Artificial Intelligence Engineer

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Term: Full Time

$: 130-200k _ Equity

Role: AI/Back End Engineer-Founding Level

Vertical: Start Up

Location: New York City

Job Details

Job Overview

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. You’ll design and ship the ML systems that power the 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.

About the Company

What you can expect

Day to Day

You’ll spend your days designing, building, and operating the AI and backend systems that powers “digital analyst” for law enforcement.

In practice, that looks like:

• Owning core data and ML pipelines that ingest, process, and search across large volumes of evidence (calls, reports, transcripts, documents, etc.).

• Designing and implementing retrieval / RAG architectures over unstructured and structured data so investigators can reliably find what matters.

• Prototyping with new models and tools (LLMs, embeddings, vector databases, observability) and turning the best ideas into robust, production-ready systems.

• Partnering closely with Forward-Deployed Engineers and founders to turn field feedback from detectives and prosecutors into concrete ML features and ranking improvements.

• Contributing across the stack when needed — from APIs and job orchestration to evaluation dashboards and monitoring — to keep the entire AI surface area healthy.

Team

You’ll join a tiny, senior founding team who are obsessed with solving meaningful problems in public safety.

• You’ll report directly to the Co-founder & CTO and work closely with another cofounder with architecture, roadmap, and product direction.

• You’ll collaborate tightly with Forward-Deployed Engineers who spend time in the field with investigators and bring back high-signal problems and feedback.

• The team is lean, highly technical, and mission-driven — everyone ships code, talks to users, and has a strong voice in what gets built next.

Growth

This is a founding-level AI role with a lot of surface area:

• Own major pieces of the AI and backend architecture from day one and shape how the digital analyst evolves over time.

• Define best practices for evaluating, monitoring, and hardening LLM / retrieval systems in high-stakes law-enforcement settings.

• Influence product strategy by connecting what’s technically possible with what investigators actually need in the field.

• Help hire and mentor future ML/AI engineers as the company grows, building out a small but world-class applied AI team.

• Build a rare track record of shipping real-world, high-impact AI systems at a YC-backed, public-safety-focused startup.