Artificial Intelligence Specialist

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Term: Full Time

$: 85-150k _ Equity

Role: Forward Deployment Engineer/Full Stack Developer

Vertical: Start Up

Location: New York City

Job Details

Job Overview

Key Responsibilities: Embed with law enforcement teams, understand their workflows, and deploy and configure software systems to enhance investigation efficiency. Translate field feedback into product features and ship full-stack solutions using Python, React, TypeScript, and AI/ML APIs. Technical

Qualifications: 5 years of ML (PyTorch, TensorFlow) and 2 years with LLMs. Proven track record in deploying production AI systems.

Responsibilities

This is a founding Forward-Deployed Engineer role. You sit at the intersection of product, engineering and field work. You will embed directly with detectives, analysts and prosecutors, learn their workflows in detail, and use that context to deploy the platform and shape the roadmap.

This is a full-time role for an engineer who wants to own real problems end to end, work closely with users, and see their work show up in live investigations.

What you will do:

• Spend significant time on-site with law-enforcement customers to understand how they investigate cases and where evidence review slows them down.
• Deploy and configure the product for new agencies, load and validate data, and make sure investigators can rely on the system in day-to-day work.
• Translate field feedback into concrete product ideas and partner closely with the founders to turn those into features.
• Build and ship full-stack features using Python, React, TypeScript and AI/ML APIs, from new workflows in the UI to backend improvements that make evidence search faster and more reliable.
• Help design and refine processes for pilots, rollouts and training so that new departments can adopt the product smoothly.
• Act as a trusted technical partner for investigators and leadership teams, helping them understand what is possible with the product.

Qualifications

Qualifications

• Machine Learning Expertise
• 5 years of experience in ML (PyTorch, TensorFlow).
• 2 years of hands-on experience working with LLMs (Hugging Face, OpenAI, Anthropic).
• AI System Development
• Proven experience building and deploying production AI systems, including RAG and vector search.
• Knowledge of prompt engineering, AI safety, and content filtering best practices.
• Comfort architecting scalable infrastructure that integrates into complex environments.
• Technical Proficiency
• Familiarity with Rails is a plus, but not required — strong candidates can ramp up quickly.
• Experience working with REST APIs, PostgreSQL, ActiveRecord, and RSpec.
• Understanding of frameworks like LangChain or LlamaIndex, or the ability to learn them rapidly.
• Communication & Collaboration
• Proven ability to engage directly with users, customers, and cross-functional teams to gather feedback and shape technical solutions.
• Comfortable explaining complex concepts clearly to both technical and non-technical stakeholders.
• Experience collaborating with product and design teams to align on goals and iterate quickly.
• Strong written and verbal communication skills.
• Builder Mindset
• Thrives in ambiguity, learns quickly, and iterates fast in lean environments.
• Excited to work in a small, high-impact team where communication and ownership are key.

Ideal Candidate

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.

Mission

The group helps law enforcement, prosecutors, attorneys, and investigators quickly find the truth in overwhelming volumes of digital evidence. Their “digital analyst” platform securely transcribes, translates, searches, organizes, and analyzes case files—such as jail communications, search-warrant returns, and scanned documents—across many languages. By turning evidence overload into clear, searchable insight, the group lets agencies focus on solving cases and delivering accurate, fair justice instead of manually combing through data.

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What you can expect

Day to Day

You’ll spend most of your time in the field with users and turning their needs into product. In practice, that looks like:

• Embedding on-site with detectives, analysts, and prosecutors to watch how they investigate cases, understand their workflows, and uncover pain points.
• Deploying and configuring the platform for new departments, loading data, troubleshooting issues, and making sure investigators can rely on the system in day-to-day work.
• Translating what you see in the field into clear product ideas and engineering tasks, then building and shipping full-stack features using Python, React, TypeScript, and AI/ML APIs.
• Owning pilots end-to-end: planning deployment, running training sessions, gathering feedback, and iterating quickly with the founding team.
• Traveling regularly (25–75% of your time) to customer sites across the U.S. while staying tightly looped in with the core team in New York.

Team

• The team is lean, highly technical, and mission-driven — everyone ships code, talks to users, and contributes to product direction.
• As one of the first Forward-Deployed Engineers, you’ll shape how the FDE function works at the firm from playbooks for deployments to how feedback flows back into the roadmap.

Growth

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

• Own critical customer deployments and relationships from day one, becoming the go-to technical partner for some of the firm’s key law-enforcement agencies.
• Directly influence product direction by bringing field context to every roadmap discussion and helping decide what gets built next.
• Help define and later scale the Forward-Deployed Engineering function — including processes, tooling, and eventually mentoring or leading additional FDEs as the team grows.
• Build a rare track record of high-impact, user-embedded engineering work at a YC-backed, seed-stage startup tackling complex, real-world problems.