F
AI Team Lead
·Israel
Not specifiedFull-timeAI EngineeringAviation
Seeking a hands-on technical leader to architect and lead development of production LLM applications, managing a cross-functional team and ensuring production readiness through evaluation, observability, and scalable architecture.
Responsibilities
- Lead a cross-functional team of engineers and data scientists developing LLM-based applications.
- Translate product and business goals into technical roadmaps, milestones, and deliverable plans.
- Own end-to-end delivery from architecture and experimentation through deployment, monitoring, evaluation, and continuous improvement.
- Design LLM workflows using RAG, tool calling, structured outputs, agents, deterministic logic, and human-in-the-loop patterns.
- Establish evaluation-driven development practices for LLM features.
- Define quality metrics, regression tests, golden datasets, production feedback loops, and observability standards.
- Ensure systems meet production standards for scalability, performance, reliability, security, and maintainability.
- Provide technical guidance, architectural oversight, mentorship, and career development for team members.
- Manage priorities, scope, risks, and trade-offs across multiple streams of work.
- Partner with product, design, DevOps, data engineering, security, and other technical leaders.
Requirements
- 8+ years of software engineering experience, including 3+ years in technical leadership, team leadership, or architecture roles.
- Solid background in ML & LLM foundations and development methodologies.
- Solid background in classical software engineering.
- Proven track record leading cross-functional teams and delivering complex production-grade systems.
- Strong understanding of modern software architecture, distributed systems, APIs, cloud-native systems, and scalable application design.
- Fluency in fullstack technologies: python, typescript, javascript, SQL, NoSQL.
- Hands-on experience with LLM-based, AI-assisted, ML-powered, or data-intensive applications.
- Practical understanding of RAG, tool calling, structured outputs, prompt/version management, workflow orchestration, agents, and LLM evaluation.
- Advanced usage of LLM based coding assistance technologies: claude code, codex, etc.
- Experienced and pragmatic code reviewer.
- Strong ability to plan, prioritize, and execute across multiple streams of work.
- Strong judgment around architecture, reliability, latency, cost, security, data access, and user trust.
- Excellent leadership, communication, mentoring, and decision-making skills.
Nice to have
- Background in NLP, search, data-intensive systems, or applied data science.
- Experience with vector search, hybrid search, embeddings, reranking, document processing, and retrieval evaluation.
- Experience with LLM observability, evaluation harnesses, model gateways, MLOps, or ML platform practices.
- Experience with enterprise LLM applications, data assistants, workflow copilots, text-to-SQL, BI systems, or semantic layers.
- Experience with CI/CD, containerized services, k8s, data pipelines, production monitoring, GCP.