דרושים » AI » AI Principal Engineer

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.

We are looking for a Senior AI Engineer to join our Cybersecurity team in Tel Aviv. You will design, build, and productionize LLM-powered applications, multi-agent systems, and MLOps infrastructure that power our company's next-generation cybersecurity capabilities. This is a high-impact, hands-on role at the intersection of applied AI, agentic systems, and network securit
What You'll Do
Design and develop LLM-powered security features and internal AI tools, including RAG pipelines, multi-agent workflows, and prompt-engineered systems tailored for cybersecurity use cases
Architect and operate multi-agent systems in production - including agent orchestration, inter-agent communication, task delegation, and failure handling at scale
Build robust agent monitoring and observability pipelines: tracing agent execution, detecting drift or failure, alerting on anomalous behavior, and maintaining agent reliability SLAs
Build and maintain scalable MLOps infrastructure: model serving, evaluation frameworks, experiment tracking, and CI/CD for ML models
Work with internal datasets (network telemetry, security logs, threat intelligence) to fine-tune and adapt foundation models for domain-specific detection and response tasks
Partner with the Cybersecurity, R&D, and infrastructure teams to define AI-driven security features and deliver them end-to-end
Establish best practices for model observability, safety, and responsible AI deployment within the organization
Stay current with the fast-moving LLM/GenAI and agentic AI ecosystem and evaluate emerging frameworks, models, and tools for adoption.

you will work at the intersection of Machine Learning and software engineering - selecting the right models, feedback strategies, and evaluation frameworks to make ai-generated code reliable, high-quality, and trustworthy.
what you'll be doing:
design and build ai-powered development pipelines - from code generation and automated review to feedback loops and evaluation systems.
evaluate and select ml approaches for specific problems: when to use llm prompting vs. fine-tuning (qlora), classical ml (random forest, linear regression) vs. reinforcement learning, rag vs. structured extraction.
architect feedback and evaluation systems that measure and improve ai output quality over time.
review and refine ai solution architectures - evaluate design decisions, identify weaknesses, propose alternatives with reasoning.
lead proof-of-concept development to validate new ai/ml approaches for development tooling.
collaborate with the core team to define risk-based development levels and calibrate ai review depth per level.

We are looking for a highly motivated AI Full stack Engineer with GenAI background in production to join our team and help us shape the future of the Agentic engineering platform (AEP).



What youll do:

were a platform by developers, for developers. Your role will encompass end-to-end design, implementation, and daily feature delivery across both backend and frontend systems.



You will:

Implement high scale AI-powered features deeply integrated into our platform
Design and build production-grade backend systems serving a wide and growing user base
Build agent-based workflows using frameworks such as AI SDK
Integrate LLMs into real production systems with attention to reliability, latency, observability, and cost
Work across frontend (React + TypeScript) and backend (NodeJS, Python, Go) to deliver complete AI-driven user experiences
Own features end-to-end: design, implementation, testing, deployment, and monitoring
Help define standards and best practices around AI reliability and evaluation
Contribute to technical planning, mentor teammates, and help recruit top talent
Develop retrieval-augmented generation (RAG) pipelines over structured and unstructured data

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.

We are seeking an experienced Generative AI Engineer to join our AI squad . This is a unique opportunity to wear multiple hats - serving as both a developer of cutting-edge GenAI solutions and an advisory expert helping organizations transform their AI capabilities. You'll build end-to-end GenAI projects from conception to production while staying at the forefront of this rapidly evolving field.
Key Responsibilities:
GenAI Development & Implementation
End-to-End Development: Build GenAI solutions from POC through production deployment, handling all backend development responsibilities
Client Engagement: Participate in technical discussions with clients, gather requirements, and help translate business visions into feasible technical solutions through presentations and consultations
Backend Development: Design and implement production-grade microservices architectures for GenAI applications using Python
Cloud Implementation: Deploy and manage GenAI solutions across GCP, Azure, and AWS platforms, leveraging cloud-native AI services
Cross-functional Collaboration: Work closely with project managers, full-stack developers, and Power Automate teams to deliver complete solutions
System Evaluation: Assess and optimize production-grade GenAI systems for performance, scalability, and reliability

We're looking for a talented Software Engineer with enthusiasm for AI/GenAI to join our innovation-focused team building agentic AI systems autonomous, reasoning-driven software agents capable of orchestrating complex tasks across tools, APIs, and data sources.
You'll design and build scalable backend systems that integrate large language models (LLMs) and other AI technologies into production-grade services. This role blends backend engineering, AI integration, and rapid prototyping, with room to learn, experiment, and deliver impactful, scalable solutions.
Architect and implement distributed services that power AI-driven applications.
Implement multi-step reasoning pipelines, retrieval-augmented generation (RAG), and domain-specific AI capabilities.
Build robust APIs, plugins, and integrations enabling AI agents to interact with external systems and data sources.
Create and refine proof-of-concepts, validating ideas quickly before scaling to production.
Implement monitoring, evaluation, and logging systems to track AI-powered features in production.
Work closely with product managers, designers, data scientists, and AI engineers to deliver user-focused solutions.
Stay curious about emerging AI frameworks, tools, and best practices to improve reasoning, planning, and autonomy in backend services.

At our company, we build AI-powered vision systems that enhance safety and decision-making for some of the worlds largest vessels.
Our platform processes live video streams from multiple onboard cameras to provide real-time situational awareness, detecting and tracking marine objects, even in low visibility and highly congested environments. These systems directly support navigational decisions and help prevent collisions, reduce human error, and improve operational efficiency.
Our systems are already deployed across thousands of vessels and have processed hundreds of millions of nautical miles of real-world data, operating in unpredictable and safety-critical conditions.
This role sits at the intersection of AI and high-performance systems engineering, focused on solving real-world problems under strict constraints. You will work on systems where performance and reliability are critical and where improvements have a direct, measurable impact on real-world safety.
This is a senior, systems-focused role with end-to-end ownership over performance and reliability of production computer vision pipelines. You will define optimization strategies, identify bottlenecks across the system, and drive improvements under real-world constraints.
What youll do
Build and optimize real-time computer vision pipelines running on edge systems processing live maritime video streams (e.g, NVIDIA Jetson, Triton Inference Server)
Take models from research and turn them into production-ready, reliable components deployed on vessels
Profile and improve end-to-end system performance across: multi-camera video ingestion; preprocessing; inference; postprocessing
Identify and resolve bottlenecks across CPU, GPU, memory, and pipeline coordination
Make and justify tradeoffs between latency, accuracy, stability, and resource utilization
Design and implement robust data and inference pipelines (video -> model -> actionable output for crew)
Develop benchmarking and evaluation workflows to measure performance end-to-end and support release gating
Build and improve observability tools, including logging, monitoring, and debugging workflows for production systems
Define and maintain clear interfaces between research code and production systems
Work closely with research and backend teams to integrate new models into production systems
Continuously improve system efficiency and reliability under hardware and runtime constraints.

Required xEngineer (ai-native software engineer)
makes it possible for anyone to succeed online. since 2006, weve grown to around 5,500 employees in 22 countries, launched over 40 products, and serve over 243 million users and their visitors worldwide. here, we push you to innovate, evolve in non-traditional ways, and collaborate. we operate in small teams that work closely together at a high level.
although were already industry leaders in web creation and business, our work is nowhere near done. our goal is to become the main engine of the internet so we can create a more open web for all.
we're proud to be an equal opportunity employer. the company was built around the idea that everyone has the right to be successful, online. this same vision defines us as an employer: creating a work environment where everyone is welcome, and anyone has the right to succeed.
as an xEngineer, youll combine deep technical expertise with system -level thinking and product ownership, applying ai across the development lifecycle to build impactful systems, make thoughtful architectural decisions, and drive technical excellence from idea to production. in your day-to-day, you will:
design and own end-to-end systems and features that serve millions of users, taking responsibility across stack boundaries - from product flows and User Experience to apis, data models, and production systems
apply ai-powered tools and workflows across planning, design, implementation, testing, debugging, and refactoring
work with modern technologies and platforms (e.g., typescript, React, Node.js, JAVA, cloud, and ci/cd), continuously evolving your toolkit with ai-powered tools
lead architectural thinking by making thoughtful trade-offs around scalability, reliability, security, performance, and maintainability
collaborate closely with product managers, designers, and engineers to shape solutions while ensuring production quality, observability, and long-term system health
at the company, we believe our best work happens together. our work model is fully in person, with 5 days a week from our office. flexibility remains a core value at the company and special requests are handled thoughtfully at the team level.
we are engineering at the company - a team of ai-native xengineers with deep expertise in frontend, backend, or mobile, who use ai support to take ownership over projects end-to-end. we work in a fast-paced, dynamic development environment with autonomous teams that never compromise high quality standards. as ai increasingly generates production code, we dedicate more and more of our time developing the skills we believe are critical for today and tomorrow: system design, architecture, scalability, reliability, and security.