Generative AI Technologist

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8647359

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05/04/2026

AI Developer

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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8600287

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לפני 4 שעות

AI Engineer, Exposure Management 25674

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

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

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

This position is open to all candidates.

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8650206

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04/05/2026

AI Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

Join us to build cutting-edge systems, collaborate with world-class engineers, and shape how autonomous software is built in production.
We are looking for an AI Engineer to join the hunt.
Responsibilities:
Take part in the design and development of AI-driven features for our Dev-Native Observability Platform.
Collaborate with cross-functional teams to integrate AI solutions into existing systems.
Contribute to the product roadmap by identifying AI opportunities and providing insights as a potential end user
Stay updated with the latest AI trends and technologies to ensure our platform remains cutting-edge.

Requirements:
At least 3 years experience in Python / TS working with AI/ML frameworks
At least 5 years of backend experience with at least one additional programming language (Java / C# / Node.js / C++)
At least 3 years experience working with database solutions (RDBMS, NoSQL, Vector)
Proven experience with writing efficient and useful LLM prompts
Proven experience building LLM-based solutions and integrating them into products
Strong system and architecture design skills, particularly in designing LLM based systems
Experience or at least substantial knowledge of GenAI technologies such as agentic flows, RAG, model fine-tuning / distilling, prompt engineering, context engineering
Hands-on experience with cloud platforms and their AI/LLM services
Experience working on a SaaS product - Advantage
Experience working with customers and direct customers feedback - Advantage
Experience using observability / profiling / remote debugging tools - Advantage
Passionate about AI and up to date with industry trends - Advantage

This position is open to all candidates.

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8636279

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1 ימים

AI Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time and Hybrid work

We are seeking an AI Engineer to design, build, and deploy AI-powered capabilities within our product.
This role focuses on integrating machine learning models and large language models (LLMs) into scalable software systems and delivering reliable AI-driven features to production.
The AI Engineer works at the intersection of software engineering, AI systems, and infrastructure.
transforming AI technologies into practical applications.
Responsibilities:
Build applications powered by machine learning and large language models (LLMs).
Implement capabilities such as intelligent assistants, semantic search, automation, and recommendation systems.
Integrate AI functionality into backend services and product workflows.
Design and implement retrieval pipelines, embedding pipelines, and inference workflows.
Build Retrieval-Augmented Generation (RAG) systems and AI-driven services.
Create scalable AI architectures capable of handling production workloads.
Package and deploy AI models as production services.
Optimize inference performance, scalability, and latency.
Monitor AI services to ensure reliability and performance.
Develop backend services and APIs that expose AI capabilities.
Integrate AI systems with databases, internal services, and external APIs.
Contribute to system architecture and microservices design.
Implement logging, metrics, and observability for AI systems.
Track model performance and system reliability in production environments.
Work closely with product managers, engineers, and data scientists.

Requirements:
5+ years of programming skills in one or more modern languages (such as Python, Java, Go, or similar).
Experience building backend services and APIs.
Experience integrating machine learning models or LLMs into applications.
Understanding of microservices architecture and distributed systems.
Experience with Docker and containerized applications.
Familiarity with Kubernetes or cloud infrastructure.
Experience working with databases and data processing pipelines.

Preferred Qualifications:
Experience building LLM-based applications.
Experience with RAG architectures and embeddings.
Experience with vector databases or semantic search systems.
Familiarity with model serving frameworks or inference platforms.
Experience working in production AI environments.

Strong Advantage:
Experience working with local or self-hosted AI models (e.g., Llama, Mistral, or similar).
Experience deploying AI models in on-premise or private cloud environments.
Familiarity with running LLM inference locally using frameworks such as Ollama, vLLM, or Hugging Face Transformers.
Experience optimizing models for GPU/CPU inference and resource-constrained environments.

This position is open to all candidates.

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8647936

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לפני 4 שעות

Senior ML Research Engineer 25539

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

Join our companys AI research group, a cross-functional team of ML engineers, researchers and security experts building the next generation of AI-powered security capabilities. Our mission is to leverage large language models to understand code, configuration, and human language at scale, and to turn this understanding into security AI capabilities which will drive our company AI future security solutions.
We foster a hands-on, research-driven culture where youll work with large-scale data, modern ML infrastructure, and a global product footprint that impacts over 100,000 organizations worldwide.
Key Responsibilities
As a Senior ML Research Engineer, you will be responsible for the end-to-end lifecycle of large language models: from data definition and curation, through training and evaluation, to providing robust models that can be consumed by product and platform teams.
Own training and fine-tuning of LLMs / seq2seq models: Design and execute training pipelines for transformer-based models (encoder-decoder, decoder-only, retrievalaugmented, etc.), and fine-tune open-source LLMs on our company-specific data (security content, logs, incidents, customer interactions).
Apply advanced LLM training techniques such as instruction tuning, preference / contrastive learning, LoRA / PEFT, continual pre-training, and domain adaptation where appropriate.
Work deeply with data: define data strategies with product, research and domain experts; build and maintain data pipelines for collecting, cleaning, de-duplicating and labeling large-scale text, code and semi-structured data; and design synthetic data generation and augmentation pipelines.
Build robust evaluation and experimentation frameworks: define offline metrics for LLM quality (task-specific accuracy, calibration, hallucination rate, safety, latency and cost); implement automated evaluation suites (benchmarks, regression tests, redteaming scenarios); and track model performance over time.
Scale training and inference: use distributed training frameworks (e.g. DeepSpeed, FSDP, tensor/pipeline parallelism) to efficiently train models on multi-GPU / multi-node clusters, and optimize inference performance and cost with techniques such as quantization, distillation and caching.
Collaborate closely with security researchers and data engineers to turn domain knowledge and threat intelligence into high-value training and evaluation data, and to expose your models through well-defined interfaces to downstream product and platform teams.

Requirements:
What You Bring
5+ years of hands-on work in machine learning / deep learning, including 3+ years focused on NLP / language models.
Proven track record of training and fine-tuning transformer-based models (BERT-style, encoder-decoder, or LLMs), not just consuming hosted APIs.
Strong programming skills in Python and at least one major deep learning framework (PyTorch preferred; TensorFlow).
Solid understanding of transformer architectures, attention mechanisms, tokenization, positional encodings, and modern training techniques.
Experience building data pipelines and tools for large-scale text / log / code processing (e.g. Spark, Beam, Dask, or equivalent frameworks).
Practical experience with ML infrastructure, such as experiment tracking (Weights & Biases, MLflow or similar), job orchestration (Airflow, Argo, Kubeflow, SageMaker, etc.), and distributed training on multi-GPU systems.
Strong software engineering practices: version control, code review, testing, CI/CD, and documentation.
Ability to own research and engineering projects end-to-end: from idea, through prototype and controlled experiments, to models ready for integration by product and platform teams.
Good communication skills and the ability to work closely with non-ML stakeholders (security experts, product managers, engineers).

This position is open to all candidates.

עדכון קורות החיים לפני שליחה

8650168

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09/04/2026

Senior AI Engineer - Applied AI Engineering Group

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

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

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

עדכון קורות החיים לפני שליחה

8603620

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20/04/2026

Senior AI Ops / MLOps Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

At our company, we aren't building a single, generic chatbot. We are building a Composable AI Microservice Architecture, a swarm of hundreds of hyper-specialized AI services, each meticulously "programmed" to solve small, focused tasks with high precision. This fleet powers Ava, our AI support engine, and a suite of cutting-edge generative tools for travel and expense management.
As a Senior AI Ops / MLOps Engineer, you are the architect of the platform that makes this scale possible. You will move beyond traditional MLOps to manage a "factory" of Language Models. Your challenge is one of orchestration and standardization, ensuring that every service in the swarm meets a rigorous bar for quality, reliability, and cost-efficiency.
What You'll Do
Orchestrate the AI Fleet: Build and own the runtime environment for 100+ specialized AI services. Manage model routing, context versioning, and standardized memory/history stores.
High-Density Inference Optimization: Design and implement SageMaker Multi-Model Endpoints (MME) and Inference Components to serve multiple tuned SLMs per GPU, maximizing hardware utilization while minimizing latency.
Deterministic Service Excellence: Treat reliability as a layered engineering problem. Build deterministic "shells" around probabilistic LM outputs, prioritizing data-layer validation and strict serialization.
Automated Evaluation & Observability: Implement "LLM-as-a-judge" patterns and automated benchmarking to detect semantic drift and hallucinations across the fleet before they impact the user.
Standardize the Workflow: Obsess over building reusable patterns and Terraform-based infrastructure that eliminate "snowflake" configurations, allowing us to deploy new specialized AI tasks in minutes.
Agency Strategy: Partner with AI Researchers to find the "Goldilocks zone" for agentic autonomy-balancing the flexibility of LLM tool-use with the precision required for production stability.

Requirements:
Experience: 5+ years in SRE, Platform Engineering, or MLOps, with at least 2 years focused on deploying LLMs/SLMs in production environments.
SageMaker Mastery: Deep hands-on expertise with AWS SageMaker, specifically configuring Multi-Model Endpoints (MME), Inference Components, and GPU-backed instances (G5/P4).
SLM Expertise: Proven experience with Small Language Models (e.g., Mistral, Llama 3, Phi) and parameter-efficient fine-tuning (PEFT) deployment strategies like LoRA/QLoRA.
Technical Stack: * Languages: Strong proficiency in Python and Terraform.
Orchestration: Experience with Docker, Kubernetes (EKS), or AWS ECS/Fargate.
Data: Familiarity with Snowflake and Vector Databases.
The "AI Ops" Mindset: You understand that AI at scale is a statistical challenge. You are comfortable debugging issues at the data/serialization layer rather than defaulting to prompt tweaks.
CI/CD & Automation: Experience building robust pipelines (Jenkins, GitHub Actions) for non-deterministic software, including automated "eval" stages.
Education: BS or MS in Computer Science, Engineering, Mathematics, or a related technical field.
Must have
Python, Terraform, Sagemaker.

This position is open to all candidates.

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8618201

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09/04/2026

AI Engineering Team Lead - Applied AI Engineering Group

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

Required AI Engineering Team Lead - Applied AI Engineering Group
Tel Aviv Full-time
The Dream Job
It starts with you - a technical leader driven to build both the agentic AI platform and the engineering team behind it. You care about backend quality, platform reliability, and growing engineers through real ownership. We are AI-first across the board - every team builds and operates agents. You'll set the technical direction for the platform that makes this possible: agent orchestration frameworks, LLM gateways, evaluation infrastructure, tool-calling systems, and retrieval pipelines. Without this platform, agents don't ship - you own the layer that turns AI research into Sovereign AI products, deployed across cloud and on-prem environments. You stay close enough to the codebase to debug production incidents, unblock your engineers, and make sound architecture calls.
If you want to make a meaningful impact, join our mission and lead the team that builds the agentic AI platform driving Sovereign AI products - this role is for you.
The Dream-Maker Responsibilities
Architect and evolve the AI platform - agent orchestration, LLM gateways, context engineering pipelines, evaluation infrastructure, tool-calling systems, and retrieval pipelines - through RFCs, prototypes, and design reviews.
Lead and grow a small team of AI Engineers building the agent framework, production backend services, and AI platform infrastructure - hire, mentor, pair on hard problems, and raise the bar through hands-on code and design reviews.
Contribute to critical systems, debug production incidents, and maintain enough codebase context to make sound technical calls.
Own reliability across AI and agent services - set and enforce SLAs, build observability for non-deterministic systems, and harden tool execution environments for cost and security.
Set the standard for AI engineering practices - agent testing strategies, evaluation frameworks with human-in-the-loop oversight, retrieval quality benchmarks, and CI/CD for AI systems.
Work closely with ML Platform, Data Platform, DevOps, Data Science, and Product teams across the Applied AI Engineering group - ensure the AI platform evolves to serve teams building agentic workflows across the organization.
Measure and improve developer experience - deploy friction, onboarding time, CI turnaround - as seriously as system performance.

Requirements:
6+ years in backend software engineering, with 4+ years focused on production systems that integrate AI/ML models or LLMs.
2+ years leading an engineering team - hiring, mentoring, conducting design reviews, and shipping alongside your team.
Engineering craft - Strong Python, Go, or Java, system architecture, API design, testing, and secure coding practices.
Agentic systems & LLM integration - Deep understanding of agent orchestration, tool-use architectures, LLM integration patterns, context engineering, and frameworks like LangGraph or similar, or custom-built equivalents
Backend & platform engineering - Experience building and operating production APIs, services, and platform infrastructure at scale; comfortable working with relational databases, message queues, and event-driven architectures
RAG & retrieval - Experience with production RAG pipelines, vector databases, embedding systems, and retrieval quality
Evaluation & observability - Experience building LLM and agent eval infrastructure, monitoring AI quality, and observability for non-deterministic systems
Nice to Have:
Platform & infra - Kubernetes, AWS, Terraform or similar IaC, CI/CD, service architecture, incident management
Experience with MCP or similar tool-use protocols for agent-to-service communication
Hands-on ML experience - model training, fine-tuning, or working directly with ML pipelines.

This position is open to all candidates.

עדכון קורות החיים לפני שליחה

8603446

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מייל

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שליחה

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13/04/2026

Machine Learning Engineer - AI Coding Agents & LLM Infrastructure

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

Required Machine Learning Engineer - AI Coding Agents & LLM Infrastructure
Tel Aviv
Full-time
A bit about us:
We are redefining how software gets built. Trusted by over 1M+ developers, we build AI-first developer experiences powered by state-of-the-art coding agents and code reasoning models. With support for 30+ programming languages and 15+ IDEs, our platform is pushing the limits of LLM-based software engineering - enabling teams to design, write, review, and ship code faster than ever. Were committed to advancing code-native AI models, multi-agent systems, agent orchestration frameworks, memory, and autonomous dev tooling to empower developers at every step of the software lifecycle.
Were growing fast, and our team is passionate about pushing AI engineering to new heights - solving complex problems in LLM training, inference optimization, reasoning, and agent orchestration at scale.
About the Role:
As a Machine Learning Engineer, youll work on cutting-edge
code-focused LLMs and AI agent systems
that power our next-generation developer platform. Youll be at the center of research, model training, and productionization of intelligent systems that understand software deeply, collaborate with developers, and help automate engineering workflows end-to-end. Your work will immediately impact millions of engineers worldwide.
Responsibilities:
Push LLM Innovation: Research, design, and fine-tune domain-specific LLMs for code generation, refactoring, debugging, and multi-turn reasoning.
Agent-Oriented Development: Build multi-agent coding systems that integrate retrieval-augmented generation (RAG), code execution, testing, and tool use to create autonomous, context-aware coding workflows.
Production-Grade AI: Own the training-to-inference pipeline for large code models-optimize inference with quantization, distillation, and caching techniques.
Rapid Experimentation: Prototype and validate ideas quickly; leverage reinforcement learning, human feedback, and synthetic data generation to push accuracy and reasoning.
Cross-Functional Collaboration: Partner with product, engineering, and design teams to ship AI-powered features that help developers focus on high-impact work.
Scale the Platform: Contribute to distributed training, scalable serving systems, and GPU/TPU-efficient architectures for ultra-low-latency developer tools.

Requirements:
2+ years of hands-on experience designing, training, and deploying machine-learning models
M.Sc. or higher in Computer Science / Mathematics / Statistics or equivalent from a university, or B.Sc. with strong hands-on ML experience
Practical experience with Natural Language Processing (NLP) and LLMs
Experience with data acquisition, data cleaning, and data pipelines
A passion for building products and helping people, both customers and colleagues
All-around team player, fast, self-learning individual
Nice to have:
3+ years of development experience with a passion for excellence
Experience building AI coding assistants, code reasoning models, or dev-focused LLM agents.
Familiarity with RAG, function-calling, and tool-using LLMs.
Knowledge of model optimizations (quantization, distillation, LoRA, pruning).
Startup or product-driven ML experience, especially in high-scale, latency-sensitive environments.
Contributions to open-source AI or developer tools.

This position is open to all candidates.

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8608813

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חברת השמה / כח אדם

03/05/2026

AI Applied Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

Were looking for a hands-on, product-minded AI professional to help us tackle real-world cybersecurity challenges using existing LLM technologies (like OpenAI, Claude, Bedrock, and more). Youll be part of the Product & AI team, working closely with product managers, engineers, and internal stakeholders to translate problems into smart, working AI-powered solutions.
This is not a researcher or data science role. Its a solution-driven, execution-oriented position for someone who knows what LLMs can do, and how to make them deliver value today.
Key Responsibilities:
Design AI-powered solutions using off-the-shelf tools and APIs (prompting, chaining, agents, etc.)
Collaborate with product and R&D teams to deliver working features and PoCs
Own the how of AI: from idea to prototype to functional integration
Track AI industry trends and apply relevant ideas and tools
Act as a cross-functional bridge between product, tech, and innovation

Requirements:
Must-Have:
2+ years of hands-on experience with GenAI tools (OpenAI, Claude, Bedrock, etc.)
Proven ability to build LLM-based solutions without model training
Familiarity with frameworks like LangChain, vector DBs, RAG
Ability to run quick PoCs (via Python, JS, no-code tools, etc.)
Solid understanding of prompt engineering and use-case design
Experience working with product managers or customer-facing teams
Strong communication and problem-solving skills
Background in software, product, AI, or system architecture
Nice-to-Have:
Experience in cybersecurity or automotive domains
Experience working in startups or agile product environments

This position is open to all candidates.

עדכון קורות החיים לפני שליחה

8633571

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