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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
we are looking for a AI Transformation Engineer.
You'll join the AI Platform team, the group building the AI infrastructure, agentic workflows, and tooling that power R&D organization. Our mandate is to make the entire software development lifecycle faster and smarter with AI, and we're a small, hands-on team that ships real systems, not pilots
This isn't a role where work arrives as tickets, and it isn't a prompt-engineering role. You'll own a set of KPIs the team is driving, and it's on you to turn a fuzzy goal into something measurable: figure out what actually needs to be built, define how you'll know it's working, and build it. That means talking to engineers, understanding where the SDLC breaks down, and turning that into agentic workflows and platform capability that ship and hold up over time.
Requirements:
6-8+ years of hands-on experience in senior software engineering positions.
Hands-on experience building and shipping agentic workflows or LLM-powered systems in production, not just prototypes.
Real experience working across agent harnesses (e.g., Claude Code and similar), and hands-on understanding of agent context: how it's built, scaffolded, and kept effective at scale.
Practical understanding of the actual building blocks: LLMs, RAG, tool use, evaluations, and human-in-the-loop patterns, not just theoretical familiarity.
Strong software engineering fundamentals: you can design, build, and operate a system end to end.
A demonstrated ability to work without a pre-defined spec: given a goal or a KPI, you can find the problem, scope the solution, and build it.
Product judgment: you can separate what's worth building from what isn't, and you know how to tell whether it actually worked.
Strong discovery skills: you can sit with engineers, map how work actually happens today, and identify where automation genuinely helps versus where it doesn't.
Strong communication skills: you can translate between technical tradeoffs and the people who need to understand the impact.
Advantages
A cost-aware mindset: you treat tokens like a resource to be managed, not an afterthought.
Experience building on top of Kubernetes, containers, or CI/CD infrastructure in production.
Experience with MCP-based tooling, agent orchestration frameworks, or LLM gateways.
Familiarity with observability tooling (e.g., Datadog) for monitoring agent or platform health.
Background in a fast-paced, high-growth B2B SaaS environment.
Exposure to health tech, healthcare institutions, or behavioral health.
This position is open to all candidates.
 
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4 ימים
Location: Tel Aviv-Yafo
Job Type: Full Time
our company's product is built around an AI agent that security analysts and detection engineers work with directly. It investigates coverage questions against live enterprise security data, authors and tests detection logic, and tunes noisy alerting.
That agent is already in production with enterprise design partners. Now we need to make it dependable and scalable enough for GA.
You will own that evolution: the agent architecture, its evaluation and quality system, and the production engineering around it. This is a hands-on senior IC role with real architectural authority - you set the technical direction and you write the code.
The agent operates inside customer security environments, where a wrong action can become a customer incident. Correctness, isolation, observability, and evaluation are not polish. They are the product.
What you'll be doing
Agent architecture: Design the evolution from today's production single-agent system to a multi-agent one: orchestration, task decomposition, runtime and framework choices, and a migration path that does not break what design partners already rely on.
Agent capability: Own the prompts, context, skills, and tool design that make the agent genuinely good at detection engineering across multiple security platforms, not just plausible-sounding.
Evaluation platform: Build the harnesses, judges, and golden datasets that turn "the agent feels better" into a number, plus the CI gates that keep regressions from shipping.
Reliability and safety: Keep long-running agentic sessions healthy in production, and build the isolation and guardrails required of an agent working inside enterprise security environments.
Production debugging: Work real failures from production traces, and turn each one into an eval case that can never regress silently.
Technical direction: Make the calls on architecture, sequencing, and quality bar and be accountable for the outcome, including raising how AI-natively the whole team builds.
Cross-team partnership: Partner with product and customer-facing teams on what the agent should do, and with platform teams on the data and integrations it depends on.
Requirements:
Senior engineering depth: You have 6+ years of experience building and operating production software, with strong backend and distributed-systems fundamentals and experience designing APIs and services.
Shipped agents, not demos: You have taken an LLM agent system with tool use, multi-turn interaction, and planning to real users, and you can talk concretely about how it failed and what you did about it.
Architectural judgment: Informed opinions on single-agent vs. multi-agent design, orchestration patterns, and the current framework and SDK landscape, with the pragmatism to pick the boring option when boring wins.
Eval discipline: You have built or owned evaluation for an LLM system, including golden datasets, LLM-as-judge with calibration, and regression gates in CI, and you can quote the metrics you moved.
Tool design instincts: You know when a deterministic tool beats a model call, how to design tool contracts an LLM will not misuse, and how to keep cost and latency under control.
Distributed systems fluency: Streaming, stateful services, and the operational instincts to keep long-running agent sessions alive in production.
Ownership in ambiguity: You can lead an area as a hands-on IC in an early-stage environment with little existing structure. Security domain experience such as SIEM platforms, SOC workflows, detection engineering, or security query languages, and experience with modern agent SDKs and protocols such as MCP, are strong advantages.
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.
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.
Strong grasp of modern patterns for integrating LLMs into real workflows, including RAG, MCP (Model Context Protocol), vector databases, agents, tool use, and context engineering- with hands-on experience building with several of them.
- Production experience implementing LLM-powered systems end-to-end, using relevant tools and frameworks (e.g. LangChain, LlamaIndex, LangGraph, Haystack, Pydantic AI, vector stores like Pinecone/Weaviate/pgvector, observability tools like LangSmith or Langfuse).
- Solid foundation in core ML concepts; embeddings, evaluation, overfitting, generalization, and how classical ML relates to and differs from modern LLM-based approaches.
Nice to Have:
- Experience fine-tuning or distilling open-source models.
- Contributions to open-source AI/ML projects.
- Experience with streaming, real-time systems, or low-latency inference.
- Familiarity with prompt evaluation frameworks and LLM-as-judge methodologies.
This position is open to all candidates.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
Required GTM AI Engineer
About the role:
Our Revenue Operations team has already begun experimenting with AI agents and automation across the go-to-market lifecycle. Weve seen enough to know there is a much bigger opportunity.
Now were looking for an AI builder to take that from experimentation to a real capability across the Go To Market teams.
Youll identify high-value opportunities, build and deploy AI-powered workflows and agents, create the foundations that allow them to operate safely in production, and help define how AI becomes part of the everyday operating model for our GTM organization.
This is a hands-on builder role with broad ownership. Youll work across Sales, Solutions, Customer Success, Marketing and RevOps, combining engineering ability with a strong understanding of how commercial organizations actually work.
What you'll do:
Build AI into the GTM lifecycle- Design and ship agents, automations and AI-powered workflows across areas such as prospecting and enrichment, lead management, account planning, deal support, approvals, pipeline management, forecasting, call intelligence and expansion.
Turn prototypes into production systems- Take promising internal experiments and build them into reliable services that can be used across the organization. Youll work with our engineering and DevOps teams to make sure what we build is secure, maintainable and scalable.
Design for trust and appropriate autonomy- Define where AI can act independently, where people should remain in the loop, and how those boundaries are enforced. Youll build the evaluation, monitoring, permissions and audibility needed for agents that interact with real commercial systems and data.
Build on strong data foundations- Agents are only as useful as the systems and data they can rely on. Youll work across our CRM, GTM tools and data warehouse to improve how information is connected, structured and made available to AI-powered workflows.
Measure real business impact- We care less about the number of agents shipped than what they change. Youll measure impact through outcomes such as faster cycle times, better data quality, higher productivity, improved conversion or time returned to teams - and communicate that impact clearly to the business.
Make the whole organization more capable- You wont be the only person building with AI. Part of your role is creating the patterns, tooling and standards that allow others to build safely and effectively - while making it easy for the wider organization to discover, trust and use what has been created.
דרישות:
3-7 years of relevant experience, in roles such as GTM Engineer, AI GTM Engineer, RevOps Engineer, Business Applications Engineer, a Solutions/Sales Engineer with a strong technical background, an AI-forward Salesforce Developer, or a Forward Deployed Engineer.
Strong engineering ability. You can take an idea from prototype to working production system, integrate with APIs and existing applications, and make pragmatic technical decisions along the way.
Hands-on experience building with LLMs and agents. Youve built systems involving tool use, structured workflows, context management, retrieval, agent frameworks or similar approaches, and understand how to evaluate whether they are actually working reliably.
Production mindset. Youre comfortable deploying and operating cloud-based services and working with concepts such as authentication, permissions, CI/CD, secrets, monitoring and observability.
Integration experience. Youre comfortable working with REST APIs, webhooks, OAuth, Slack applications, SQL and data warehouses.
Good judgment about AI autonomy. You understand the difference between generating an answer and taking an action, and know how to design systems appropriately when AI interacts with important business processes.
Commercial curiosity. You naturally look for high-leverage problems. You can understand a workflow, determine whether it is worth automating#E המשרה מיועדת לנשים ולגברים כאחד.
 
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23/09/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
we are looking for a Senior AI Builder to take AI from a "promising demo" to real production systems that customers rely on - and that continue to work well over time. Our R&D group is a team of 12 engineers and one architect, spanning backend to mobile, building the accounting platform businesses actually run on every day.
What you'll do
* Build and ship LLM-powered AI capabilities to production- agentic flows, retrieval over our data, extraction from real-world documents, and more. Solutions need to be accurate, measurable, cost-efficient, and rollback-ready.
* Build and lead the evaluation process - continuously measure the quality of models and solutions, and be able to answer clearly: is the new version actually better than last week's?
* Own whatever it takes to get the solution into production- from AWS Lambda to Vue and PHP. You don't need to be an expert in every technology, but you should be comfortable getting into the code and solving problems wherever the work actually lives.
Why this is a real challenge - and why it's worth it Our customers trust us with their financial data. There's no room for "almost right" when it comes to the answers our systems provide, and we operate in an environment with significant regulatory requirements- including PCI-DSS, GDPR, and Israeli privacy law. The goal is to take AI capabilities, turn them into real products people can trust, and see them reach customers- at a company small enough that your work can ship this quarter, not next year.
Advantages:

* Experience with Databricks/Spark, Vue 3, fintech or another regulated domain, and significant experience with AI-powered development tools and agentic development.
Requirements:
* 5+ years of experience building and operating production systems - real hands-on experience building software, shipping it to production, and operating it over time.
* Significant hands-on experience building with LLMs- including dealing with challenges like retrieval quality degrading, agent loops running out of control, token costs spiking, and reliability and accuracy issues.
* Strong TypeScript or Python skills and comfort with AWS serverless.
* The engineering judgment to tell a stakeholder: "This isn't an AI problem."
This position is open to all candidates.
 
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31/08/2026
חברה חסויה
Location: Tel Aviv-Yafo and Netanya
Job Type: Full Time
We're seeking a hands-on AI Solutions Specialist to lead the development and implementation of enterprise-wide AI applications. In this pivotal role, you'll evaluate and deliver cutting-edge AI solutions to employees and teams across the organization. You'll spearhead AI solution projects from initial concept and gathering requirements through execution and widespread adoption, serving as the central point of contact between business, IT, and data teams. You'll also be at the forefront of the latest AI technologies.

As an AI Solutions Specialist you will
Partner directly with cross-functional and non-R&D teams to understand workflows, pain points, decision-making processes, manual tasks, and operational bottlenecks - diagnosing where GenAI and AI Agents can provide real, measurable value.
Translate ambiguous business problems into clear AI use cases, MVP definitions, solution designs, success metrics, and rollout plans.
Lead the lifecycle of GenAI-driven applications and Agents, transitioning rapidly from initial concept and technical feasibility to full enterprise-grade production rollouts.
Build and configure AI-powered solutions, including agentic workflows, workflow automations, RAG-based tools, decision-support tools, and integrations with internal systems.
Conduct technical audits of emerging AI technologies, leading "Build vs. Buy" analyses to ensure global scalability, security, and measurable value to the organization.
Run training and enablement sessions for both technical and non-technical teams, fostering a culture of AI literacy and ensuring the organization can leverage new tools effectively.
Build and evolve the Enterprise AI technology stack, continuously scouting and integrating next-generation platforms, LLM orchestration tools, and agentic frameworks.
Serve as the primary technical liaison between IS, IT, Legal, and Data teams to ensure AI solutions are securely integrated and compliant with enterprise standards.
Be a product owner of enterprise AI platforms, driving continuous solution adoption, impact measurement, and performance optimization across the organization.
דרישות:
5+ years in a technical role such as software engineering, solutions engineering, automation engineering, AI engineering, business application implementation, or a similar hands-on role, including 1+ years delivering AI, GenAI, agentic, or automation solutions for business or operational users.
A clear builder track record: you have shipped tools, automations, workflows, internal products, or prototypes that people actually used.
Deep, hands-on understanding of the LLM lifecycle, including Prompt Engineering, Retrieval-Augmented Generation (RAG), fine-tuning strategies, AI agents, tool use, human-in-the-loop workflows, evaluations, and responsible AI patterns.
Proven experience in implementing Enterprise GenAI platforms (e.g., Gemini Enterprise, Claude Chat).
Hands-on experience developing agentic workflows on top of agentic framework tools like Google ADK, AgentCore, and low-code platforms (Workato)
Proven experience developing GTM-related projects, mainly around sales and marketing.
Proven knowledge of GTM best practices and technology.
Proven project management skills and a demonstrated product management mindset, including the ability to define MVPs, prioritize, separate nice-to-have ideas from high-value use cases, and measure outcomes.
Strong discovery skills with non-technical stakeholders: you can map how work happens today and redesign it around AI, automation, and human accountability.
Excellent communication skills: able to explain technical tradeoffs to business stakeholders and business context to technical teams, and to run training and enablement sessions.
Strong ownership and execution, with creative, out-of-the-box thinking: comfortable moving from ambiguous problems to working solutions, with a focus on business impact and the ability to run and react fast.
Full-stack Web development experienc המשרה מיועדת לנשים ולגברים כאחד.
 
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22/09/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
You'll be a senior engineer on a deliberately flat, entrepreneurial team. Day to day you'll design and build agentic AI systems - agents, workflows, the orchestration layer that ties them together, and the infrastructure that makes all of it reliable at scale. This is hands-on building, not oversight.
What you'll do
Design and build agentic workflows and the AI systems behind them - agents, the orchestration layer, and the infrastructure that runs them reliably
Take significant, ambiguous areas of the system and drive them from rough idea to working capability
Help scale the platform from a first working workflow to something used across the marketing organization
Contribute to evaluation, quality, and reliability - making sure systems don't just run, but run well
Work directly with the people who'll use what we build, and translate their needs into systems.
Requirements:
Substantial software engineering experience, with a track record of building and shipping complex systems
Hands-on experience building agentic or LLM-based systems - this is a requirement, not a nice-to-have. Were looking for someone who has designed agent workflows, wrestled with prompts and context, handled the failure modes, and shipped something real
Strong product instincts: comfortable with ambiguity, able to define a problem before solving it, and opinionated about what's worth building
Comfort working in a small, flat, fast-moving team where you set much of your own direction
The ability to communicate clearly with non-technical partners across marketing
Nice to have:
Experience with orchestration frameworks for agentic systems (e.g. LangGraph or similar)
Experience with evaluation frameworks, RAG, or working with knowledge bases at scale
Familiarity with the marketing domain, or a genuine interest in it
Experience taking a system from early prototype to broad organizational adoption.
This position is open to all candidates.
 
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4 ימים
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
Were looking for an AI Builder to serve as the technical backbone of Nomas internal AI function. Youll build the LLM-powered agents, automation pipelines, integrations, and infrastructure that teams across the company rely on every day.

This is a rare opportunity to build a new function from the ground up within a company where the work can have an immediate and meaningful impact. Youll create systems such as tools that help Sales track competitive deals in real time, pipelines that automatically turn customer calls into Salesforce updates, and agents that identify competitor activity and deliver actionable insights directly to Slack.

This is a highly hands-on role with true end-to-end ownership-from translating business needs into focused technical solutions to deploying, monitoring, and continuously improving production systems.

What Youll Do:

Build AI-Powered Agents and Automations
Design and build LLM-powered agents, automation pipelines, and backend services used across the organization.
Develop complex integrations that bring together data from multiple internal and external systems.
Build custom MCP servers and other infrastructure required to support scalable internal AI workflows.
Turn fuzzy business needs into practical, focused, and maintainable technical solutions.

Own the Internal AI Infrastructure
Harden and maintain Nomas existing MCP Gateway ecosystem.
Improve reliability, error handling, authentication, secrets management, and versioning.
Implement secure, vault-based credential management and strong security practices across production automations.
Build infrastructure that enables agents and workflows to operate reliably at scale.

Drive Production Readiness and Reliability
Own the deployment, monitoring, maintenance, and reliability of agents and automations in production.
Build evaluation frameworks, test sets, and monitoring processes to measure accuracy, precision, recall, hallucination rates, and overall agent performance.
Identify regressions and continuously improve the quality and stability of production workflows.
Troubleshoot failures across integrations, mod
דרישות:
What You Bring:
3-5 years of software engineering or hands-on development experience.
Strong Python skills and experience writing clean, maintainable, production-grade code.
Hands-on experience working with LLM APIs such as Anthropic Claude, OpenAI, or similar.
Experience building integrations using REST APIs, webhooks, and asynchronous pipelines.
Experience with automation platforms such as n8n, Make, Zapier, or similar.
Hands-on experience with MCP and building or integrating MCP servers.
Experience evaluating LLM or agent performance in production, including building evaluation harnesses or test sets to identify regressions.
Understanding of secrets management, credential handling, and security best practices for production automations.
Ability to work independently and own projects end-to-end.
Strong problem-solving skills and the ability to turn ambiguous requirements into practical technical solutions.

Who You Are:
Genuinely excited about AI and actively following developments in the space.
Adaptable by default-you learn quickly, pivot when needed, and dont become overly attached to a specific tool or approach.
You ship quickly, gather feedback, and iterate.
You care about the end user and business impact, not only the technology.
Comfortable working in a fast-moving startup environment without an established playbook.
Highly accountable, hands-on, and motivated by building something from the ground up.

Nice to Haves:
Background in cybersecurity or enterprise B2B SaaS.
Experience with agent frameworks such as LangChain, LangGraph, CrewAI, or equivalent.
Experience building internal developer platforms or company-wide automation infrastructure.
Familiarity with Salesforce, Slack, and other common enterprise systems.
Experience driving internal adoption of AI tools and המשרה מיועדת לנשים ולגברים כאחד.
 
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27/08/2026
Location: Tel Aviv-Yafo
Job Type: Full Time and Hybrid work
We're looking for an AI Tech Lead to own that standard across three surfaces:
The platform - Today each agent flow is close to a bespoke implementation. You'll turn our hard-won patterns into shared components, conventions, and infrastructure so the next agent is a week of work rather than a quarter - with evaluation, observability, and cost control built in rather than bolted on.
Enablement - Miggo's advantage compounds only if the whole company is AI-fluent, not just R&D. You'll raise that fluency everywhere - engineering, research, product, GTM - through tooling, patterns, and teaching.
The voice - You'll publish the methodology: how we benchmark agentic security output, how we model residual risk, what we learned failing. This is a category-defining position and we want it argued in public.
This is a hands-on lead role with no direct reports. Your authority comes from the quality of what you build and how clearly you explain i
Requirements:
You've shipped agentic systems to production - real orchestration, tool use, structured outputs, and the failure modes that only appear at scale. Not "I've called an LLM API."
You've built the evaluation discipline, not just consumed it: trajectory tests, golden datasets, regression gates, offline replay. "It seems better" is not a metric, and you have opinions about what is.
Deep backend and distributed-systems engineering. Strong Python, and comfort with workflow orchestration (Temporal or equivalent), streaming, and cloud-native infrastructure. Agent platforms are systems problems wearing an AI hat.
Fluency across the modern agent stack - LangChain/LangGraph-style frameworks, multi-provider routing, structured output contracts, prompt and context engineering - with the judgment to know which parts are load-bearing and which are fashion.
Security literacy. Enough to reason about whether an agent's security output can be trusted, and to argue with researchers on the merits. You don't need to be a vulnerability researcher.
Influence without authority. You'll change how three teams work with no one reporting to you. Show us where you've done that.
Advantage: experience with AI/LLM security - red-teaming agents, prompt injection, or agentic attack patterns.
Advantage: background in cybersecurity, detection engineering, or WAF/mitigation systems.
Advantage: you've driven AI adoption across a whole company, not only an engineering org.
This position is open to all candidates.
 
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תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
24/08/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
we are looking for a AI Engineer - Algorithm Team.
As an AI Engineer, you will join a fast-moving, highly technical team that works at the intersection of computer vision, deep learning, and modern AI. You will be the driving force behind our LLM and agentic AI efforts - exploring, evaluating, and deploying the latest research and tooling in this rapidly evolving space, and shaping how we apply it across the organization to turn cutting-edge ideas into production-ready tools and agents.
You will design and build LLM-powered applications, agentic workflows, and internal tools that empower our algorithms, mapping, and engineering teams to move faster and operate at greater scale. Collaboration is central to the role, you will work closely with researchers, engineers, and domain experts to identify high-impact opportunities, prototype quickly, and integrate reliable AI systems into real-world products.
Key Responsibilities:
Design, build, and iterate on LLM-powered applications, including retrieval-augmented generation (RAG) systems, agents, and fine-tuned models tailored to unique data and workflows.
Develop agentic workflows that automate complex, multi-step tasks across research, data analysis, and engineering pipelines.
Build internal tools and assistants that empower algorithm researchers, mapping experts, and engineers to work faster and more effectively.
Evaluate and integrate the latest foundation models, frameworks, and techniques (e.g., prompt engineering, fine-tuning, tool use, multi-agent orchestration), keeping pace with rapid advances in the field.
Design robust evaluation methodologies to measure quality, reliability, and safety of LLM-based systems.
Collaborate closely with the Algorithms, Mapping, and Software teams to identify high-impact opportunities and transition prototypes into reliable, production-grade systems.
Requirements:
Experience in building and shipping meaningful, production-grade agentic systems - not just demos or prototypes. Were looking for people who can walk us through what they built, the real problem it solved, and the value it created.
Deep, in-depth understanding of LLMs - including how they work under the hood (transformer architecture, tokenization, attention, sampling), their failure modes, and the practical tradeoffs between models, prompting strategies, fine-tuning, and retrieval.
Strong hands-on experience with modern agentic frameworks (e.g., LangGraph, LangChain, or equivalent) and with designing multi-step, tool-using workflows.
Strong command of RAG, prompt engineering, evaluation methodologies, and techniques for improving reliability and reducing hallucinations in LLM-based systems.
Strong proficiency in Python and experience with common AI/ML libraries and APIs (e.g., OpenAI, Anthropic, Hugging Face, PyTorch).
solid software engineering practices, including writing clean, maintainable code and building robust, scalable systems.
5+ years of experience developing machine learning, AI, or software systems.
B.Sc. in Computer Science, Computer Engineering, Electrical Engineering, or similar field.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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מודים לך שלקחת חלק בשיפור התוכן שלנו :)
4 ימים
Location: Tel Aviv-Yafo and Yokne`am
Job Type: Full Time
We are at the forefront of the AI revolution, delivering brand new accelerated compute platforms for global impact. Our Network Architecture group is seeking a talented and motivated Sr. Software Engineer to build the agentic workflows that our architects use in their daily work. The software at the center of this role is our hardware network simulation environment - you will design multi-step agent workflows over it, engineer the context that grounds them in our own specifications and source code, and optimize their runtime performance. If you are passionate about building the practical infrastructure that brings intelligent agents to life, we want to hear from you.


What you'll be doing:
Build agentic workflows - loops, graphs, and multi-step pipelines - that carry real hardware network simulation and analysis work end to end.
Engineer the context these workflows run on, turning our simulation models, specifications, design documents, and source code into context that makes agents accurate in our domain.
Work closely with network architects to understand their workflows and translate them into agent workflows they use daily.
Optimize the runtime performance of our simulation tooling on these platforms, including execution time, compute cost, and end-to-end latency.
Define evaluation and regression testing for agent workflows, so that changes to a prompt, a graph, or a context source are measurable.
Build observability across agent runs: what the agent did, where it failed, and why.
Champion guidelines for secure and reliable agent workflows, including data handling, access control, and interaction boundaries.
Serve as a key technical resource for solving sophisticated integration issues between agents and internal tooling.
Requirements:
What we need to see:
B.Sc. or above in Computer Science, Computer Engineering, or a related field, or equivalent experience.
5+ years of hands-on experience in software engineering, with demonstrated ownership of production systems from design through deployment.
Expert-level programming skills in C++, with strong Python skills alongside it.
Strong understanding of the full stack, including hardware: memory, I/O, networking, accelerators, and where real performance bottlenecks occur.
Current, practical knowledge of how to build systems around AI models: agent loops, tool interfaces, context retrieval and management, and common failure modes.
Understanding of inference serving, including request lifecycle, batching, caching, and the tradeoffs between throughput, latency, and cost.


Ways to stand out from the crowd:
Experience writing hardware simulation software - network, system, or architectural simulators, models, or testbenches.
Networking experience - protocols, fabrics, switching, or RDMA - and experience working alongside silicon, systems, or architecture teams.
Hands-on experience with inference serving engines such as vLLM, TensorRT-LLM, or Triton Inference Server, including low-level internals such as KV cache, batching and scheduling, and quantization, and related performance work such as profiling and GPU programming.
Hands-on experience building or fine-tuning LLMs or other generative models.
Agent workflows, tooling, or context pipelines adopted by other engineering teams.
This position is open to all candidates.
 
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