Senior AI Infrastructure Engineer

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8728094

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2 ימים

Senior ML Platform Engineer - Sovereign AI Engineering

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

Required Senior ML Platform Engineer - Sovereign AI Engineering
The Dream Job
It starts with you - an engineer driven to build the ML platform that turns research into reliable, production-grade intelligence. You care about reproducibility, low-friction experimentation, and infrastructure that earns the trust of the scientists and researchers who depend on it daily. You'll architect and ship our ML platform - training pipelines, model serving, feature stores, experiment tracking, and compute orchestration - turning models into production capabilities across cloud and on-prem, including air-gapped deployments. A significant part of the platform supports large language models, with unique challenges across training, evaluation, and inference in mission-critical environments.
If you want to make a meaningful impact, join our mission and build the ML platform that drives Sovereign AI products - this role is for you.
Responsibilities
Build and operate ML training infrastructure - distributed training pipelines, compute scheduling, and reproducible experiment workflows that data scientists rely on daily.
Own model serving and inference systems - packaging, deployment, autoscaling, A/B testing, canary rollouts, and latency/cost optimization for production models.
Run feature stores, model registries, and dataset versioning - enabling self-serve feature engineering, model lineage, and reproducible experiments across teams.
Build experiment tracking and evaluation infrastructure - automated evals, comparison dashboards, drift detection, and monitoring that give teams visibility into model behavior and performance.
Build and maintain production pipelines for training, fine-tuning workflows, and serving domain models - owning reliability, reproducibility, and scale.
Build and maintain the monitoring and observability layer - model performance tracking, data and prediction drift detection, data quality validation, and alerting.
Improve performance and cost across the ML stack - training throughput, inference latency, batch vs. real-time tradeoffs, and compute cost management.
Ship shared tooling - libraries, templates, CI/CD for models, IaC, and runbooks - while collaborating across Data Platform, AI, Data Science, Engineering, and DevOps. Own architecture, documentation, and operations end-to-end.

Requirements:
5+ years in software engineering, with 2+ years focused on ML infrastructure, MLOps, or data-intensive systems
Engineering craft - Strong Python, distributed systems design, testing, secure coding, API design, CI/CD discipline, and production ownership.
ML platform & serving - Model serving frameworks (e.g., Triton, TorchServe, vLLM, Ray Serve); model packaging, deployment pipelines, and inference optimization
Training infrastructure - Distributed training pipelines (e.g., frameworks like PyTorch, JAX) experiment orchestration and reproducibility
ML lifecycle tooling - Feature stores, model registries, experiment tracking (e.g., MLflow, Weights & Biases); dataset versioning and lineage
Data pipelines - Building training and inference data pipelines; familiarity with tools like Spark, Airflow/Dagster, and streaming ingestion
Comfortable with AI coding tools like Cursor, Claude Code, or Copilot
Nice to Have:
Experience operating in constrained environments - on-premise, private cloud, or air-gapped deployments
Hands-on experience with simulation environments, synthetic data generation, or reinforcement learning workflows
Platform & infra - Kubernetes, AWS, Terraform or similar IaC, CI/CD, observability, incident response
Hands-on data science or applied ML experience.

This position is open to all candidates.

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8723338

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28/06/2026

AI Architect

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time and Hybrid work

we are looking for a AI Architect.
Responsibilities:
1. AI Architecture & Technical Leadership
Guide AI architectural direction across Navinas 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.
Optional / Nice-to-Have :
Deep experience in NLP, NLU, or clinical text processing.
Experience deploying LLMs or agent-based systems in production.
Familiarity with cloud-native ML stacks (AWS, Docker, Kubernetes).

This position is open to all candidates.

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8713908

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18/06/2026

Senior AI Infrastructure Engineer

חברה חסויה

Location: More than one

Job Type: Full Time

We're looking for a Senior AI Infrastructure Engineer to join a group that specializes in Security and Networking, and specifically ML/AI, MLOps, and agentic AI development. As a Senior AI Infrastructure Engineer, youll build and maintain the infrastructure, tools and processes necessary to support the AI lifecycle in a production environment. You will collaborate closely with data scientists, software engineers, and security architects to ensure smooth development, deployment, evaluation, and optimization of AI pipelines, models, and agents. This role requires a balance of high-level engineering rigor and a collaborative spirit; youll be a technical anchor and a supportive peer for teams across the organization.

What youll be doing:

Architecting, developing and optimizing scalable infrastructure for deploying security and networking AI models and agents in production.

Managing ML/agentic workflows to ensure performance, high availability, resource efficiency, and cost-effectiveness.

Designing and implementing pipelines and frameworks for AI training, inference, and experimentation.

Partnering with data scientists and security architects to operationalize AI agents, including packaging and integration with existing systems. This includes contributing to and reviewing code, design documents, and test plans.

Partnering with DevOps teams to integrate pipelines and workflows into CI/CD processes, ensuring reliable deployments and rollbacks.

Building proactive monitoring systems to identify issues in quality and infrastructure before they impact production.

Implementing access controls, authentication mechanisms, and encryption standards to keep our AI models and data secure.

Documenting guidelines and leading knowledge-sharing sessions to elevate the teams collective development expertise.

Requirements:
What we need to see:

BSc/MSc in CS/CE or related field (or equivalent experience).

At least 8 years of experience in ML engineering with a track record of deploying LLMs and agents to production at scale (including distributed environments).

Proficiency in Python and/or C++, with a deep understanding of ML/AI frameworks.

Hands-on experience with microservices, container orchestration, and cloud platforms for large-scale training and inference workloads.

Knowledge of ML training and inference optimization techniques.

Understanding of build infrastructure and CI/CD tools and practices (e.g. GitLab, GitHub Actions, Jenkins)

Experience with teaching and mentoring.

You are a proactive owner who takes pride in your work but remains humble and approachable. You believe that "how" we build is just as important as "what" we build.

Excellent collaboration skills, with the ability to explain complex infra concepts to non-technical stakeholders clearly and kindly.

Ways to stand out from the crowd:

Experience deploying and optimizing generative models and multi-agent systems for performance.

Deep systems knowledge (Linux internals, network protocols, or high-performance computing).

A background in security research, including knowledge of firewalls, intrusion detection, or network architectures.

This position is open to all candidates.

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8701273

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חברת השמה / כח אדם

07/06/2026

Senior AI Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

we are looking for a Senior AI Engineer to design and build production-grade, LLM-powered systems. You'll work at the intersection of software engineering and applied AI - shipping agents, RAG pipelines, and tool-using systems that solve real problems at scale. This is a hands-on, high-ownership role for someone who thrives at the frontier of what's possible with modern LLMs and isn't afraid to write the glue, the infrastructure, and the prompts that make it all work.
This is a **cross-functional, company-wide role**. You won't be embedded in a single product team - instead, you'll partner with every department to identify high-leverage opportunities and build AI-powered tools and workflows that boost productivity and efficiency across the entire organization.
This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence.
"our company's data management vision is the future of the market."- Forbes
we are the data platform company for the AI era. We are building the enterprise software infrastructure to capture, catalog, refine, enrich, and protect massive datasets and make them available for real-time data analysis and AI training and inference. Designed from the ground up to make AI simple to deploy and manage, our company takes the cost and complexity out of deploying enterprise and AI infrastructure across data center, edge, and cloud.
Our success has been built through intense innovation, a customer-first mentality and a team of fearless workers who leverage their skills & experiences to make real market impact. This is an opportunity to be a key contributor at a pivotal time in our companys growth and at a pivotal point in computing history.
What You'll Do:
- Design, build, and operate LLM-powered applications, agents, and workflows end-to-end - from prototype to production.
- Architect retrieval, context engineering, and tool-use strategies that make models reliable, accurate, and cost-efficient.
- Integrate LLMs with internal services, third-party APIs, and data stores to automate complex business and engineering workflows.
- Build, evaluate, and continuously improve evaluation harnesses for non-deterministic systems.
- Collaborate closely with product, research, and platform teams to translate ambiguous problems into shipped capabilities.
- Stay ahead of the rapidly evolving LLM ecosystem (models, frameworks, agentic patterns) and bring the best ideas into our stack.

Requirements:
Engineering Foundations:
- Strong Python skills- you write clean, idiomatic, well-tested code and understand the language deeply.
- Hands-on experience using coding agents(Cursor, Claude Code, GitHub Copilot, or similar) to build complex software systems. You know how to delegate effectively to AI assistants and review their output critically.
- Experience with multiple database paradigms- both SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Redis, DynamoDB, or similar). You can choose the right tool for the job.
- Experience designing and integrating with third-party APIs- REST and gRPC. Comfortable building robust clients, handling auth, retries, rate limits, and schema evolution.
- Production experience with Docker and Kubernetes- containerizing services, writing manifests, and debugging deployments.
- Strong Linux fundamentals- confident in bash and the terminal; you can navigate, script, and troubleshoot a server without reaching for a GUI.
- Experience building cloud-native tools on AWS, GCP, or Azure (compute, storage, queues, serverless, IAM).
AI / LLM Expertise:
- Solid understanding of what an LLM is and how it works- tokenization, attention, context windows, sampling, and the practical implications of each for system design.

This position is open to all candidates.

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8682766

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1 ימים

Senior AI Engineer-AI Research

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We are seeking a Senior AI Engineer to join our core product organization, where you will design, build, and scale next-generation AI systems powering real-world cybersecurity use cases across our diverse product portfolio (Posture, Detection, and CTI). This role focuses on developing production-grade systems leveraging LLMs, advanced machine learning, and agent-based architectures.
You will join a team within our Cyber R&D organization-leading the companys core product portfolio- while driving AI innovation and establishing engineering best practices across the domain. The team focuses on building and optimizing large-scale AI systems, including LLM-based solutions and advanced multi-agent workflows, working closely with data scientists and researchers to bring ideas into production.
Responsibilities
Design, build, and own end-to-end AI solutions- from data collection and preprocessing to model training, evaluation, and production deployment.
Optimize systems for performance, scalability, and reliability in production environments.
Collaborate closely with product, design, and engineering teams to identify and deliver AI-driven capabilities that address real customer needs.
Stay up to date with emerging AI/ML technologies, frameworks, and best practices, and apply them where they create real impact.
Work across the stack, contributing to backend systems and data pipelines that support large-scale AI applications.
Troubleshoot and resolve complex system issues, including performance bottlenecks, race conditions, and memory-related challenges.
Approach problems with a strong analytical mindset, delivering robust solutions while contributing to a high-performing, collaborative team environment.

Requirements:
Must-have:
5+ years of experience in backend or AI engineering with strong coding skills (Python preferred).
Proven experience building and deploying production-grade AI/ML systems.
Strong software engineering fundamentals (data structures, algorithms, system design).
Experience with distributed systems, microservices, and cloud platforms (AWS/GCP/Azure).
Hands-on experience with LLMs and generative AI, including prompt engineering and model integration.
Experience with LLM frameworks and agent orchestration tools (e.g., LangChain, CrewAI, ADK, or similar).
Strong debugging and problem-solving skills, with an ownership mindset.
Nice-to-have:
Experience with ML frameworks such as PyTorch or TensorFlow.
Experience with MLOps tools and practices (MLflow, Kubeflow, CI/CD for ML).
Background in NLP, LLM optimization, or agent-based systems in production.
Experience with large-scale data pipelines and NoSQL databases.
Experience with model evaluation, monitoring, and continuous improvement in production environments.
Contributions to open-source projects or research publications.

This position is open to all candidates.

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8725228

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5 ימים

AI Engineer, Exposure Management 25674

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We're looking for an AI Engineer who is equal parts builder, enabler, and visionary.
This is a rare opportunity to join a small, elite team at the ground floor and have outsized impact on how AI is designed, built, and shipped across a globally recognized cybersecurity platform.
If you thrive at the intersection of cutting-edge AI research and real-world production systems and you want your fingerprints on something that matters - read on.
Why Join Us?
Greenfield opportunity - you're not joining a mature team with fixed patterns, you're helping define them.
Real impact at scale - your work will influence products used by thousands of organizations worldwide.
A team of great people - small, senior, and genuinely collaborative.
Freedom to innovate - we encourage bold ideas, fast experiments, and honest feedback.
our company's AI moment - AI is a company-wide strategic priority, and this group is at the center of it.
*we are an equal opportunity employer committed to diversity and inclusion.
Key Responsibilities
What You'll Do:
Build AI infrastructure - Design and develop the foundational tools, frameworks, and pipelines that power the group's AI capabilities, with a focus on LLMs and Generative AI.
Enable AI across the team - Act as the group's AI enablement engine: establish best practices, create internal tooling, and uplift teammates to work effectively with AI systems.
Own AI agents & agentic workflows - Design, implement, and iterate on autonomous agents and multi-step AI pipelines integrated with a variety of tools and environments.
Bring AI to production - Take models and capabilities from prototype to production-grade systems - reliable, scalable, and observable.
Shape the big picture - Contribute to the group's AI strategy, not just its execution. We want someone who asks "why" before diving into "how."
Stay ahead of the curve - Continuously research and evaluate emerging AI techniques, models, and tools - and bring what's relevant back to the team.
Collaborate and communicate - Write clearly. Think clearly. Work closely with researchers, engineers, and product stakeholders to align on goals and drive outcomes.

Requirements:
Must-Haves:
5+ years of experience in Software Development in production environments
Relevant academic background or Army experience.
Strong hands-on experience with LLMs and Generative AI- prompt engineering, fine-tuning, RAG pipelines, evaluation, and beyond.
Proven ability to build and ship production-level AI systems - not just notebooks, but real, deployed infrastructure.
Experience building or working with AI agents - tool use, agentic frameworks (e.g., LangChain, LlamaIndex, AutoGen, or similar).
Excellent written and verbal communication skills - you can explain complex AI concepts to both engineers and non-engineers.
Strong command-line proficiency and comfort working across diverse tools and environments.
A growth mindset - you read papers, break things, and love learning.
Nice to Have:
Experience in AI enablement - building internal tools, templates, frameworks, or training that help others work with AI more effectively.
Background in cybersecurity or working with security data.
Familiarity with cloud-based ML infrastructure (AWS, GCP, or Azure).
Experience with observability and evaluation frameworks for LLM-based systems.
Mindset & Culture Fit:
Big-picture thinker - you zoom out to understand what the team is building toward and zoom in to execute.
Team player with ambition - you lift others up while pushing yourself and the work forward.
Self-driven - in a small team, you own your domain end to end.
Comfortable with ambiguity- we're building something new; not everything is defined yet.

This position is open to all candidates.

עדכון קורות החיים לפני שליחה

8721046

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28/06/2026

AI Lead

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We are looking for a visionary AI Lead to build our internal AI platform and architect adaptive intelligence systems that serve as a dedicated security architect for each of our customers. You will lead a team of AI Researchers and Engineers to move beyond simple integrations and build true autonomous security solutions.
What You Will Build:
Autonomous Workflows: Build agents that execute security workflows end-to-end, automating detection, investigation, and response processes.
Runtime Defense: Productize research into active runtime guardrails and defensive control mechanisms.
Internal AI Platform: Build the shared infrastructure for models, training, and evaluations to enable safe, scalable AI features across the organization.
Adaptive Intelligence: Oversee the development of models that learn from customer-specific environments to generate high-signal, personalized insights.
Responsibilities:
Lead the AI Research Group, managing AI Researchers, Engineers, and DevOps.
Own the intelligence engine end-to-end, delivering next-generation analytics and contextual visualization features.
Drive the strategic "build vs. partner vs. buy" decisions for cloud prevention and AI controls.
Collaborate with the Threat Team to develop AI-driven threat detections against emerging attack vectors and novel AI threats.

Requirements:
+6 years in the field of ML/AI engineering or science with proven products; cyber is an advantage.
Significant experience leading AI/ML engineering teams, preferably with a background in security or complex data environments.
Hands-on experience with LLMs, agentic frameworks, and building internal ML platforms.
Military background (e.g., 8200 or equivalent high-intensity technical leadership experience is a plus.

This position is open to all candidates.

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8712862

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חברת השמה / כח אדם

28/06/2026

Senior Staff Software Engineer - Agent Platform team

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

Were looking for people who are relentlessly curious and committed to continuous learning. AI is reshaping every function across our business, and we enable every team member, regardless of role or level, to build fluency in AI tools and concepts. Those who thrive here actively seek out new solutions, experiment thoughtfully, and apply what they learn to drive better, faster, smarter outcomes.
As a Senior Staff Software Engineer on the Agent Platform Detection team, you will be the technical visionary responsible for defining and evolving the architecture of our detection, triage, and response platform. You will lead the design and execution of backend systems and SaaS services that power alert propagation, alert lifecycle management, and response capabilities at extraordinary scale. Your technical leadership will bridge the gap between long-term architectural strategy and high-velocity product delivery, influencing how detection and response workflows are built and operated across our company's platform.
What Will You Do?
Primary responsibilities include:
Architectural Vision: Define and drive the long-term technical roadmap for the Agent Platform Detection domain, owning the architecture of backend systems that power alert ingestion, triage, lifecycle management, and response workflows across our company's SaaS platform.
System Design at Scale: Lead the design and implementation of highly available, cloud-native services that process billions of security events daily, ensuring alerts move reliably and efficiently from ingestion through investigation and action for the world's largest enterprises.
Technical Leadership & Influence: Act as a key stakeholder in cross-organizational architectural reviews, ensuring the Detection platform provides the extensibility, reliability, and observability that other product teams depend on. Drive alignment across engineering, product, and design on the technical direction of the team's feature area.
Full-Stack Depth: While backend-oriented, bring practical depth across the stack - owning and evolving frontend components in the company console built in React and TypeScript, and ensuring complex detection and response workflows are exposed in a clean, usable, and performant way.
Operational Excellence: Champion engineering best practices across the team, including advanced observability, alert health reporting, performance optimization, and the continuous improvement of runbooks, diagnostics, and incident response processes.
Mentorship & Growth: Elevate the engineering bar by mentoring Staff and Senior engineers, fostering a culture of technical excellence, accountability, and proactive problem-solving across the team.

דרישות:
Ideal candidates will have:
Extensive Backend Expertise: 12+ years of professional experience in backend development, with deep production-level mastery of Golang, Java, Python, or similar languages, and a strong track record of building and operating high-scale distributed services.
Platform Thinking: Proven experience building and evolving platforms - not just features - with a focus on API design (gRPC, REST), service boundaries, multi-tenancy, and shared infrastructure in a high-scale SaaS environment.
Full-Stack Capability: Practical frontend experience with React and TypeScript, with the ability to own production UI components and lead the frontend direction for a backend-heavy product area.
Data & Distributed Systems: Expert-level knowledge of RDBMS (PostgreSQL), query optimization, and extensive experience with high-throughput messaging systems such as Kafka and distributed caches such as Redis.
Cloud-Native Proficiency: Deep experience with AWS/GCP, Kubernetes, Docker, and modern CI/CD patterns in a hyper-scale SaaS environment.
Strategic Communication: Ability to articulate complex technical trade-offs to both technical and non-technical stakeholders, including Product Management, Directors, and VPs.
Cybersecurity Context: (Bonus) Familiar#ENG המשרה מיועדת לנשים ולגברים כאחד.

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8713789

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18/06/2026

Senior AI Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We are seeking a Senior AI Engineer to join a talented and fast-moving AI Engineering team. We're the central hub for AI across, driving innovation and putting AI to work for every team and product in the company.
AI already plays a foundational role in how we operate. It lets us ship features quickly and at scale, equips non-technical team members with tools that boost their productivity, and underpins much of the innovation happening across the company today.
If this kind of environment excites you - and if you believe great engineering means crafting the most effective and elegant solution within real-world constraints - we'd love to hear from you.
What You'll Be Doing:
Design, build, and maintain reusable AI capabilities - spanning models, tools, APIs, and platforms that support both internal operations and customer-facing products.
Develop and maintain our internal MCP server, giving AI agents easy and secure access to our extensive data stores.
Create and implement rigorous evaluation frameworks and AI guardrails to protect our value and ensure model reliability.
Cultivate deep expertise and establish sustainable AI engineering practices across the organization.
Champion AI readiness and track adoption company-wide to build lasting impact.
Build and optimize RAG (Retrieval-Augmented Generation) systems.
Own projects end to end - from gathering requirements from non-technical stakeholders through development, deployment, and ongoing operation.
Serve as a consultant and advocate for AI engineering, guiding other teams in leveraging the platforms and tools you create.
Collaborate with teams throughout to accelerate AI adoption and productization.

Requirements:
5+ years of solid backend and server-side development experience, building complex and highly scalable systems.
Proven proficiency in at least one general-purpose language (Python preferred, though not required).
A natural collaborator who builds trust across functions - comfortable working with product, business development, account management, and other non-technical partners, and able to translate between their needs and technical solutions.
Strong product-oriented thinking, with the ability to elicit, refine, and prioritize requirements from non-technical stakeholders.
A deep sense of ownership, some DevOps experience, and the drive to develop, deploy, and operate projects from start to finish.
Able to navigate an organization and influence without authority - communicating effectively with engineers and managers as well as VP and C-suite leadership.
A bias toward driving change: you spot opportunities to improve processes and accelerate technology adoption, and you act on them.
High proficiency with AI-assisted coding tools such as Copilot, Cursor, or equivalents.
Hands-on experience with public cloud platforms (AWS, GCP, or Azure).
Fluency in written and spoken English.
Bonus Points If You:
Are experienced with agentic coding tools like Claude Code or Copilot CLI.
Have familiarity with Strands Agents (or comparable agentic frameworks), RAG architectures, and Bedrock.
Have worked with MCP (Model Context Protocol).
Are comfortable operating in containerized environments.

This position is open to all candidates.

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1 ימים

Senior AI Platform Engineer - Sovereign AI Engineering

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

Required Senior AI Platform Engineer - Sovereign AI Engineering
The Dream Job
It starts with you - an engineer driven to build the agentic AI platform that turns LLMs into reliable, production-grade capabilities. You care about clean APIs, well-defined service boundaries, and systems that teams can build on with confidence. We are AI-first across the board - every team builds and operates agents. You'll architect and ship the platform that makes this possible: agent orchestration frameworks, LLM gateways, evaluation pipelines, tool-calling infrastructure, and retrieval systems. Without this platform, agents don't ship - you own the layer that turns AI research into Sovereign AI products, deployed across cloud and on-prem environments.
If you want to make a meaningful impact, join our mission and build the agentic AI platform that drives Sovereign AI products - this role is for you.
Responsibilities
Design and build agentic systems - single and multi-agent workflows with planning, memory, context engineering, and tool use - for both internal automation and product-facing autonomous capabilities operating over long time horizons.
Build and operate the AI platform layer - LLM gateways, prompt management, structured output handling, tool-calling infrastructure, and cost/latency optimization - deployed on Kubernetes, consumed by every team for their agentic work.
Own the agent framework layer - orchestration primitives, execution environments, state management, and sandboxed tool execution - giving every team the building blocks to create and operate their own agents.
Build evaluation infrastructure that gives teams confidence in agent behavior - automated LLM and agent evals for quality, correctness, safety, latency, cost, and regressions, including human-in-the-loop oversight for mission-critical workflows.
Productionize and harden backend services (APIs, gRPC, async workers) that integrate LLMs - with proper error handling, retries, circuit breakers, and high-availability patterns.
Own RAG pipelines and retrieval systems - indexing, chunking, embedding, vector database management, filtering, and relevance tuning for production retrieval.
Optimize performance and cost across the AI stack - model routing, caching, batching, and inference cost management.
Ship shared tooling - libraries, SDKs, agent templates, and documentation - while working closely with ML Platform, Data Platform, DevOps, and other teams across the Applied AI Engineering group. Own architecture, documentation, and operations end-to-end.

Requirements:
5+ years in backend or distributed systems engineering, with 2+ years focused on production systems that integrate AI/ML models or LLMs.
Engineering craft - Strong Python, Go, or Java, system architecture, API design, testing, and secure coding practices.
Agentic systems - Experience designing and building agent orchestration, tool-use systems, and autonomous workflows; familiarity with frameworks like LangGraph or similar, or having built equivalent from scratch
Backend engineering - Experience building production APIs and services (FastAPI or similar); async programming, service architecture, high-availability, and reliability patterns (retries, circuit breakers, backpressure)
LLM integration - Hands-on experience integrating LLMs via SDKs and APIs; context engineering, structured outputs, tool calling, and model routing
RAG & retrieval - Experience with embedding pipelines, vector databases (e.g., Milvus, Qdrant, Pinecone), chunking strategies, and relevance tuning
Evaluation & observability - Experience designing LLM and agent evals, monitoring AI system quality, and building observability for non-deterministic systems
Nice to Have:
Platform & infra - Kubernetes, AWS, Terraform or similar IaC, CI/CD, container orchestration, deploying and operating production services
Experience with MCP or similar tool-use protocols for agent-to-service communication.

This position is open to all candidates.

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8725214

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