Job description

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.

Requirements

Must-haves

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.
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.

Nice-to-haves

Agentic AI experience is a plus. Applicants must be authorized to work in the United States; visa sponsorship is not available.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningmlpythonjavascriptreact

Platform: ashby
Effort: quick

Benefits

Benefits detected in the listing.

Vision