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Senior Member of Technical Staff
San Francisco · Hybrid · FullTime · Engineering
$150K – $215K
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About the role
Distributed SystemsMachine LearningLLMsRAGPythonReact
ABOUT THE ROLE
Join a small, early-stage team building AI-powered software for law enforcement and other public-sector investigative workflows. In this high-autonomy role, you will design and deploy secure systems that help teams search and analyze complex evidence.
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 settings.
- Design retrieval-augmented generation pipelines and semantic search infrastructure for unstructured data.
- Architect structured data systems, including query planning and semantic reasoning layers.
- Develop or work with agentic systems that reason, plan, and take actions across investigative data.
- Evaluate emerging AI models and infrastructure approaches, and drive solutions from idea through deployment.
WHAT WE'RE LOOKING FOR
- At least 6 years of backend engineering experience building distributed systems, including experience in senior, staff, founding, or technical leadership roles.
- Production experience deploying LLMs, vision models, or other machine learning systems.
- Strong skills across multiple programming languages, including Python, and experience with React and multiple infrastructure providers.
- Hands-on experience building RAG or similar pipelines for unstructured data, and systems for structured data such as query planning or semantic modeling.
- Experience building secure, resilient systems and working in both established technology environments and early-stage startups.
- Comfort with ambiguity, fast iteration, and taking ownership. Experience with agentic AI systems is a plus.
- Authorization to work in the United States is required. Visa sponsorship is not available.
COMPENSATION & BENEFITS
Base salary: $150,000 to $215,000 annually. Equity is not specified.
LOCATION
Hybrid role based in San Francisco, California, United States.