AI Engineer (Mid-Level)

San Francisco on site Until 10/1/2026 2+ years exp First posted August 2, 2026 Last posted August 2, 2026
Job description

About the Role

We're a pre-seed AI-powered HR tech startup based in San Francisco, building the next generation of intelligent talent-matching products. Our core product team is small, fast-moving, and deeply technical — you'll work shoulder-to-shoulder with founders, product, and design to ship agentic systems that automate complex, multi-step workflows across regulated and enterprise domains.

We're looking for a mid-level AI Engineer (2–8 years of experience) who is comfortable owning production systems end-to-end, from data model to deploy and monitoring, and who thrives in an environment where pragmatic engineering judgment matters as much as technical depth.

Visa sponsorship is not available for this role.

What You'll Do

  • Design, build, and maintain agentic systems that automate complex, multi-step workflows across domains such as healthcare, legal, fintech, logistics, and compliance.

  • 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: design APIs and data models, implement frontend and backend code, and operate production systems with CI/CD, monitoring, and testing.

  • Collaborate cross-functionally to prioritize work, define success metrics, and iterate based on user feedback and telemetry.

What We're Looking For

Must-haves:

  • 2+ years of software engineering experience with a track record of shipping user-facing or backend products.

  • Practical experience deploying LLMs or LLM-based services in production, including prompt design, orchestration, and tool integration.

  • Full-stack proficiency: Python plus TypeScript/React (or equivalent), 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 designing API-driven, high-throughput systems and real-time product features.

Nice-to-haves:

  • Experience with agent or workflow frameworks such as LangGraph or CrewAI, and orchestration tools such as Temporal or Trigger.

  • Background building multi-tenant or enterprise-ready systems, or experience in regulated industries (healthcare, fintech, legal).

  • Familiarity with fine-tuning, parameter-efficient tuning, or multi-modal model integration.

Compensation & Benefits

  • Salary: $180,000 – $400,000 USD annually (inclusive of equity where applicable)

  • Early-stage equity opportunity

  • High-ownership, high-impact role on a lean, experienced core team

Location

This is an on-site role based in San Francisco, CA. Candidates must be located in or willing to relocate to the San Francisco Bay Area. Visa sponsorship is not available.

About this role

Summary

Design, build, and deploy AI systems involving LLMs, retrieval pipelines, and full-stack development.

Job title

AI Engineer (Mid-Level)

Experience level

2+ years

Minimum experience

2+ years exp

Industry

software

Location requirements

On-site in San Francisco, CA; relocation required

Salary

$180k–$400k

Management role

No

Skills & keywords

Required skills

pythontypescript/reactaws or gcpretrieval-augmented generationapi designmonitoring

Preferred skills

langgraphcrewaimulti-tenant systemsfine-tuningmulti-modal models

Specializations

aillmsretrieval augmented generationfull-stackvector databases
Locations

Structured locations inferred from the posting.

San Francisco, CA, USA

On-site City