דרושים » AI » Senior AI Builder

משרות על המפה
 
בדיקת קורות חיים
VIP
הפוך ללקוח VIP
רגע, משהו חסר!
נשאר לך להשלים רק עוד פרט אחד:
 
שירות זה פתוח ללקוחות VIP בלבד
AllJObs VIP
כל החברות >
סגור
דיווח על תוכן לא הולם או מפלה
מה השם שלך?
תיאור
שליחה
סגור
v נשלח
תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
לפני 4 שעות
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.
 
Hide
הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8829780
סגור
שירות זה פתוח ללקוחות VIP בלבד
משרות דומות שיכולות לעניין אותך
סגור
דיווח על תוכן לא הולם או מפלה
מה השם שלך?
תיאור
שליחה
סגור
v נשלח
תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
23/08/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We're forming a new AI Group and looking for a Senior AI Engineer to help shape it from an early stage - a greenfield, long-term effort to evolve how decisions are made across the platform using AI-driven systems. You won't just integrate APIs or build demos; you'll build the AI brain that works alongside (and increasingly drives) our core automation engine, with real production impact from day one and room to grow into technical leadership as the group scales.

Agentic AI Architecture: Design and build autonomous AI agents that analyze infrastructure in real time and make intelligent decisions. Work with modern agentic frameworks (LangGraph, PydanticAI) and conversational AI to create multi-agent systems - including troubleshooting, optimization, FinOps, and how-to agents. Leverage core LLM capabilities (tool-use, memory, retrieval) to operate safely in production.
Platform Integration & Intelligent Decision Systems: Develop MCPs to expose capabilities to AI agents that reason over infrastructure environments, metrics, configurations, and cost signals. Build integrations with tools like Slack, Jira, and AI-powered IDEs (Cursor, Windsurf) to deliver context-aware insights, from "why is this pod not scheduling?" to "how can we reduce costs by 30% safely?"
AI Model Development & MLOps: Build and deploy machine learning models that learn from infrastructure patterns - detecting the right resource policies for workloads, predicting optimal scaling triggers, and recommending GPU configurations. Own the complete ML pipeline from training to production, ensuring models are reliable, monitored, and continuously improving.
R&D AI Tools Development & Adoption: Build and embed internal AI tools to accelerate engineering, development, research, and support.
AI Tools for Business Impact: Develop AI-powered tools that help Sales and Support teams demonstrate value instantly - agents that analyze customer infrastructure, generate cost optimization reports automatically, and turn technical data into clear business recommendations.
End-to-End Ownership: Own AI systems from concept to production, ensuring they're fast (sub-2-second responses), reliable, safe, and cost-effective. Build evaluation frameworks to measure quality, implement security controls, and balance performance tradeoffs in production.
Technical Leadership: Define AI architecture and best practices as a founding member of the AI team. Make key technical decisions - choosing frameworks, designing multi-agent systems, establishing data governance - and shape how evolves from AI-enhanced internal tools to customer-facing AI products.
Requirements:
Core Engineering: Significant software engineering experience (typically 4+ years) with strong Python skills and solid backend engineering fundamentals.
Production Experience: Experience building and operating production systems in cloud environments.
Real-World GenAI Experience: Practical experience bringing LLM-based systems into production, including handling latency, cost control, and failure modes. Familiarity with additional agentic frameworks (e.g., LangChain, MetaGPT) and evaluation frameworks.
Builder Mentality: Strong ownership and the ability to operate independently while collaborating closely across teams, with the motivation to grow into technical leadership as the group expands.
(Advantage) Data & RAG: Experience enabling LLMs to consume structured or operational data (configurations, logs, metrics) and experience with retrieval systems (RAG) or vector databases.
This position is open to all candidates.
 
Show more...
הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8792284
סגור
שירות זה פתוח ללקוחות VIP בלבד
סגור
דיווח על תוכן לא הולם או מפלה
מה השם שלך?
תיאור
שליחה
סגור
v נשלח
תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
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.
 
Show more...
הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8805503
סגור
שירות זה פתוח ללקוחות VIP בלבד
סגור
דיווח על תוכן לא הולם או מפלה
מה השם שלך?
תיאור
שליחה
סגור
v נשלח
תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
19/08/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are a fast-paced, technology-driven team where everyone's contribution impacts product success.

We are looking for a hands-on, business-minded AI Engineer to join our Data & AI Team.

This role is for someone who has already built and shipped real AI products in a company environment. You will work as an integral part of the Data & AI Team, partnering directly with business stakeholders to identify high-impact opportunities, translate business needs into technical solutions, and build AI products that automate internal processes and create immediate value.

The ideal candidate is a builder. You should be comfortable working with LLMs, AI agents, automation workflows, APIs, data pipelines, data warehouses, and internal company systems. You should also be comfortable taking ownership, asking sharp business questions, and moving ideas from concept to production.

Our Data Team has already built internal AI products at our company. Now we are looking for someone who can help take us to the next level.

What Were Looking For
The right person has built with AI in a real company environment and knows how to turn business needs into practical internal products. They should be comfortable working with stakeholders, understanding how teams operate, and identifying where AI can create meaningful value.

Because this role sits inside the Data & AI Team, they also need to be strong with data. That means working confidently with company data, data warehouses, pipelines, APIs, and the technical building blocks that make AI products reliable and useful.

This role is for someone hands-on, curious, and hungry to build. Someone who can combine AI, data, and business context to help our company move faster, automate smarter, and turn ideas into measurable business wins.

What Youll Do
Build end-to-end internal AI products, automations, agents, and workflows that solve real business problems across our company.
Work directly with business stakeholders to understand pain points, define requirements, and turn ideas into scalable AI-driven solutions.
Design, prototype, test, deploy, and maintain production AI products using LLMs, AI agents, APIs, automation frameworks, and internal company data.
Work hands-on with data tools and infrastructure, including Snowflake, ETLs, data pipelines, APIs, AI tools, and internal servers.
Identify high-impact manual processes and turn them into automated AI-driven business wins.
Evaluate new AI tools, frameworks, and agentic workflows, and apply them where they can improve productivity, decision-making, or business operations.
Help shape internal AI development best practices around reliability, usability, security, documentation, maintainability, and production readiness.
דרישות:
2-5 years of hands-on experience in AI Engineering, Data Engineering, Software Engineering, Data Science, Analytics Engineering, or a similar technical role.
Proven experience building and deploying AI-powered products, workflows, agents, automations, or business solutions in a real company environment.
Strong hands-on experience with LLMs, AI agents, prompt engineering, RAG, workflow automation, APIs, or AI development frameworks.
Ability to code and build practical solutions using Python, SQL, JavaScript/TypeScript, or similar languages.
Strong data experience, including ETLs, data pipelines, APIs, databases, data warehouses, and Snowflake.
Experience working in a SaaS or B2B technology company.
Strong business acumen, ownership, and communication skills, with the ability to work independently with stakeholders and drive projects from idea to production.
Degree in Engineering, Computer Science, Mathematics, Statistics, Physics, or a related quantitative field - advantage
Advantages
Experience with agent frameworks, RAG systems, vector databases, orchestration tools, Snowflake, Airflow, Rivery, Gitlab, Claude, OpenAI, or similar tools.
Experience working in a cybersecurity or data company.#ENGLISH המשרה מיועדת לנשים ולגברים כאחד.
 
Show more...
הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8789170
סגור
שירות זה פתוח ללקוחות VIP בלבד
סגור
דיווח על תוכן לא הולם או מפלה
מה השם שלך?
תיאור
שליחה
סגור
v נשלח
תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
08/09/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for a Senior Data Engineer to build and scale the data foundation behind platform and products. You will own complex data end-to-end - from ingestion and transformation through modeling, quality, observability, and production delivery.
This is a hands-on senior IC role for a strong builder who can solve difficult data problems independently, set a high technical bar, and collaborate closely with engineering, DS, and product. You will turn large, fragmented datasets into reliable, reusable capabilities that power every product.
Responsibilities
Build and own scalable data pipelines- Design, implement, and operate robust pipelines for high-volume structured and unstructured data, with validation, monitoring, lineage, and recovery built in.
Scale the platform for growth- A key near-term initiative is re-architecting the system to support a significantly larger customer base. You will own performance and cost-efficiency across pipelines and services, keeping reliability and operating costs under control as the platform scales.
Build across the stack- This is not a pipelines-only role. You will also write backend services and some frontend, including the internal backoffice the team runs on. We hire builders, not narrow specialists.
Own the core data tables- Own schema design and evolution, data contracts, and the modeling standards the team follows - naming, shared dimensions, normalization, documentation. Be accountable when a table is wrong, late, or drifting.
Level up the teams data work- Pair with and advise software engineers and data scientists on Spark, SQL, and modeling, and help turn notebook-grade code into production-grade pipelines.
Partner cross-functionally- Translate product, client, compliance, and business requirements into clear technical designs and dependable production systems.
Requirements:
Spark at scale- You have tuned real Spark jobs for performance and cost - skew, shuffle, partitioning, memory, spill - run pipelines over TB-scale or billions of rows in production, and can reason about the physical execution plan, not just write DataFrame code.
5+ years of professional experience building and owning production systems.
Strong Python and SQL, with maintainable, tested production code.
Strong software engineering fundamentals across the stack. You can own backend services and pick up frontend when the work needs it - not a pipelines-only specialist.
AI-first way of working- You build with AI in your day-to-day development, using it to move faster and raise the quality of what you ship.
Deep experience designing and operating ETL/ELT pipelines, data models, and distributed data-processing systems.
Comfortable advising and pairing with other engineers and data scientists on data work.
Strong AWS experience: S3, Glue, EMR, Athena, and related compute and orchestration services.
Experience with modern data lakehouse or warehouse architectures. Apache Iceberg is a strong advantage.
Experience with workflow orchestration (Airflow or similar), CI/CD, Docker, Git, and infrastructure as code such as AWS CDK and CloudFormation.
Strong understanding of data quality, schema evolution, lineage, observability, privacy, security, and access controls. Experience with regulated or sensitive data, such as healthcare / PHI, is an advantage.
High comfort in a fast-moving environment with incomplete requirements, high ownership, and a strong sense of urgency.
This position is open to all candidates.
 
Show more...
הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8814966
סגור
שירות זה פתוח ללקוחות VIP בלבד
סגור
דיווח על תוכן לא הולם או מפלה
מה השם שלך?
תיאור
שליחה
סגור
v נשלח
תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
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.
 
Show more...
הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8804088
סגור
שירות זה פתוח ללקוחות VIP בלבד
סגור
דיווח על תוכן לא הולם או מפלה
מה השם שלך?
תיאור
שליחה
סגור
v נשלח
תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
6 ימים
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
This role owns the AI-native GTM engine: the systems that find, enrich, reach, and route prospects and customers, and the workflows that create new opportunities for the company. You build revenue systems with AI tooling, then run them against pipeline targets. The scope is wide on purpose. You own the motion and the measurement, so theres no gap between what you build and what you can prove.

What youll own
Outbound engine. Multi-channel outbound end-to-end: list building, segmentation, messaging, sequencing, launch, and A/B iteration across email and LinkedIn. AI-driven personalization at scale, moving prospects from first touch to booked meeting with minimal manual input from sales.
Inbound conversion. Everything between the first visit and the booked meeting: on-site conversion paths, forms, chat, scoring, routing, and speed-to-lead. Instrument every step, find where intent leaks, and close the gap with automation instead of headcount. No inbound lead should sit waiting for a human to qualify it.
CRM truth and attribution. The measurement layer under everything else. If outbound, inbound, AEO, and content cant be attributed, none of it can be optimized or defended. Own data quality across HubSpot and Salesforce.
Data and enrichment. Prospect identification and signal tracking: enrichment waterfalls, buying signals, social listening, and clean push architecture into the CRM.
AI agents and automation. Claude is a teammate here, not a chatbot. Build the agents, skills, and workflows that encode our GTM playbooks and kill anything manual.
AI content and discovery. Build the writing agents that produce inbound at volume: programmatic pages, competitor comparisons, persona and vertical landing pages, localized variants, and one asset turned into fifteen across channels. AEO is the other half of this. Buyers now start in ChatGPT, Claude, Perplexity, and AI Overviews, not on a results page, so the content has to be built to be retrieved and cited: structured content and schema, presence on the review sites and communities models pull from, and a technical layer that makes our legible to crawlers.
Customer expansion. The signal engine that finds revenue inside the base: segmentation, expansion triggers, and routing each account to the right owner or the right sequence at the right time.
The stack itself. The GTM tech stack end-to-end: evaluate, buy, integrate, and kill tools as the motion evolves, and build tools with direct impact on revenue when nothing off the shelf does the job.
Requirements:
Who you are
A builder. Youd rather ship the system than write the spec.
AI-native. You build with LLMs, agents, and skills as core infrastructure. ChatGPT usage alone doesnt count.
Automation-first. You see a manual handoff and immediately think about how to remove it, including by putting an AI agent on it.
Product-oriented. You understand the value proposition from the personas point of view and can make it land.
Analytical. You can model the full funnel, build attribution, run conversion analysis, and turn it into decisions.
Founder-like mindset. You act like the outcome is yours: carry pipeline numbers, not activity metrics, spot leaks before anyone asks, and move without waiting for permission.
Preferred experience
3+ years in growth, GTM engineering, RevOps, or a builder-heavy commercial role in high-growth B2B SaaS
Hands-on building with Clay, a sequencer (Alta, Outreach, Apollo, Lemlist), and an automation platform (n8n, Make, Zapier), plus comfort with APIs, webhooks, and JSON
Deep HubSpot or Salesforce fluency: objects, workflows, reporting
Experience building LLM and agent workflows in production
This position is open to all candidates.
 
Show more...
הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8825456
סגור
שירות זה פתוח ללקוחות VIP בלבד
סגור
דיווח על תוכן לא הולם או מפלה
מה השם שלך?
תיאור
שליחה
סגור
v נשלח
תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
26/08/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for an AI Research Engineer to build the backbone of our autonomous security platform.
our company builds AI Digital Employees who help cyber teams close the execution gap. Our first AI Digital Employee, Alex, learns, understands and takes away the burden of Identity and Access Management (IAM) tasks - proactively completing the organization's cyber objectives.
About the Role:
You'll own technically difficult problems before the solution is known. Starting with a cybersecurity need, you'll study the domain, frame the technical challenge, investigate possible approaches, and build the solution through production. You'll have access to our company's shared agent infrastructure, but the role goes far beyond configuring existing components. Many use cases will require new reasoning methods, agent architectures, evaluation techniques, data strategies, or model behavior. This is a role for someone who enjoys applied research but is motivated by outcomes. The goal is not simply to prove that an idea can work, it is to make it useful and reliable for customers.
What You'll Do:
Design and implement AI solutions for complex cybersecurity workflows.
Develop new approaches for agent reasoning, planning, tool use, context management, decision-making, and recovery from failures.
Determine the right technical approach for each problem, combining models, algorithms, data, and conventional software where appropriate.
Define quality for each use case and create evaluations that measure correctness, task completion, consistency, safety, latency, and cost.
Analyze agent behavior deeply, identify the underlying causes of failures, and improve the relevant model, data, tool, or architecture.
Collaborate with cybersecurity experts, product teams, software engineers, and AI infrastructure engineers throughout development.
Requirements:
Excellent software engineering skills and substantial experience with Python.
Hands-on experience building advanced systems with modern language models.
Deep familiarity with several areas relevant to AI agents, such as planning, tool use, retrieval, memory, structured generation, model adaptation, or evaluation.
The ability to turn an ambiguous problem into a technical research plan and then into working software.
Strong experimental instincts: you form clear hypotheses, design meaningful tests, and make decisions based on evidence.
Sound judgment about when to use an AI technique and when a deterministic approach is more effective.
Ownership of the complete result, including its behavior after reaching production.
Nice to Have:
Developing autonomous or long-running agents that interact with real systems.
Building evaluation environments, simulations, or benchmarks for complex model behavior.
Experience in cybersecurity, identity, security operations, or enterprise automation.
Applying published research or your own research to production problems.
This position is open to all candidates.
 
Show more...
הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8797759
סגור
שירות זה פתוח ללקוחות VIP בלבד
סגור
דיווח על תוכן לא הולם או מפלה
מה השם שלך?
תיאור
שליחה
סגור
v נשלח
תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
30/08/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
As an AI Expert at our company, youll take full ownership of AI-powered product capabilities - from concept to production. Youll work closely with Product, Engineering, and Security domain experts to build practical, reliable AI systems that improve how teams operate and secure cloud environments. This is an applied role: we care about shipping, adoption, and measurable outcomes. Youll engage with users, test MVPs in production, iterate quickly based on feedback, and make sure what you build holds up in the real world. And yes youll also jump in as a Support Hero when needed, helping customers succeed and learning directly from how they work.
Key Responsibilities
Build and ship AI features that improve cloud security operations (e.g., control recommendations, drift detection explanations, guided remediation, policy generation, investigations, workflow automation).
Design and implement AI agents tuned for cloud-security tasks, including the surrounding framework (tools, permissions, orchestration, guardrails, and automation).
Apply deep understanding of cloud security domains (IAM, network controls, logging/telemetry, posture management, governance, misconfiguration, threat scenarios) to guide product decisions and ensure the AI behaves safely and correctly.
Integrate with multi-cloud APIs and security controls (AWS/Azure/GCP/OCI), building end-to-end flows from user intent → actionable outcome. Create and maintain evaluation methods for model quality (accuracy, coverage, hallucination rates, latency, cost, and user satisfaction) and build tooling to continuously measure performance in production.
Build data and feedback loops to keep systems relevant over time (user corrections, outcome tracking, regression testing, prompt/model iteration).
Stay current with practical advancements in LLMs/agents and engineering patterns, and adopt whats useful (not hype) into production.
Requirements:
What Were Looking For
5 years of experience in cloud security, cloud engineering, or building security products for cloud environments.
Deep knowledge of public cloud security fundamentals, such as:
IAM (roles, policies, permissions boundaries, identity federation)
Network security (security groups, NACLs, firewall constructs, private connectivity)
Logging and monitoring (cloud audit logs, flows, detections, telemetry pipelines)
Governance and posture (misconfigurations, guardrails, policy-as-code concepts)
Strong coding skills with the ability to develop end-to-end production features (not just notebooks/POCs).
Hands-on experience building with modern AI systems (LLMs, retrieval, structured outputs, agents/tool use, evals) and a mindset for reliability, security, and guardrails.
Practical engineering instincts: you know how to trade off quality/speed/cost and ship incrementally without breaking trust.
Excellent communication and team collaboration skills; comfortable working cross-functionally.
Fluency in English.
Youll be a great fit if
You think like a product engineer: focused on impact, users, and shipping.
You love getting things done and taking ownership end-to-end.
Youre excited about building AI systems that operate safely inside real cloud environments - with real consequences and real customers.
This position is open to all candidates.
 
Show more...
הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8801666
סגור
שירות זה פתוח ללקוחות VIP בלבד
סגור
דיווח על תוכן לא הולם או מפלה
מה השם שלך?
תיאור
שליחה
סגור
v נשלח
תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
26/08/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are constantly striving to make our systems reliable, scalable, and simple to operate so our services are available to travelers when they need them most. With our continued growth, we have exciting challenges ahead and we're looking for a Senior Site Reliability Engineer to join our team in Tel Aviv. This role blends classic SRE ownership with pragmatic AI SRE work: you will build and operate the platforms, automation, observability, and incident response practices that keep Navan reliable, while helping teams use AI solutions, AI providers, and their APIs safely and dependably.



This is a hands-on engineering role, not a research role. You will partner with product, platform, data, security, support, and incident response teams to make production systems and AI-powered experiences more resilient. You will use software engineering, infrastructure as code, SLOs, telemetry, provider observability, and automation as your main tools, and you will apply AI where it creates measurable reliability value rather than novelty.



This position is based out of our new Tel Aviv office.



What You'll Do:

Support AI-based application solutions where reliability matters. Partner with the development teams building AI-powered travel experiences to support the development and production operation of their solution.
Work with AI solutions, providers, and APIs. Partner with teams integrating AI capabilities and providers, with attention to API reliability, authentication, quotas, rate limits, latency and provider-specific operational constraints.
Troubleshoot AI tools and provider issues. Diagnose failures across AI-powered workflows, provider APIs, configuration, permission errors, degraded responses and related areas.
Operate reliable production platforms. implement and run cloud infrastructure,and help product teams move quickly without compromising reliability.
Improve observability. Build dashboards, alerts, traces, logs, and runbooks that make service health clear, actionable, and tied to SLOs and customer impact.
Apply AI to SRE workflows. Prototype and productionize AI-assisted systems that create effective and efficient operations
Automate operational toil. Create tools, workflows, and automation that remove repetitive manual work and make operational knowledge easier to use.
Requirements:
5+ years of experience as a Senior SRE, Infrastructure Software Engineer, Production Engineer, or DevOps Engineer.
3+ years of experience operating production, 24x7 customer-facing systems.
Hands-on experience delivering production infrastructure, platform tooling, and automation used by engineering teams.
Strong software engineering skills in Python, Go, Java, or a similar language, with a bias toward production-quality code, tests, monitoring, and documentation.
Experience with cloud infrastructure, container orchestration, Linux systems, networking, CI/CD, and infrastructure as code such as Terraform or CloudFormation.
Experience building, tuning, and automating observability systems such as Grafana, Prometheus, New Relic, Datadog, Splunk, or similar tools.
Familiarity with SLOs, incident response, on-call practices, root cause analysis, and blameless postmortems.
Practical experience or strong interest in AI solutions, AI providers, agents, AI APIs, provider integrations, or AI-assisted internal tools.
Ability to troubleshoot AI tools and provider/API issues, including rate limits, quota, auth, permission errors, latency, SDK or API contract changes, content quality issues, and service degradations.
Excellent communication skills and the ability to work with stakeholders and domain experts across the company.
This position is open to all candidates.
 
Show more...
הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8797911
סגור
שירות זה פתוח ללקוחות VIP בלבד
סגור
דיווח על תוכן לא הולם או מפלה
מה השם שלך?
תיאור
שליחה
סגור
v נשלח
תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
1 ימים
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.
 
Show more...
הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8828333
סגור
שירות זה פתוח ללקוחות VIP בלבד