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לפני 1 שעות
Location: Merkaz
Job Type: Full Time
we are looking for a Senior Software Engineer - Integrations - AI/ML.
As a Senior Software Engineer specializing in the AI & ML ecosystem, you'll be a core contributor owning and evolving critical parts of AI ecosystem. This role sits at the intersection of high-performance database engineering and developer experience. You'll craft tools that enable Engineers and Data Scientists to harness speed and scale in the frameworks they already use.
We're looking for someone who has firsthand experience as an AI & MLEngineer or Data Scientist. The data practitioner's world is shifting rapidly: databases are no longer just query targets, but they're becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should build and why.
You'll own the full lifecycle of key AI/ML integrations, driving architecture, performance, and feature direction across AI & LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation as a vector store, ML feature stores, and LLM-powered data applications.
Requirements:
7+ years of software development experience, including hands-on time as a Data Scientist or ML Engineer
Deep, proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform (orchestration, BI, MLOps, or data transformation)
Hands-on experience applying AI/ML in production data-engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling that shipped and ran in production
Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries
Strong database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases
Solid experience with concurrent Python: threading, multiprocessing, and async patterns
Outstanding written and verbal communication; comfortable collaborating across engineering functions and with open-source communities
Bonus points for:
Prior experience as a Data Engineer or Data Scientist in a product-facing or platform role
Familiarity with ClickHouse or similar high-performance OLAP platforms
Familiarity with the JVM ecosystem
Experience deploying AI/ML models in production, including inference APIs and vector databases
Familiarity with tools like dbt, Airflow, Dagster, Prefect is a plus
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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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.
 
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לפני 4 שעות
Location: Tel Aviv-Yafo
Job Type: Full Time
Your Career:
The Cortex Content team powers Palo Alto Networks security operations platforms (XSIAM/XSOAR) by building the essential integrations, data connectors, and intelligence layers that protect our customers.
We are looking for a Senior Software Engineer who is passionate about AI and automation to help scale our content ecosystem. In this role, your focus will be leveraging AI to accelerate the delivery, quality, and quantity of our security integrations and content infrastructure. You will design and develop intelligent tools and workflows that enable engineering peers and Technical Program Managers (TPMs) to scale their output, collaborating with them as they test, adopt, and integrate these solutions into our development lifecycle.
Your Impact:
Scale Content Delivery: Design and implement AI-driven systems that empower the team to significantly increase both the quantity and the rigorous quality of our security integrations.
Develop Cross-Functional Tooling: Build internal developer tools and agentic workflows that enable other engineers and TPMs to streamline content creation, validation, and management.
Optimize Workflows: Create reliable CI/CD pipelines incorporating AI agents to automate code generation and testing processes.
Support Team Adoption: Collaborate with engineering peers and cross-functional partners as they test and integrate your tools into their daily workflows, using their feedback to drive continuous improvements.
Contribute to AI Integration: Help lead the practical integration of LLMs and automation frameworks into our day-to-day engineering processes.
Requirements:
Your Experience:
Experience: 3+ years of professional software engineering experience delivering clean, maintainable code in a production environment.
Proven AI/Automation Impact: Demonstrated experience in at least one of the following areas:
Supported or led an AI transformation/adoption effort within an engineering team.
Developed and deployed a major AI-powered feature or internal productivity tool.
Built CI/CD workflows or developer tooling that utilizes autonomous AI agents.
Collaborative Mindset: Experience building tooling meant for other technical stakeholders (engineers/TPMs) and incorporating user feedback into future iterations.
Core Engineering Skills: Solid understanding of software design, API development, and data workflows.
Nice to Have:
Python Proficiency: Strong experience with Python and its associated libraries or AI frameworks (e.g., FastAPI, LangChain, or similar orchestration tools).
Security Knowledge: Familiarity with SIEM, API integrations, or general cybersecurity operations.
This position is open to all candidates.
 
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Location: Kefar Sava
Job Type: Full Time and Hybrid work
we are looking for a hands-on technical leader to build and operate a secure local large-language-model platform for the company. The platform will allow engineering and business teams to use generative AI with proprietary source code, product documentation, technical standards, test artifacts, support knowledge, and other approved internal data while keeping sensitive information within company-controlled environments.
This is a senior individual-contributor role spanning applied LLM engineering, platform architecture, search and data pipelines, security, and production operations. You will turn promising prototypes into a dependable internal capability: selecting and optimizing open-weight models, building permission-aware retrieval, creating reusable APIs and tools, integrating with existing engineering workflows, and establishing objective ways to measure quality, safety, latency, capacity, and business value.
The successful candidate will understand that a useful enterprise LLM is more than a model and a chat interface. It requires trustworthy source grounding, strong access controls, repeatable evaluation, careful tool permissions, observable production services, and an operating model that keeps data, indexes, prompts, models, and dependencies current. You will make pragmatic build-versus-buy decisions and choose the simplest approach-search, retrieval-augmented generation (RAG), prompting, workflow automation, or model adaptation-that meets each use case.
Initial use cases may include engineering knowledge discovery, source-code understanding, troubleshooting assistance, technical-document Q&A and summarization, test and log analysis, and drafting structured engineering artifacts. The platform should be extensible to additional approved use cases as needs and model capabilities evolve.
Requirements:
BSc or MSc in Computer Science, Computer Engineering, Electrical Engineering, Data Science, or a related field, or equivalent practical experience.
Typically 7+ years of hands-on experience in production software, ML platform, search, data, or infrastructure engineering, including meaningful recent experience shipping LLM-powered systems; exceptional candidates with equivalent depth are welcome.
Strong Python engineering skills and experience designing maintainable APIs, services, libraries, and data pipelines. Experience with Go, Java, or C/C++ is an advantage.
Strong understanding of transformer-based language models and production inference, including tokenization, context management, batching, KV caching, parallelism, quantization, structured output, tool calling, and common model failure modes.
Demonstrated experience building production RAG or enterprise-search systems using embeddings, vector and/or lexical search, metadata filtering, reranking, source attribution, and systematic retrieval evaluation.
Experience defining task-specific LLM evaluations using representtive datasets, strong baselines, domain-expert review, automated metrics, human feedback, error analysis, and regression thresholds.
Experience deploying and operating containerized services on Linux using Docker and Kubernetes or an equivalent orchestration environment.
Practical experience with GPU-backed model serving, performance profiling, capacity planning, monitoring, and reliability engineering.
Strong knowledge of distributed-system fundamentals, authentication and authorization, API security, secrets handling, encryption, auditability, and data lifecycle controls.
Experience with Git, automated testing, CI/CD, infrastructure as code, observability, and production incident response.
Sound technical judgment about quality, security, maintainability, hardware efficiency, and total cost-not just model benchmark scores.
Ability to lead an ambiguous, cross-functional initiative, explain complex AI behavior in plain language, and help other teams ship safely on a shared platform.
This position is open to all candidates.
 
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2 ימים
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
Were looking for a highly motivated AI Developer to help design, build, and deploy intelligent agentic systems across our product ecosystem. In this role, you'll work at the intersection of machine learning, backend systems, and modern frontend technologies to deliver AI-first features that feel magical to users.

This is a hands-on, cross-functional role ideal for engineers who love building full-fledged features-from data pipelines and LLM orchestration to intuitive UI experiences-with a strong product mindset.

Responsibilities:
AI Agent Design & Integration
Design and implement autonomous or semi-autonomous agents using LLMs (e.g., OpenAI, Anthropic, open-source models).
Work with prompt engineering, RAG pipelines, and tool/plugin integrations to enable agents to interact with internal and external systems.
Build scalable agent runtimes and orchestration layers (e.g., LangChain, Semantic Kernel, ReAct-based agents).
Fullstack Product Development
Own full-stack features end-to-end: from backend APIs and data models to React-based frontend interfaces.
Integrate AI/agent capabilities into customer-facing products with clean UX and measurable performance.
Collaborate closely with design, product, and data teams to bring ideas from concept to production.
Systems & Infrastructure
Build and maintain backend services and pipelines that support AI agents, including vector search, embeddings, function calling, and observability.
Optimize inference flows for performance and cost, potentially using streaming, caching, or local model inference.
Ensure systems are secure, reliable, and compliant with InfoSec standards.
Experimentation & Continuous Improvement
Rapidly prototype and iterate on new AI capabilities and user experiences.
Analyze performance and usage metrics to drive product and model improvements.
Stay up to date with the evolving AI toolchain and emerging agent architectures.
Requirements:
8+ years of fullstack development experience with strong skills in TypeScript/JavaScript, React, and Python (or Node/Go for backend).
Solid understanding of LLM APIs, agent frameworks (e.g., LangChain, AutoGPT, CrewAI), or custom AI pipelines- Advantage
Experience with modern cloud infrastructure (e.g., AWS, GCP, Docker, CI/CD).
Familiarity with vector databases (e.g., Pinecone, Weaviate, FAISS) and retrieval-augmented generation (RAG)- Advantage
Product-oriented mindset: you care deeply about building things that work well for users.
Bonus: experience with observability, feedback loops for AI agents, or embedded AI evaluation techniques.
This position is open to all candidates.
 
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07/09/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for a Senior II Software Engineer to join the CX Platform team, the foundational engineering team powering our entire Customer Experience group. This is a high-impact, hands-on role at the intersection of backend engineering, AI infrastructure, and customer-facing product.

You'll work across the full platform stack (backend services, data pipelines, security, cost, and scale) with a meaningful and growing focus on AI infrastructure. We own the agentic platform for the entire Product Offering group: from building the LLM infrastructure and agentic workflows to ensuring they're reliable, observable, and safe in production.

What you'll be doing:
Own AI infrastructure for the Product Offering group. Design, build, and evolve the shared AI platform (agentic workflows, LLM integrations, observability, and guardrails) that CX product teams build on.
Ship agentic features end to end. Lead development of AI-driven capabilities using LangChain, LangFuse, and AWS Bedrock, from architecture through production deployment and monitoring.
Drive platform architecture. Set the technical direction for the CX backend (services, data pipelines, API patterns) with an eye for scalability, reliability, and developer experience.
Own core data foundations. Design resilient data-access patterns across Snowflake, Elasticsearch, Kafka, Redis, and MySQL; keep pipelines fast, fresh, and reliable.
Mentor and elevate. Help engineers across the CX group grow in backend craft, AI engineering, and system design thinking.
Collaborate cross-functionally. Work with product, design, and customer-facing teams to turn ambiguous problems into well-scoped, high-quality solutions.
Requirements:
What you'll need:
6+ years of backend engineering experience with strong expertise in Node.js and TypeScript.
Hands-on experience building or integrating LLM-powered features or agentic workflows into a production product (not just internal tooling).
Experience with distributed systems and event-driven architectures, and comfort with stores like Kafka, Redis, Elasticsearch, MySQL, and Snowflake.
Strong familiarity with cloud-native environments. AWS experience is a significant advantage.
Deep systems thinking: you design for scale, resilience, and maintainability from the start.
Experience building customer-facing products alongside product managers and designers.
Excellent communication: you can align engineers, product, and non-technical stakeholders around a technical decision.
Proven ability to own and drive complex initiatives with minimal oversight.

Itd be really cool if you also have:
Experience with LangChain, LangGraph, LangFuse, or similar orchestration and observability tooling.
Hands-on experience with AWS Bedrock or other LLM provider APIs.
Experience designing or running AI evaluation frameworks (evals, LLM-as-judge, regression suites).
Familiarity with MCP (Model Context Protocol) or building tools for coding agents.
Experience with React, Next.js, or micro-frontend architectures.
Knowledge of Python for AI/data workflows.
This position is open to all candidates.
 
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חברה חסויה
Location: Ramat Gan
Job Type: Full Time
Required Senior ML Data Engineer
About the team:
The AI Engineering group builds modern infrastructure and solutions that improve how algorithms are developed.
We are a small, independent team of experienced engineers with a mix of skills in algorithms, software, and infrastructure. We work in a DevOps style and build cross-team solutions that support research and development of advanced perception algorithms.
Our flagship project is a unified AV dataset used to train and evaluate next-generation models. We take large volumes of multi-camera video, object labels, HD maps, and sensor data from across the organization, and turn it into a curated, high-quality training set - at scale.
We are looking for someone who brings ML and computer-vision depth to the team - someone who can help shape the intelligence layer that decides what data is worth training on.
What will your job look like:
Work collaboratively with shared ownership. Your focus area will be the curation and ML side of our data pipeline, but you will contribute across the full stack alongside the rest of the team.
Build and improve the curation pipeline - from vision-model embeddings and scene detection, through VLM-based scene analysis, to scoring, deduplication, and sampling that produces a balanced and diverse dataset.
Run and optimize GPU inference at scale (embedding extraction, VLM inference) across thousands of driving sessions using workflow orchestration.
Develop scoring and sampling strategies that ensure rare but important scenarios (night driving, adverse weather, hazardous situations) are well-represented in the final dataset.
Work with algorithm teams to understand what data gaps hurt model performance and translate those into curation criteria.
Build validation and diagnostics that measure dataset quality - not just pipeline health, but whether the data is actually good for training.
Contribute to the core dataset SDK, converter, and 3D-geometry tooling (camera projection, calibration, coordinate transforms).
Requirements:
4+ years in data engineering or backend/software engineering with serious data work - pipelines that run in production, not just notebooks.
Strong Python and the PyData stack (NumPy, PyArrow, Pandas, DuckDB).
Some background in research, algorithms, or ML - enough that you can read a paper, understand a model's outputs, and have informed conversations with algorithm engineers.
Comfort working with vision-model outputs as data: embeddings, detection results, VLM responses.
Ability to work across team boundaries - this role lives between algorithm teams, infra teams, and our own.
Nice to have:
Experience with autonomous-driving datasets or perception pipelines.
3D geometry and camera model intuition (or the mathematical background to ramp up).
Workflow orchestration (Argo, Airflow, Kubeflow).
Vector databases or columnar analytics (LanceDB, DuckDB, Parquet at scale).
Familiarity with curation concepts (active learning, hard-example mining, distribution balancing) - useful context, not a requirement.
Exposure to LLM agents or agentic workflows for data tasks.
This position is open to all candidates.
 
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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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חברה חסויה
Location: Herzliya
Job Type: Full Time
We are seeking a candidate who views AI tooling as a fundamental force multiplier in their daily engineering process. This position is central to our transition into an AI-native function, requiring an individual capable of making decisive, pragmatic architectural choices on reversible matters to maintain momentum. We need an experienced builder of production-grade, data-centric systems who is obsessed with delivering customer value and possesses a deep, curious enthusiasm for the transformative potential of AI.
What You Will Build:
AI-Native Systems Development. Design, build, and own scalable data and ML pipelines, backend services, and AI-powered capabilities that are part of the platform's production decision-making layer. AI and ML components are runtime dependencies in this role - not research projects or experiments. Candidates will have strong back end and data engineering skills to thrive in this space.
Daily Shipping. Decompose complex work into safely mergeable increments and ship them daily. Treat large, multi-day pull requests as a risk to momentum. Use feature flags, canary releases, and rollback architecture to manage risk through isolation - not through avoidance.
AI-Augmented Engineering Workflow. Leverage AI-assisted development tooling (code generation, automated testing, architecture prototyping) as a core workflow multiplier. Evaluate and experiment with emerging AI tools and frameworks with direct hands-on engagement. Bring technical depth to AI fluency - architecture and capability tradeoffs, not surface-level awareness.
End-to-End Ownership. Own your work from design through production deployment, operational monitoring, and business impact measurement. Accountability extends beyond the feature to CI/CD pipeline health, observability, cost efficiency, and domain-level outcomes.
Architectural Decision-Making. Make pragmatic, timely architectural choices that balance modern AI and data technologies with reliability, cost, and delivery speed. Distinguish reversible vs. irreversible decisions and move forward without waiting for consensus on the former. Document decisions in lightweight ADRs and own the outcomes.
Cross-Functional Collaboration. Partner with product, design, infrastructure, and GTM teams to translate customer and business needs into technical solutions. Operate with business awareness - understand how your systems impact revenue, customer outcomes, and strategic priorities.
דרישות:
5+ years building and shipping production-grade back end and data systems in distributed cloud environments (AWS and/or GCP).
Hands-on AI/ML integration in production workflows. You have shipped systems where AI, LLM, or agent-based components are part of the production runtime - not just prototypes or research. You can speak to the architectural tradeoffs of integrating AI into live backend systems.
Active use of AI-assisted development tooling as a workflow multiplier. You currently use AI tooling (Copilot, Cursor, or equivalent) to accelerate your engineering output and can articulate specifically how it increases your throughput. You stay current on relevant tooling without being directed to do so.
Strong back end expertise in Java (Spring Boot), Python, and/or Go. Hands-on experience with relational and non-relational databases, data modeling, and query optimization.
Demonstrated expertise in automated testing, CI/CD, and observability.
High-Velocity ownership - candidates should thrive in high-ownership, builder-first environments where shipping daily and owning outcomes are fundamental to the role.
Demonstrated ability to break work into small, incremental deliveries and maintain strong delivery flow. You have a track record of decomposing complex work into small, safely mergeable increments and shipping software solutions to solve customer pain continuously. You can describe your approach to scope deconstruction and provide concrete examples.
Preferred
Experience shipping ML-Ops powered s המשרה מיועדת לנשים ולגברים כאחד.
 
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הגשת מועמדותהגש מועמדות
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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.
 
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