AI Engineer (Mid-Level)
Remote · United States or San Francisco, California, United States
Job Summary
Design, build, and maintain agentic AI-driven systems that automate complex, multi-step workflows across regulated domains; own production RAG pipelines and vector-based retrieval infrastructure; implement multi-agent orchestration, tool-calling, memory, and reasoning components; develop evaluation and safety infrastructure to measure model performance and reliability; ship full-stack AI products from MVP to enterprise-grade, including API and data-model design, frontend and backend code, and production operations with CI/CD, monitoring, and testing; collaborate with leadership, product, and design to prioritize work and iterate based on user feedback and telemetry.
Required Qualifications
- 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
- 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
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