As AI-powered commerce becomes a new standard, Teak is building an agentic layer on top of our established platform APIs, letting partner AI agents offer, explain, and fulfill refund solutions compliantly and without friction at the point of purchase. As a Senior AI Engineer, you'll help lead and build that layer end-to-end:
Architecting the agentic systems, integrations, and infrastructure that turn our existing APIs into AI-native capabilities.
This is a hands-on engineering role for someone who owns production AI systems from design through deployment and operation, well beyond prompt work, while staying closely connected through code reviews, technical discussions, and regular team syncs.
This is an excellent opportunity to make a meaningful impact at a rapidly growing company at the forefront of agentic commerce.
Qualifications
Bachelor's Degree in Computer Science, Engineering, a related field, or equivalent practical experience.
5+ years of professional software engineering experience, with at least 2 years focused on production AI/LLM application development.
Strong Python proficiency and solid software engineering fundamentals.
Deep backend engineering experience, designing, building, and operating production services and APIs (Django or similar framework), with strong fundamentals in testing, code quality, and system design.
Hands-on experience building and deploying agentic AI systems (LangGraph, LangChain, AWS Bedrock Agents, or similar).
Demonstrated experience integrating LLM APIs (Anthropic, OpenAI, or similar) into production applications.
Experience building and maintaining RAG pipelines and vector search systems.
Working knowledge of Model Context Protocol (MCP) and tool-calling patterns.
Experience designing and running LLM evaluation frameworks for quality, reliability, and safety.
Experience building and operating AI infrastructure on a major cloud platform (AWS, GCP, or Azure).
Strong written and verbal communication, with the ability to explain AI system design to technical and non-technical stakeholders.
Fully remote position; reliable internet connection and an appropriate home office workspace required.
Requirements
Background in a compliance-sensitive industry (insurance, fintech, legal) where regulated AI output and guardrails matter.
Experience operating LLM systems at high volume, with attention to latency, cost, and caching.
Familiarity with AWS Bedrock or similar managed AI platforms and agent runtimes.
Experience with model fine-tuning, customization, or distillation.
Contributions to open-source AI tooling or frameworks.