Location: Strong preference for New York City. Hybrid in the Bay Area is possible due to customer proximity
Salary / Hourly Rate: $85,000 - $150,000 per year
Benefits: U.S.-based role with visa sponsorship available for strong candidates. (NO H1Bs),Equity: 0.20% - 1.00%,Bonuses based on company performance,We contribute 3% to your 401(k), regardless of your own contribution,Unlimited PTO,Paid Short- & Long-term Disability Insurance,Paid Life Insurance,Criminal Justice Ready: Given the sensitivity of our work, we support employees through FBI background checks / CJIS clearance process as needed.
Role Information
Role Overview: N/A
Responsibilities: 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: Machine Learning Expertise
5+ years of experience in ML (PyTorch, TensorFlow).
2+ years of hands-on experience working with LLMs (Hugging Face, OpenAI, Anthropic)., 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., 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., 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., 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., 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.
Minimum 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: (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.,(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.,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.
Company Information
About Company: N/A
Culture: N/A
Additional Information
Interview Process: Initial Call (30 min) – Introductory conversation with a founder to learn more about your background, walk through the role, and assess mutual fit., Technical Deep Dive (60–75 min) – Live discussion with an engineer covering your experience building and shipping products, system-design style questions, and how you’ve handled messy real-world requirements., Practical Exercise / Case Study (60–90 min) – Short take-home or live exercise focused on how you’d approach a forward-deployed problem (e.g., understanding a customer workflow and translating it into product/technical changes)., Final Round (60–90 min) – Conversations with founders and team members to go deeper on collaboration style, working with customers, mission alignment, and any remaining technical topics.
Day to day: Embedding on-site with detectives, analysts, and prosecutors to watch how they investigate cases, understand their workflows, and uncover pain points., Deploying and configuring Closure’s 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: You’ll report directly to Aaron Zelinger (Co-founder) and work closely with the other founders on both product and customer work., 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 Closure, from playbooks for deployments to how feedback flows back into the roadmap.
Growth: Own critical customer deployments and relationships from day one, becoming the go-to technical partner for some of Closure’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.
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.
