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 Closure’s 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 Closure 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 Closure 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.

Must-Have Requirements

  • 3+ years of professional software engineering experience working across the stack (backend + frontend) and shipping production features in a modern web stack (e.g., Python, TypeScript/React, or similar).
  • Comfort working directly with customers or end users – you’ve been in roles like solutions engineer, forward-deployed engineer, founder/early engineer, or similar where you regularly met with users and incorporated their feedback.
  • Willingness to travel 25–75% of the time to visit law-enforcement agencies and work with investigators on-site as needed.
  • High ownership and startup mindset – experience in small, fast-paced teams where you’ve worn multiple hats, worked with ambiguity, and owned projects end-to-end.
  • Strong communication skills – able to translate between technical details and non-technical stakeholders (detectives, prosecutors, agency leadership).

Screening Questions

1. (Optional Video). This step is completely optional. If you’d like, record a short 2–3 minute video introducing yourself and your experience — or share a recording of your interview with the recruiter if that’s easier. You can upload the link via Loom or Google Drive. This just helps us get to know you better, but there’s no pressure if you’d prefer to skip it.
2. (Optional Portfolio / GitHub) If available, please share a link to your GitHub, portfolio, or any recent projects you’ve worked on. This is entirely optional but helps provide more context about your work.
3. Are you comfortable building with AI hands-on and working directly with customers to gather feedback, shape features, and help launch new products? Please share an example of when you’ve done this or how you would approach it.

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