Founding AI Engineer

Title: Founding AI Engineer / Member of Technical Staff (YC-backed public-safety startup)

Location: NYC (Preferred) or SF Hybrid

Must-Have Requirements

• 3 years of professional software engineering experience with strong backend fundamentals (distributed systems APIs data modeling) in a modern stack (e.g. Python TypeScript/React or similar).
• Hands-on experience building and shipping ML/AI systems ideally with LLMs or other deep-learning models used by real users (not just research or prototypes).
• Experience with retrieval / RAG or similar pipelines over unstructured text or multi-modal data (documents audio transcripts etc.) including designing data flows and evaluation approaches. (Based directly on the JDs Data Versatility / RAG or similar pipelines section.)
• Comfort working in a fast-moving startup environment with high autonomy ambiguity and end-to-end ownership of projects.
• Strong communication skills able to partner with founders FDEs and investigators explain technical trade-offs and turn messy requirements into robust systems.

Job Description:

• Responsibilities: Owning Core AI and Backend Systems: Design and manage ML systems for ingesting and analyzing large evidence volumes. Data Retrieval Architecture: Create reliable retrieval/RAG pipelines for quick investigator access to structured and unstructured data. Model Prototyping: Experiment with LLMs and other novel tools developing robust production systems for law enforcement. User Collaboration: Implement ML features using feedback from detectives and prosecutors enhancing...

Responsibilities

• This is a founding AI / backend engineering role. Youll design and ship the ML systems that power Closures digital analyst for law enforcement-working closely with the founders Forward-Deployed Engineers and investigators in the field.
• What you will do:
• Own core AI and backend systems that ingest process and search across large volumes of evidence (calls reports documents transcripts and more).
• Design and implement retrieval / RAG pipelines for unstructured and structured data making it fast and reliable for investigators to find what they need.
• Prototype with new models and tools (LLMs embeddings vector databases observability stack) then harden the best ideas into production systems agencies can trust.
• Collaborate closely with Forward-Deployed Engineers and users to turn real-world feedback from detectives and prosecutors into concrete ML features and ranking improvements.
• Contribute across the stack when needed (APIs internal tools evaluation dashboards) to keep the overall AI surface area robust monitored and maintainable.

Qualifications

• 3 years of professional software engineering experience with strong backend fundamentals (distributed systems APIs data modeling) in a modern stack (e.g. Python TypeScript/React or similar).
• Hands-on experience building and shipping ML/AI systems used by real users ideally involving LLMs or other deep-learning models (not just research or PoCs).
• Experience with retrieval / RAG or similar architectures over unstructured text or multi-modal data (documents transcripts logs) including designing data pipelines and evaluation approaches.
• Comfortable working end-to-end: from understanding investigator workflows and problem framing to designing experiments to deploying and monitoring models in production.
• Strong communication and collaboration skills; able to work directly with founders Forward-Deployed Engineers and non-technical stakeholders in a small fast-moving mission-driven team.

Ideal Candidate Profile

• Field-Driven Engineer Strong full-stack engineer (Python modern frontend) who enjoys leaving the office sitting with users and seeing how software actually gets used in the wild.
• Customer-Obsessed Problem Solver Comfortable building trust with detectives and agency leadership asking good questions and turning messy requirements into clear product and technical decisions.
• High-Ownership Operator Thrives in tiny fast-moving teams takes full responsibility for deployments and outcomes and is happy to do whatever the situation requires (from debugging to running training sessions).
• Mission-Motivated Energized by improving public safety and the criminal-justice system and comfortable working with sensitive sometimes difficult case material.
• Startup-Ready Has prior experience in early-stage or talent-dense environments and is excited by ambiguity rapid iteration and having a big say in how the product and company evolve.