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AI Summary
About the Role
This is a mid-level AI Engineer role on the core product team, focused on building agentic systems that automate complex, multi-step workflows across regulated and enterprise domains. You'll work across the full stack to ship production LLM-based services, ensure reliability and safety, and collaborate with leadership, product, and design to deliver measurable user impact.
What You'll Do
Design, build, and maintain agentic systems that automate complex, multi-step workflows across healthcare, legal, fintech, logistics, and compliance domains.
Own production retrieval-augmented generation (RAG) pipelines and retrieval infrastructure including vector databases, embeddings, and indexing for domain-specific search at scale.
Implement multi-agent orchestration, tool-calling, memory, and reasoning components to deliver robust AI-driven user experiences.
Develop evaluation and safety infrastructure to measure model performance, surface regressions, and enforce enterprise-level trust and reliability.
Ship full-stack AI products from MVP to enterprise-grade by designing APIs and data models, implementing frontend and backend code, and operating production systems with CI/CD, monitoring, and testing.
Collaborate with leadership, product, and design to prioritize work, define success metrics, and iterate based on user feedback and telemetry.
What We're Looking For
2–8 years of software engineering experience with demonstrated delivery of shipped user-facing or backend products.
Practical experience deploying LLMs or LLM-based services in production, including prompt design, orchestration, and tool integration.
Proficiency across the stack: Python plus TypeScript/React (or equivalent), and experience with cloud platforms (AWS or GCP) and relational or NoSQL databases.
Working knowledge of RAG patterns, vector databases, embeddings, and retrieval pipelines, with sound judgment to choose appropriate approaches.
Experience building automated tests, evaluations, and monitoring for AI systems to ensure reliability beyond demos.
Experience with agent or workflow frameworks and orchestration tools.
Familiarity with fine-tuning, parameter-efficient tuning, or multi-modal model integration.
Background building multi-tenant or enterprise-ready systems, or experience in regulated industries such as healthcare, fintech, or legal.
Experience designing API-driven, high-throughput systems and real-time product features.
Proven ownership delivering end-to-end features from data model to deploy and monitoring, with a user-centric and pragmatic engineering mindset.
Location
Remote or San Francisco, CA, United States.
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