Lead AI System Architect
$72,600–$89,760 year
Hybrid · Warsaw, Mazovia, Poland
Job Summary
Lead AI System Architect at EIS leads the architecture of an agentic AI platform that orchestrates multi-agent workflows across policy, billing, and claims domains. Owns patterns, MCP-native tool ecosystems, agent memory, planning, tool calling, and safety with a focus on autonomous and semi-autonomous agents, human-in-the-loop checkpoints, and scalable automation. Drive MCP strategy, maintain multi-stack support (Typescript and Java), ensure observability and compliance, set safe-AI standards, translate insurance use cases into production agent designs, and provide technical leadership and mentorship to executives, customers, and engineers. Strong emphasis on scalable architecture, software quality, and regulated-domain awareness.
Required Qualifications
- Proven track record designing and shipping agentic systems in production with meaningful autonomy and multi-step tool use
- Strong systems background: data-intensive, distributed, latency-sensitive design
- Hands-on with agent patterns: orchestration, planning, ReAct-style and graph-based agents, memory, tool/function calling, MCP
- Experience with Java/Spring ecosystem
- Experience with Typescript and Python for AI (LangChain, LangGraph, or equivalent) in production
- Hands-on with vector databases including embedding models, hybrid search, and retrieval evaluation
- Experience with agent evaluation and observability: traces, replays, eval harnesses, guardrails, cost/latency telemetry
- Experience shipping AI services on cloud platforms (AWS, Azure, GCP) in regulated enterprise environments (security review, data residency, audit trails)
- Familiarity with insurance, financial services, or other regulated domains (a plus)
- Strong architectural judgment on build vs. buy, vendor vs. in-house, agent vs. deterministic workflow, model choice, total cost of ownership
- Excellent written and verbal communication; ability to communicate agentic trade-offs to non-AI audiences
- Advanced degree in Computer Science, AI/ML, or related field or equivalent practical experience
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