About this role
About the Role
Join a small, early-stage public safety technology team building AI-powered tools for law enforcement. You will design and deploy secure, real-world systems that help investigators search and analyze evidence for serious cases.
What You'll Do
- Build resilient, secure distributed systems for AI-driven evidence search and analysis.
- Deploy large language models, vision models, and other machine learning systems in production.
- Design retrieval-augmented generation pipelines and semantic search for unstructured evidence.
- Architect structured data systems, including query planning and semantic reasoning layers.
- Build or work with agentic systems that reason, plan, and take actions across investigative data.
- Evaluate emerging AI models and infrastructure approaches, and own solutions from discovery through deployment.
What We're Looking For
- At least 6 years of backend engineering experience building distributed systems, with production deployment experience for LLMs, vision models, or other ML systems.
- Proficiency across multiple programming languages, including Python, and experience with JavaScript or React.
- Experience building secure, resilient systems and working across multiple infrastructure providers.
- Hands-on experience with RAG or similar pipelines for unstructured data, and structured data systems involving query planning, semantic modeling, or reasoning.
- Experience in both established engineering environments and early-stage startups is valued.
- Agentic AI experience is a plus. Applicants must be authorized to work in the United States; visa sponsorship is not available.
Compensation & Benefits
Base salary: $150,000 to $215,000 annually. Equity details were not provided.
Location
Hybrid role based in San Francisco, California.