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AI Platform Engineering Team Lead

·Israel
Not specifiedFull-timeAI EngineeringFinTech

Lead and build alongside a team of engineers creating AI agents, intelligent workflows, and decision-making systems. Own architecture, production systems, and team growth in a fintech environment focused on reliable, secure, and scalable AI solutions.

Responsibilities

  • Lead a team of software engineers and build alongside them
  • Own architecture and evolution of the AI Platform
  • Build production-grade AI agents, intelligent workflows, and decision-making systems
  • Combine LLMs with business logic, data, tools, and deterministic software
  • Own AI systems across full lifecycle from design to continuous improvement
  • Make architectural trade-offs across accuracy, latency, scalability, reliability, security, and cost
  • Turn ambiguous product and business problems into clear technical direction
  • Raise the bar for code quality, system design, and engineering execution
  • Help strong engineers become exceptional

Requirements

  • 7+ years of software engineering experience with strong backend, platform, or distributed systems background
  • 3+ years leading engineers including mentoring, technical direction, and performance ownership
  • Hands-on experience shipping LLM- or GenAI-powered capabilities to production
  • Practical understanding of agentic systems, tool use, orchestration, RAG, evaluations, and AI observability
  • Experience building and operating complex, distributed, or event-driven systems at scale
  • Strong architectural judgment balancing speed with long-term quality
  • Hands-on mindset with active code writing, reviewing, and challenging
  • Ability to connect technical decisions with product, customer, and business outcomes
  • Ownership extending beyond immediate team or scope
  • Active use of AI development tools such as Codex, Claude Code, and Cursor

Nice to have

  • Experience with Node.js, TypeScript, and Python
  • Experience with Kafka, AWS, MongoDB, PostgreSQL, Docker, Kubernetes, and ECS
  • Experience with AI evaluation, monitoring, and observability

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