Lead AI Engineer

Lead AI Engineer 

The details 

• Location: Sweet James Headquarters (Newport Beach, CA), on-site 

• Team: Technology 

• Reports to: Chief Technology Officer 

• Compensation: $200,000 to $250,000 base salary, depending on experience 

The role 

Technology is how we practice law, not a department beside it. We have built a highly automated, AI-forward experience for every client-facing role, from intake to settlement, and it is one of the leading examples of applied AI in the legal field: Our case teams run at a fraction of the headcount our largest peers need for the same work. The systems behind that result are built in-house, and you will be one of the people building them. 

Sweet James is seeking a Lead AI Engineer to own the direction, standards, and health of the AI platform and to lead the engineers who build it. This is a player-coach seat for a staff-level engineer ready to manage: You will set the architecture, turn the roadmap into a build plan the team can execute, and remain hands-on in the code. 

You will report to the Chief Technology Officer and own how the platform is built and run. The distinction from our Senior AI Engineer seat is scope: Senior engineers own features end to end; you own the system they fit into and the people who build it. 

Responsibilities 

• Direction: Own the architecture of the AI platform (e.g., document intake and filing, fact extraction, case search, the internal assistant and its agents, voice agents) and review every major design before it is built. The roadmap is set by the Chief Technology Officer and product leadership; you decide how it gets built. 

• Standards: Define how the team ships, including code review, testing, and the evaluation sets every AI feature must clear before release. 

• Platform health: Own uptime, monitoring, incident response, and access controls across the platform, and ensure no system depends on one person. 

• People and capacity: Allocate the team's capacity against the priorities the Chief Technology Officer sets, make the trade-offs when demand exceeds it, and coach, review, and hire the engineers who carry the work. 

• Delivery: Ship production code yourself every week. 

• Business partnership: Decide with attorneys, case managers, and operations leaders which work is worth automating next, and report results in hours returned, error rates, and adoption. 

• Data governance: Set the rules for least-privilege access, audit trails, and which client and medical data may reach which model. 

Qualifications 

Required: 

• Experience: 8+ years building production software, with a track record as the technical lead on systems other engineers depended on. 

• Leadership: Mentoring, design review, and ownership of a team's output; formal people management is welcome but not required. 

• LLM craft: Systems shipped to real users spanning prompt and tool design, retrieval, structured extraction, evaluation, and cost and latency tuning. 

• Stack: Strong Python and TypeScript/Node, production SQL in Postgres, Docker, containerized cloud services (Azure preferred), CI/CD, and monitoring. 

• Operations: Ownership of uptime, including on-call, incident reviews, and rollbacks. 

• Communication: Clear design docs, runbooks, and plain-language explanations for non-engineers. 

Preferred: 

• Models and tooling: Anthropic Claude and OpenAI APIs at production scale; agent frameworks or the Model Context Protocol; vector search (e.g., pgvector); self-hosted or open-weight models (e.g., vLLM, Baseten). 

• Workflow automation: Platforms such as n8n. 

• Salesforce: The data model and APIs; Litify a plus. 

• Voice: Voice AI and telephony (e.g., Retell, Twilio, Zoom). 

• Industry: Legal, insurance, or healthcare.