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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are seeking talented, motivated AI builders to join our Strategic Initiatives team as part of a new AI Center of Excellence. Reporting to the Sr. Director of Engineering, this team designs and ships AI-native solutions - agents, assistants, and reusable skills - that advance our security mission and multiply the impact of teams across the company.
This is a builder role. We're looking for experts engineers fluent in modern AI application development - agent frameworks, harnesses, tool use, prompting, retrieval, and evaluation - not machine learning engineers. You will be expected to train foundation models / frontier models . You will compose capable, production-grade AI systems on top of frontier models, get them into people's hands, and bring the rigor to prove they actually work.
What you'll do:
Design, build, and bring to production ready: models, AI agents, assistants, and reusable skills that solve real problems for us and our customers.
Turn ideas into working MVPs fast, then partner with engineering to harden them into reliable, production-ready systems.
Build evaluation into everything you ship - define what "good" means for each solution, measure it, and hold the bar. Due diligence through rigorous evals is non-negotiable, not an afterthought.
Compose agentic workflows that are secure by construction, using secure harnesses along with appropriate isolation, guardrails, and controls.
Select and integrate the right frameworks, tools, and models for each job, and turn what works into reusable patterns and best practices for the COE.
Also be a part of the COE Consult team to help across the organization.
Document what you build and how it should be used, operated, and evaluated.
Requirements:
An AI Expert in Multi-agentic solutions.
Demonstrated experience building real AI solutions - agents, assistants, copilots, or skills - that shipped and got used, not just prototyped.
Deep, hands-on familiarity with modern agent frameworks and developer tooling (agent SDKs such as the Top 3 providers SDKs (Claude, OpenA and Google), thorough understanding and use of SKILL.md skills standard, plus the judgment to know which to reach for when.
Strong evaluation discipline: building test sets, defining metrics, and measuring quality, safety, and reliability before and after deployment.
Proficiency in Python and comfort integrating APIs, tools, and cloud services (AWS, Azure, or GCP) with containerization (Docker, Kubernetes).
Bachelor's or Master's in Computer Science, Engineering, or a related field, or equivalent professional experience.
Preferred:
Experience in security, or building AI for security use cases
What this role is not:
A machine learning / model-training role. We are not hiring ML engineers or building training pipelines.
This position is open to all candidates.
 
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02/07/2026
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.
 
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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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22/06/2026
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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21/06/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time and Hybrid work
You will manage the AI Platform Engineer(s), set the technical standards for the AI Power User group's citizen development program, and serve as the connective tissue between business leadership, platform owners, and development teams. You will shape the multi-year AI architecture roadmap while also rolling up your sleeves to conduct architecture reviews, resolve blockers, and move use cases from concept to production. This is a role for someone who can think big and execute - and who understands that in an enterprise context, the quality of your governance is inseparable from the quality of your architecture.
What You'll Own
Strategy & Architecture
Define and own the enterprise AI integration strategy - identifying opportunities to embed intelligent automation, agentic workflows, predictive analytics, and generative AI capabilities across our core platforms
Develop and maintain reference architectures, design patterns, and the AI architecture decision log that governs how AI models connect to enterprise systems and what they are permitted to do
Consult on enterprise system architecture and implement best practices for the Enterprise Business Systems team to leverage in their day-to-day execution.
Lead Proof-of-Concept initiatives for new AI tools and platform-native AI features, evaluating them against build-vs-buy criteria before recommending adoption
Partner with business stakeholders to translate operational pain points into AI use cases with clear ROI framing and sequencing criteria
Contribute to our enterprise data strategy, ensuring AI initiatives are supported by clean, accessible, and well-governed data pipelines
Integration Architecture & Delivery

Design and own the Workato eMCP layer - the MCP governance model, persona-scoped token framework, workspace isolation strategy, and the single sanctioned action surface through which all AI agents write back to enterprise systems
Define integration patterns and standards for AI model connectivity (Claude, ChatGPT) to Salesforce, NetSuite, HiBob, and Jira - specifying what agents can read, what they can write, through which surfaces, and with what confirmation and audit requirements
Requirements:
8+ years of experience in enterprise solutions architecture, systems integration, or a closely related discipline - with a strong track record of designing and delivering production-grade integration platforms at scale
Deep hands-on expertise with Workato or a comparable enterprise iPaaS platform (MuleSoft, Boomi, Azure Integration Services) - including workspace design, governance configuration, and operational management
Demonstrated experience building and integrating across CRM (Salesforce preferred), ERP (NetSuite preferred), and iPaaS platforms at the enterprise level - in production, not just proof-of-concept
Hands-on experience designing or deploying AI/ML features in production enterprise environments - including at least one of: agentic AI systems, LLM-powered workflows, predictive analytics, or intelligent document processing
Strong command of integration patterns: REST/GraphQL APIs, event streaming, ETL/ELT pipelines, webhook-based automation, and API security best practices
Experience designing and enforcing integration governance: access control models, audit logging, approval workflows, and token management
Familiarity with Model Context Protocol (MCP) or direct experience connecting AI models to enterprise systems in a production context
Proven ability to lead distributed technical teams and communicate architecture clearly to both executive sponsors and engineering teams - you can hold a technical standard without becoming a bottleneck
Experience with the requisite AI-related Audit Management frameworks (ISO42001, ISO27001, SOC 2, etc.)
This position is open to all candidates.
 
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14/07/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We're looking for a Senior Applied AI Scientist to sit at the frontier of AI security - turning emerging threats into the detection models that protect how AI is used inside the world's largest organizations. You'll be part of the AI Security Research department, working hand-in-hand with security researchers to translate threat intelligence into trainable signals that catch malicious behavior and security risks across the AI-powered workflows of Fortune 500 companies.
You'll bring deep technical versatility - reaching for classical ML, deep learning, or agentic based approaches based on what the problem demands, and the evaluation rigor to know when a model is truly ready for the real world. If you want to define what AI security engineering looks like, not just practice it, this role is for you.
What Youll Do:
Build, train, and ship detection models end-to-end, from raw data to production
Choose the right method for each problem - traditional ML, deep learning, fine-tuned LLMs, agents or heuristics - based on theoretical insights turned into practical results.
Partner with security researchers to turn security research outputs and domain expertise into detection capabilities
Own evaluation: design benchmarks, build labeled datasets, and define production standards
Monitor models in production across all paradigms - ML, deep learning, LLM-based, and agentic systems to track degradation and ensure reliability
Iterate fast, with a tight feedback loop between model performance and product outcomes
Requirements:
5 years of hands-on ML and deep learning experience, with a track record of shipping, debugging, and diagnosing models in production
Data-first mindset: you know how to define the right evaluation criteria for each model - before and after shipping, to ensure it delivers real quality and value in production
Hands-on experience building and deploying agentic AI systems to production
Proficiency in Python; experience with PyTorch, scikit-learn, HuggingFace, or equivalent
Practical, applied mindset - focused on the problem, success metrics and impact, not lab research.
Background in security, trust & safety, or content moderation - an advantage
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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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We're looking for exceptional backend engineers who understand modern AI systems and enjoy building the infrastructure and products around them.
Our team is creating the foundational technologies that allow AI agents to operate safely, securely, and reliably at scale. This includes building secure agent control planes, embedded controls, developer tooling, observability, and infrastructure that enables production-ready AI systems.
This is a hands-on engineering role for someone who enjoys building products from the ground up. You'll partner closely with AI researchers and backend engineers to rapidly move ideas into production.
What You'll Do:
Design and build secure AI infrastructure for production AI agents.
Develop Agent Control Plane capabilities that manage, monitor, and secure agent execution.
Build embedded controls and security mechanisms directly into AI agents.
Develop reusable services, APIs, and developer tooling that support AI applications.
Build and maintain integrations with modern Agent SDKs and Model Context Protocol (MCP).
Design backend microservices using Python and AWS.
Build observability into AI systems, including telemetry, monitoring, tracing, and operational visibility.
Develop public-facing developer tools and command-line interfaces (CLI).
Partner closely with AI researchers to rapidly transition prototypes into production-ready systems.
Own projects from architecture through deployment.
Help define engineering standards and reusable patterns across the AI platform.
Collaborate with senior engineers while independently leading technical initiatives when appropriate.
Requirements:
Required
6+ years of professional software engineering experience.
Strong backend engineering background.
Excellent Python development experience.
Experience building backend services and microservice architectures.
Experience working with AWS cloud services.
Experience designing APIs and distributed systems.
Hands-on experience building AI applications, AI agents, or agentic workflows.
Experience working with Agent SDKs.
Familiarity with Model Context Protocol (MCP).
Experience building developer tools, APIs, or CLI applications.
Strong understanding of software architecture and production engineering.
Comfortable working in startup environments with significant ownership.
Ability to independently drive projects from concept through production.
Security engineering background.
Preferred Qualifications:
Experience building Agent Control Planes.
Experience implementing embedded controls or policy enforcement within AI agents.
Experience building AI observability platforms.
Infrastructure engineering background.
Experience building secure AI systems.
Experience working with LLMs in production environments.
Experience with Kubernetes and containerized services.
Experience integrating AI systems with cloud infrastructure.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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18/06/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We're hiring a software engineer to work directly with our business teams - finance, sales, legal - building tools and automations that help them do their jobs better. You'll write production code and own what you build, but most of your time will be spent understanding business processes and how to impact them.
Most business teams have more day-to-day operational pain than they realize, and a lot more they could be doing with AI than they know. Your job is to find those gaps and build something that fixes them. Success looks like the team being able to move faster and spend their time on the work that matters, because everything else just runs.
You'll have a lot of autonomy in this role. You'll decide what to work on, build it, ship it, and see whether it actually made a difference. You'll be doing this as part of a small, senior AI team, so while the day-to-day work is independent, you'll have other engineers to collaborate with and a shared bar for how we build things.
What You'll Be Doing:
Build & Engineer:
Take the lead on technical implementation and be the owner of how it all works - picking the right tool for the job (code, no-code, or otherwise) and keeping the knowledge of the system in your handsDesign and deliver end-to-end AI solutions - from first stakeholder conversation through production deployment and iteration
Implement LLM-powered systems: RAG pipelines, AI agents, multi-step automations, and tool-integrated workflows
Integrate solutions with enterprise systems (Salesforce, NetSuite, Slack, Data platforms) and build for production: observable, reliable, and cost-optimized
Embed With the Business:
Work directly with Finance, Sales, HR, Legal, and Customer Success to identify and scope high-leverage AI opportunities
Translate ambiguous business needs into concrete engineering plans; own both the solution definition and the build
Help business stakeholders develop AI fluency and become stronger partners over time
Requirements:
Engineering Skills:
4-6+ years of software engineering experience with a track record of shipping production systems
Hands-on experience with AI orchestration frameworks: LangChain, LangGraph, LangFlow, or similar (LlamaIndex, CrewAI, AutoGen)
Strong Python skills and hands-on experience building AI-powered applications in production
Deep knowledge of LLMs, RAG architectures, agent patterns, tool use, and prompt engineering
Experience with vector databases and semantic search (Pinecone, Weaviate, pgvector, or similar)
Solid fundamentals: API design, microservices, data pipelines; cloud experience (AWS) is an advantage
The Differentiators:
People person - you genuinely enjoy working with non-technical colleagues and build trust naturally with stakeholders at every level
Can-do mindset - you find a way and ship, rather than waiting for perfect conditions
Team player - you operate with autonomy but share context, invite feedback, and make those around you better
Self-taught by nature - you learn new frameworks in days and apply them in production; you dont wait for someone to tell you whats next
Outcome-obsessed - you measure success by business impact, not technical elegance
Nice to Have:
Experience with automation platforms (n8n, Workato, or similar)
Familiarity with enterprise tooling ecosystems (Salesforce, NetSuite, BI, HRIS)
Background in solutions engineering, technical consulting, or product management.
This position is open to all candidates.
 
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8700931
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25/06/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
we are building the technical layer that brings AI-native code quality into real engineering workflows. As our partnership ecosystem grows, were looking for a principal-level engineer to turn strategic integrations into shipped products.
In this role, youll be a technical visionary and builder. You will design and implement the next generation of Model Context Protocol (MCP) servers, APIs, and platform integrations for key strategic partners like cloud providers, Anthropic, Cursor, and OpenAI. This is a high-leverage role where your expertise will directly shape how our company- the missing quality-focused system-plugs into the complex, autonomous, multi-agent development environments of tomorrow.
Ideal for someone who thinks deeply about developer experience, moves fast, and enjoys building technical infrastructure that scales through partnerships.
Mission: Make our companyunavoidable across the Agentic SDLC. Own the integration playbook that brings our company into every critical developer surface - IDEs, repos, CI/CD, code review, cloud platforms, and the AI agents shaping how software gets built. Build the technical layer that turns our company into the default quality, governance, and trust gate across the SDLC, translating cutting-edge research into integrations that scale, ship, and become embedded in how teams work.
Responsibilities
Wrap our companys capabilities as a public, composable surface. Turn our company Review, Aware, and Skills into clean, documented building blocks that any partners engineering team can adopt without hand-holding. Treat the public API, SDK, and MCP surface as a product - versioned, stable, well-documented, and obsessively focused on DX.
Be the engineering counterpart on partner conversations. Sit shoulder-to-shoulder with the Product Partnerships Lead in partner discussions. Translate ambiguous we want to integrate conversations into concrete technical scopes, integration paths (MCP vs. SDK vs. API), and shipping timelines. Be credible enough that a partners principal engineer takes the conversation seriously the first time.
Ship marketplace and cloud integrations. Own the technical execution behind cloud marketplace launches (AWS, Azure, GCP) - deployment artifacts, SaaS metering, private offer plumbing - so the commercial motion is never bottlenecked by engineering.
Define the integration playbook. Make the path from new partner interested to integration live repeatable. Document the patterns, build the reusable primitives, and reduce the per-partner engineering cost over time so the team can scale partnership volume without scaling headcount linearly.
Hold the DX bar across every partner-facing surface. Docs that work the first time. SDKs that dont surprise. Errors that explain themselves. Examples that run. If a partners engineer cant get to hello world
Requirements:
5+ years of backend or platform engineering experience, with at least 2 years building developer-facing products (SDKs, APIs, integrations, or open source libraries that external engineers consumed)
Preferable to have worked at or with AWS, Microsoft Azure or Google Cloud specifically on dev related products
Shipped production integrations with third-party platforms - point us to the code, the package, or the partner that went live because of you
Practical, hands-on fluency with MCPs and SDKs
Strong API design instincts - knows when to wrap vs. expose, when to version, when to break compatibility, and how to make errors that explain themselves
Comfortable in customer-facing technical conversations - can scope an integration with a partners principal engineer in a 30-minute call and walk out with a working spec
Ships fast under ambiguity - has a track record of going from partner asked for X to something working in days, not sprints
Owns the full lifecycle: design, code, docs, release, support. No throwing things over the wall.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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8711460
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מודים לך שלקחת חלק בשיפור התוכן שלנו :)
Location: Tel Aviv-Yafo
Job Type: Full Time
we are looking for a Staff AI Engineer, Innovation.
As a Staff AI Engineer in global CTO group, you will play a central role in building the next generation of AI-powered security capabilities across product portfolio. This role is focused on rapid prototyping, experimentation, and innovation, turning emerging ideas into working product features that can scale across multiple products and technology stacks.
You will design and build AI-driven systems end-to-end, from agent-based workflows and model integrations to backend services, data pipelines, and product-facing capabilities. You will work closely with product, engineering, and research teams across the company to explore new use cases, validate ideas quickly, and bring impactful AI features into production.
This role is ideal for an experienced AI engineer who enjoys moving fast, working across boundaries, and building real production systems, not just experiments. Your work will directly influence how AI is embedded across platforms and how customers experience secure AI at enterprise scale.
Requirements:
8 or more years of professional experience in software engineering, with significant hands-on experience in AI engineering or applied machine learning.
Strong expertise in building AI-powered systems, including LLM-based applications, agents, and orchestration workflows.
Proven experience integrating and operating AI and ML models in production environments.
Proficiency in multiple programming languages, including Python and at least one of the following: .NET, Go, or similar backend languages.
Experience working across diverse technology stacks and product architectures.
Solid understanding of backend system design, APIs, and distributed systems.
Strong experience with databases, including data modeling, performance considerations, and working with both relational and non-relational systems.
Practical experience with DevOps practices, including CI/CD pipelines, containerization, and cloud-based deployment.
Comfort working in cloud environments and modern infrastructure platforms.
Ability to rapidly prototype, iterate, and evolve ideas into production-ready features.
Strong ownership mindset, curiosity, and ability to collaborate across teams.
Nice to Have:
Experience designing and building AI agents for real-world workflows.
Hands-on experience training, fine-tuning, or evaluating machine learning models.
Familiarity with MLOps practices and model lifecycle management.
Experience working in security, cloud platforms, or large-scale SaaS products.
Ability to communicate complex AI concepts clearly to both technical and non-technical audiences.
This position is open to all candidates.
 
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8739952
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