner with DevOps/SRE on deployment, monitoring, data quality, and incident response; identify areas of high technical debt or architectural risk and lead remediation initiatives; define and track technical KPIs tied to architecture decisions.
Act as a technical mentor for senior engineers and tech leads, fostering a culture of thoughtful design, documentation, and constructive technical debate; lead by influence- help teams make better decisions instead of making every decision for them.
Requirements:
8+ years of experience in software / data engineering, including several years in a senior / staff / architect role designing complex data systems.
Strong experience designing modern data platforms and distributed data architectures (lakehouse/warehouse, batch and streaming/event-driven patterns, robust data APIs).
Experience working with columnar/serialization data formats such as AVRO and Parquet, including schema evolution and storage trade-offs.
Experience with DBT and ELT management tools for building, testing, and maintaining transformation pipelines.
Experience with Apache Airflow (or comparable orchestration tooling) for scheduling and managing data workflows.
Experience working with Databricks (or Snowflake) and medallion architecture (bronze/silver/gold).
This position is open to all candidates.
 
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09/08/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are seeking a Senior Software Architect to lead and shape the architectural vision of our SaaS healthcare platform, guide the adoption of cutting-edge AI technologies, and ensure our solutions remain scalable, secure, and future-ready. This is a hands-on, strategic leadership role that combines visionary system design, proof-of-concept development, and AI-first innovation enablement.

Responsibilities
1. Architectural Leadership

Define, communicate, and evolve the platforms architectural vision to ensure alignment with business goals.
Lead high-level design discussions and decisions for new and existing products.
Establish and maintain architectural principles, standards, and patterns across all engineering teams to ensure consistency and coherence.
Drive cloud-native architecture in AWS with a strong focus on scalability, availability, performance, and cost efficiency.
2. Innovation & Emerging Technology

Build POCs and pilots for new solutions, frameworks, and AI capabilities.
Evaluate emerging trends in AI, LLMs, MCPs, agents, and developer productivity tools, ensuring strategic adoption where relevant.
Initiate projects/features to solve widespread problems (including work with Support, DevOps, Infosec)
3. AI Tooling Evangelism

Spearhead engineering-wide adoption of AI-assisted development workflows, including developer productivity tools, code copilots, automated quality checks, and automated documentation.
Define best practices, guidelines, and governance for AI usage in development (e.g., Cursor configuration rules, prompt engineering standards).
Educate and mentor teams on effective AI utilization for engineering, product, and operational tasks, taking into account security, costs, and compliance.
4. Technical Governance & Best Practices

Overall ownership of the system scalability, COGS, and stability of the product(s)
Define standards for coding, testing, CI/CD, and monitoring.
Enforce architectural and design reviews for key initiatives.
5. Cross-functional Collaboration

Work closely with Engineering, Product, Data Science, DevOps, and Security teams to deliver well-architected solutions.
Communicate complex technical concepts to non-technical audiences, including executives and external partners.
Requirements:
Proficiency in modern programming languages (e.g., Python, TypeScript, Node.js)
Hands-on experience with AI/ML tooling, including LLM integration, developer productivity platforms, MCP/agent-based architectures, and AI-enhanced workflows.
Strong leadership, mentoring, and decision-making skills.
Excellent written and verbal communication skills in Hebrew and English, with the ability to influence stakeholders at all levels.
This position is open to all candidates.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We're hiring the engineering leader who will own its AI core.
Small senior team, greenfield architecture and real production environments from day one. You'll be one of the founding technical leaders - writing code, shaping the architecture, and growing the team as the product scales.
What You'll Do:
Agent Architecture & Engineering:
Design and build the AI systems at the center of the product: researcher agents, deterministic runners, multi-agent orchestration across thousands of targets and hundreds of sites.
Own the full agent stack - LLM selection and behavior, RAG pipelines, tool use, memory, evaluation, and observability. Make architectural decisions that will define how the product works for years.
Drive adoption of the modern agent ecosystem: LangGraph, MCP, semantic tool discovery, hybrid edge/cloud workflows, A2A patterns. Keep pushing the frontier.
Safety & Reliability:
Design for progressive autonomy: pre-checks, fault tolerance, rollback, and full audit trails. In our customers' environments - critical infrastructure, enterprise security - a wrong action has real consequences.
Build the evaluation and observability pipelines that make autonomous agent behavior trustworthy and debuggable in production.
Partner with Security and DevOps on agent execution boundaries, especially across on-prem ↔ cloud data flows.
Technical Leadership:
Spend most of your time in the codebase. Set the technical bar by example - architecture, code quality, and engineering judgment.
Establish standards for testing, evaluation, and safe deployment of AI systems. Build the practices that scale with the team.
Work directly with the PM and enterprise design partners to shape the roadmap. Your decisions will drive the product, not just execute it.
Team:
Start with a small senior group, grow it deliberately. Hire well, mentor, and shape the engineering culture of a startup inside a public company.
Requirements:
Must have:
8+ years engineering experience with production systems, including time leading or tech-leading a team.
Experience building a team from the ground up - first hires, culture, hiring bar.
Shipped AI/LLM products to production - not just demos or POCs.
Strong Python and/or TypeScript.
Deep hands-on experience with LLMs, agent frameworks (LangGraph, Mastra, AWS Strands, Vercel AI SDK, or similar), prompt engineering, RAG, and model behavior in production.
Distributed systems fundamentals: workflow orchestration, fault-tolerant architectures, async patterns.
Cloud and self-hosted model deployment (Bedrock, Vertex AI, Azure OpenAI, Anthropic, Ollama).
Hands-on leadership - you write code, review PRs, set the bar. You also know when to step back.
Comfortable with ambiguity and the pace of a zero-to-one build.
Nice to have:
Background in network security, asset discovery, or traffic analysis
Familiarity with OT/ICS network protocols (Modbus, S7comm, PROFINET, DNP3)
Multi-agent architectures in production (A2A, agent swarms).
Memory libraries (Mem0, LangMem, MemGPT).
LLM evaluation frameworks (LangSmith, Bedrock Evaluations).
Vector stores (Pinecone, Weaviate, Chroma), PostgreSQL/MongoDB.
Background in cybersecurity or critical infrastructure.
IaC (CDK, Terraform).
This position is open to all candidates.
 
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09/08/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
1. AI Architecture & Technical Leadership

Guide AI architectural direction across platform, focusing on system design, model lifecycle, and integration of AI components into product workflows.
Act as a senior technical reviewer and thought partner for complex or cross-team AI design decisions.
Provide technical oversight on areas such as exploring new models/technologies/opportunities for the company
Surface architectural risks, tradeoffs, and long-term implications, including cost, security and compliance aspects and clearly advise the VP of AI when certain technical directions should not be pursued.
This role influences judgment, clarity, and experience, not through blocking authority.

2. Hands-on Applied Innovation (Core Pillar | ~50%)

Spend at least 50% of time hands-on, building:
End-to-end AI prototypes
Technical demos and proofs of concept
Exploratory implementations of new AI capabilities
Drive applied innovation that:

De-risks new technologies
Demonstrates feasibility and impact
Informs product direction and business opportunities
Build fast, concrete examples that teams can learn from and extend.
Transition successful prototypes to team ownership for further development and scaling.
This role is expected to lead AI innovation by doing, while working closely with product, medical and engineering

3. Best Practices & Technical Enablement

Define and promote best practices for applied AI development, including:
Rapid prototyping and vibe coding.
Agent design, orchestration, and evaluation patterns
Experimentation, benchmarking, and validation workflows
Help teams align on shared technical patterns, tools, and standards.
Identify opportunities to consolidate duplicated efforts and improve cross-team coherence.
Lead technical deep dives, architecture discussions, and design reviews.
4. AI Compliance & Regulatory Enablement (Technical Scope)

Ensure Navinas AI development practices align with applicable AI regulations for a software product handling sensitive medical data.
Define and guide AI-specific compliance practices, including data usage, transparency, evaluation, and documentation expectations.
Support and contribute to AI-related compliance and regulatory documentation, in close collaboration with Legal, Security, and Medical Research teams.
Serve as a technical point of reference for AI compliance questions.
Requirements:
Proven experience designing and building complex AI systems that have been successfully delivered to production, with an end-to-end understanding of research, architecture, validation, and production handoff.
Strong hands-on experience with modern AI approaches, including Machine Learning, Deep Learning, and LLM-based systems; experience with agentic AI systems or orchestration patterns is a strong advantage.
Demonstrated ability to move quickly from idea to working prototype, with a strong passion for hands-on experimentation and applied innovation.
Experience working in environments involving sensitive data and regulatory constraints, with an understanding of how these considerations shape AI system design.
Excellent system-level technical judgment, including the ability to identify risks, tradeoffs, and unintended consequences in AI systems.
Proven ability to act as a technical leader without formal authority, influencing and guiding senior peers through collaboration and expertise.
Strong communication and interpersonal skills, with the ability to explain complex technical concepts to diverse stakeholders.
Ability to contribute to clear technical and AI-related compliance documentation.
High proficiency in Python and modern AI/ML tooling.
This position is open to all candidates.
 
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17/08/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
The Architect leads the design and implementation of scalable AI platforms and central services for AI, creating shared capabilities, tools, and frameworks that transform how our company builds, delivers, and operates products.
Beyond architecture, this role drives strategic, high-impact projects with powerful ROI that positively disrupt operations and elevate customer outcomes, improving efficiency, innovation, and product value across the company.
Strategic Objectives:
Accelerate AI Transformation across the organization by designing and operationalizing central AI services and a unified platform framework that powers key transformation initiatives, including Agentic Workflows.
Institutionalize AI Engineering and Governance Standards through common architecture, services, and enablement frameworks ensuring scalability, security, quality, and compliance.
Deliver measurable transformation outcomes through strategic, ROI-driven projects that reshape how our company's products are built and operated, directly benefiting customers and business performance.
Drive sustainable transformation at scale, balancing rapid innovation with operational excellence and long-term maintainability.
Key Responsibilities
Architect the AI Transformation Framework
Design and own the end-to-end architecture that enables the companys AI Transformation vision - spanning data, models, pipelines, APIs, and governance layers.
Define blueprints and integration standards to embed AI and automation throughout the SDLC, from ideation to delivery.
Build Generative AI Platforms and Central Services
Lead the design and implementation of the AI Enablement Platform and central AI services powering transformation initiatives such as Agentic Workflows and the Knowledge Hub.
Create scalable, secure, and modular AI components that can be leveraged across product lines and engineering domains.
Partner with infrastructure, platform, and security teams to operationalize LLM-based services, retrieval systems, and agentic automation flows.
Drive Strategic Transformation Projects
Lead cross-functional initiatives that deliver tangible operational and business impact - improving speed, quality, and cost-efficiency across the product organization.
Develop strong business cases and ROI frameworks to prioritize and communicate transformation value at the executive level.
Translate successful outcomes into reusable playbooks and AI cookbooks that scale across teams, roles, and product domains.
Technical Leadership and Enablement
Act as the senior technical authority and coach for AI transformation initiatives, guiding teams through architecture reviews, proofs of concept, and scale-up phases.
Mentor internal architects and tech leads to develop AI-native architectural competencies.
Requirements:
10+ years in software or platform architecture, including experience leading cross-organizational transformations.
Proven track record of designing large-scale, data-driven, or AI-enabled systems.
Experience delivering projects with measurable business outcomes and ROI.
Expertise
Enterprise and cloud-native architecture (multi-tenant, microservices, API-first, distributed systems).
Deep understanding of AI/ML infrastructure, LLM integration patterns, agent frameworks, and MLOps.
Familiarity with data engineering, retrieval-augmented generation (RAG), and workflow orchestration (e.g., n8n, LangChain).
Background in cyber security or secure software design - strong advantage.
Mindset & Skills
Transformation-oriented thinker who connects technology to organizational capability and business strategy.
Excellent communicator and influencer at multiple levels (executive to technical).
Bias for action, simplification, and measurable outcomes.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8785697
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תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for a Senior Software Architect to help define and evolve the architecture of our SaaS platform and core products. You will work closely with product, delivery, and engineering squads to design scalable, reliable systems, set technical direction, and guide teams in making high‑quality architectural decisions that balance delivery speed with long‑term sustainability.
This is a hands‑on, senior technical leadership role: you will spend most of your time shaping architectures with teams, reviewing designs and critical code, and driving shared standards and patterns across the organization, all in an advance agentic environment.
Responsibilities:
Architecture & technical leadership:
Define and evolve the architecture for key domains in our platform (APIs, services, data flows, integration, observability, security).
Translate business and product requirements into clear, pragmatic technical designs and architecture roadmaps.
Create and maintain architecture artefacts: diagrams, decision records (ADRs), reference implementations, and guidelines.
Evaluate design options and technology choices, articulate trade‑offs, and lead the decision‑making process with stakeholders.
Push forward the agentic mindset and implementation.
Working with squads (R&D):
Partner with squad leads and senior engineers to design solutions, break down complex problems, and keep implementations aligned with the target architecture.
Participate in design / tech reviews, ensuring non‑functional requirements (performance, resilience, security, operability) are addressed early.
Provide hands‑on support where it matters most: spike and prototype critical flows, review complex pull requests, and help debug tricky production issues.
Partnering with Product:
Collaborate with Product to shape technical feasibility, sequencing, and scope for roadmap items and cross‑squad initiatives.
Communicate complex technical topics in simple language to non‑technical stakeholders when discussing roadmap options and trade‑offs.
Standards, reuse, and platform mindset:
Define and promote architecture principles, coding standards, and reusable patterns (modules, libraries, services) that reduce duplication and technical debt.
Champion platform thinking: design services and components that can be safely reused across teams and products.
Drive adoption of shared platform capabilities (observability, CI/CD, authentication, data, DevOps tooling) across squads.
Quality, reliability, and continuous improvement:
Ensure architectures are observable, operable, and resilient by design; partner with DevOps/SRE on deployment, monitoring, and incident response.
Identify areas of high technical debt or architectural risk and lead structured remediation initiatives.
Help define and track technical KPIs (e.g., performance, reliability, incident volume) tied to architecture decisions.
Mentoring and leadership:
Act as a technical mentor and sounding board for senior engineers and tech leads, helping them grow their architecture skills.
Foster a culture of thoughtful design, documentation, and constructive technical debate.
Lead by influence rather than authority: you help teams make better decisions instead of making every decision for them.
דרישות:
8+ years of experience in software engineering, including several years in a senior / staff / architect role designing complex systems.
Strong experience with modern backend and distributed architectures (microservices or modular monoliths, event‑driven patterns, robust APIs).
Solid understanding of cloud‑native architecture (e.g., AWS/Azure/GCP), containers, and infrastructure‑as‑code practices.
Proven ability to design for scale, performance, security, and reliability in production SaaS environments.
Hands‑on experience with at least one major language and ecosystem used in our stack (e.g., Java, Python, Node.js, or sim המשרה מיועדת לנשים ולגברים כאחד.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8796435
סגור
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סגור
דיווח על תוכן לא הולם או מפלה
מה השם שלך?
תיאור
שליחה
סגור
v נשלח
תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
5 ימים
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We're forming a new AI Group and looking for a Senior AI Engineer to help shape it from an early stage - a greenfield, long-term effort to evolve how decisions are made across the platform using AI-driven systems. You won't just integrate APIs or build demos; you'll build the AI brain that works alongside (and increasingly drives) our core automation engine, with real production impact from day one and room to grow into technical leadership as the group scales.

Agentic AI Architecture: Design and build autonomous AI agents that analyze infrastructure in real time and make intelligent decisions. Work with modern agentic frameworks (LangGraph, PydanticAI) and conversational AI to create multi-agent systems - including troubleshooting, optimization, FinOps, and how-to agents. Leverage core LLM capabilities (tool-use, memory, retrieval) to operate safely in production.
Platform Integration & Intelligent Decision Systems: Develop MCPs to expose capabilities to AI agents that reason over infrastructure environments, metrics, configurations, and cost signals. Build integrations with tools like Slack, Jira, and AI-powered IDEs (Cursor, Windsurf) to deliver context-aware insights, from "why is this pod not scheduling?" to "how can we reduce costs by 30% safely?"
AI Model Development & MLOps: Build and deploy machine learning models that learn from infrastructure patterns - detecting the right resource policies for workloads, predicting optimal scaling triggers, and recommending GPU configurations. Own the complete ML pipeline from training to production, ensuring models are reliable, monitored, and continuously improving.
R&D AI Tools Development & Adoption: Build and embed internal AI tools to accelerate engineering, development, research, and support.
AI Tools for Business Impact: Develop AI-powered tools that help Sales and Support teams demonstrate value instantly - agents that analyze customer infrastructure, generate cost optimization reports automatically, and turn technical data into clear business recommendations.
End-to-End Ownership: Own AI systems from concept to production, ensuring they're fast (sub-2-second responses), reliable, safe, and cost-effective. Build evaluation frameworks to measure quality, implement security controls, and balance performance tradeoffs in production.
Technical Leadership: Define AI architecture and best practices as a founding member of the AI team. Make key technical decisions - choosing frameworks, designing multi-agent systems, establishing data governance - and shape how evolves from AI-enhanced internal tools to customer-facing AI products.
Requirements:
Core Engineering: Significant software engineering experience (typically 4+ years) with strong Python skills and solid backend engineering fundamentals.
Production Experience: Experience building and operating production systems in cloud environments.
Real-World GenAI Experience: Practical experience bringing LLM-based systems into production, including handling latency, cost control, and failure modes. Familiarity with additional agentic frameworks (e.g., LangChain, MetaGPT) and evaluation frameworks.
Builder Mentality: Strong ownership and the ability to operate independently while collaborating closely across teams, with the motivation to grow into technical leadership as the group expands.
(Advantage) Data & RAG: Experience enabling LLMs to consume structured or operational data (configurations, logs, metrics) and experience with retrieval systems (RAG) or vector databases.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8792284
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סגור
דיווח על תוכן לא הולם או מפלה
מה השם שלך?
תיאור
שליחה
סגור
v נשלח
תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
Location: Tel Aviv-Yafo
Job Type: Full Time
We are hiring an AI Researcher to join the research team building the next generation of AI-native security systems. You will work alongside security and threat researchers to build large-scale AI agents that reason over software, code, endpoint activity, and security signals to detect malicious behavior, uncover vulnerabilities, assess risk, and make autonomous security decisions in real-world production environments. We are entering the Mythos era - where attackers operate at machine speed using autonomous systems and AI-generated software, and defenders must evolve the same way. We use state-of-the-art frontier models, including access to Mythos, to build reliable AI-native security systems at global scale. You will help design the evaluations, harnesses, and reliability infrastructure that make autonomous agents dependable under real customer load, while collaborating with leading AI organizations including Anthropic on initiatives such as Glasswing. This is an opportunity to work at the frontier of AI, autonomous systems, and cybersecurity while helping define how the next generation of security systems will operate.
Key Responsibilities
Build AI agents and autonomous security systems that reason over software, code, endpoint activity, MCPs, and security signals to detect malicious behavior, uncover vulnerabilities, and assess risk at production scale.
Develop systems, tooling, and infrastructure that enable agents to autonomously investigate threats, hunt for malware in massive datasets, and operate reliably in complex security environments.
Design and run experiments to evaluate frontier-model and agent capabilities in realistic adversarial scenarios, including benchmark creation, large-scale datasets, automated evaluations, and human-in-the-loop review systems.
Build the evaluation harnesses, observability systems, and reliability infrastructure required to make autonomous agents accurate, scalable, and dependable under real customer load.
Engineer for scale and performance across large distributed AI systems, including inference optimization, orchestration, batching, caching, cost controls, and graceful degradation under high demand.
Continuously evaluate emerging models, agent architectures, prompting techniques, and research directions to ensure our systems remain at the frontier of AI-native cybersecurity.
Rapidly prototype and test new approaches across reasoning, autonomy, evaluations, and security workflows as the AI landscape evolves.
Partner closely with threat and security researchers to extract domain expertise, translate analyst reasoning into AI workflows, and enable new forms of automation and autonomous investigation.
Collaborate with leading AI and security researchers to shape the future of AI-native cybersecurity as the industry transitions into the Mythos era.
Senior candidates will help define research direction, shape technical strategy, identify high-leverage problems, and influence how autonomous AI systems are deployed across the organization.
Requirements:
Strong experience building and operating AI agents or autonomous systems in production environments.
Hands-on experience with LLMs, agent frameworks, tool use, reasoning systems, retrieval, evaluations, or multi-agent orchestration.
Proven ability to rapidly design experiments, iterate on ideas, and turn research into reliable production systems.
Deep familiarity with the rapidly evolving AI ecosystem; enthusiasm for continuously experimenting with new models, techniques, architectures, and research directions.
Strong intuition for identifying which new AI capabilities are production-ready versus hype, and ability to quickly translate frontier advances into practical systems.
Strong engineering skills, especially in Python and modern AI infrastructure.
Proven ability to own problems end-to-end, from research and prototyping through deployment, scaling, and reliability.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8781327
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