AI Engineer Team Leader

Location: Israel

Company

hirify.global provides an AI-native Agentic HR platform powered by a workforce context engine, supporting talent redeployment, internal mobility, skills intelligence, and workforce redesign.

What you will do

• Manage, mentor, and grow a team of AI and software engineers.
• Plan sprints, allocate work, and lead daily agile ceremonies.
• Design and build multi-agent systems covering intent routing, planning, tool use, and coordination.
• Drive architecture and engineering practices for scalable LLM applications grounded in a knowledge graph.
• Integrate LLMs with tool calling and MCP to connect agents to HCM systems, business logic, and workflows.
• Build evaluation harnesses, guardrails, monitoring, and observability while optimizing latency, cost, safety, and reliability for production use.

Requirements

• 2+ years of experience managing or leading a high-performing software or AI engineering team.
• 5+ years of hands-on experience as a Backend or AI/Software Engineer building complex, scalable distributed systems in production.
• Proven experience building and shipping LLM agents to production, including hands-on experience with an agent orchestration framework such as LangGraph, LangChain, AutoGen, CrewAI, or Semantic Kernel.
• Strong Python skills, solid software engineering fundamentals, and strong agile project management and sprint execution skills.
• Ability to work effectively in a dynamic, high-pressure startup environment with frequent changes in direction.
• Excellent communication skills and ability to collaborate with Product Managers and cross-functional stakeholders.

Nice to have

• 2+ years of hands-on experience with LLMs or generative AI.
• Practical experience with RAG, embeddings, and vector databases such as pgvector or Pinecone.
• Experience with tool use, function calling, MCP, agent memory, and planning or reasoning patterns.
• Experience with responsible AI, including bias evaluation, guardrails, and AI governance.

Culture & Benefits

• Fast-paced startup environment with frequent pivots and rapid development cycles.
• 50% hands-on engineering and 50% team leadership responsibilities.
• Close collaboration with Product Management, Data, Design, and enterprise customers.
• Focus on reliable, safe, scalable, and fast AI product experiences.