Senior AI Engineer

Key Responsibilities

• Agentic System Design: Design, build, and maintain production-grade agentic systems, multi-agent orchestration, specialist agents, and Human-in-the-Loop workflows, with context management, memory, and tool-calling.

• MCP & Tool Integration: Develop MCP servers and tool integrations connecting AI agents to Teak's platform APIs and partner systems.

• LLM Integration & Output Control: Orchestrate LLMs (Claude, GPT, Gemini, or similar) across the AI layer, selecting the right model per task and managing prompt and system-prompt strategies so agents present refund solutions in pre-approved, compliant language.

• RAG & Knowledge Systems: Build RAG pipelines that ground agent responses in Teak's policy and product data, with versioning and isolation that prevent hallucination on compliance-sensitive topics.

• Compliance & Safety: Implement guardrails that enforce compliant offer language, prevent unauthorized coverage claims, and meet regulatory requirements across Teak's markets.

• Evaluation: Build evaluation frameworks to monitor, test, and continuously improve agent performance, reliability, and output quality.

• AI Infrastructure & Observability: Build and operate AI infrastructure on AWS, with structured logging and tracing for auditability and rapid issue resolution.

• Backend Development: Contribute to backend services, APIs, and platform improvements in Python alongside AI work, applying clean code, testing, and strong engineering fundamentals.

• Collaboration & Code Quality: Participate in code reviews, document agent system design and integration patterns, take part in Agile workflows, and join the on-call rotation.