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Today

Forward-Deployed AI Engineer, Backend

Draftwise New York, NY

New York, NY

Today

$135k - $175k/yr Full time Backend Developer Artificial Intelligence Database

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Job Description

Draftwise is seeking an early-career Forward Deployed AI Engineer to embed with a law firm and translate how lawyers draft into an ontology, then build the backend (and enough frontend) to extend the product so it operates the way the firm works. This role blends backend engineering with production AI systems, applied directly in real customer environments.

Location and Compensation

Location: New York, NY (onsite)
Salary: USD 135,000 - 175,000 per year

What You Will Do

Model a firm’s precedent and playbooks into an ontology, and implement the backend that sits behind it; when platform capabilities fall short for a firm’s needs, build the missing parts.
Embed with the firm to learn how lawyers draft, then extend the product until it aligns with their workflows.
Own features end to end, including understanding how the pieces work together.
Write and test prompts, build retrieval and evaluation scaffolding, and measure quality using real customer data.
Perform profiling, query tuning, and cost-related work as part of routine engineering for scale and performance.
Lead early pieces of a firm’s rollout and investigate why a playbook does not map cleanly onto the product.
Ship UI changes without waiting on others.

Core Responsibilities in Practice

You will apply production engineering to LLM-driven systems, including drafting, review, and search workflows. The work includes ontology modeling for legal knowledge, backend services behind product features, and engineering improvements that support scale, performance, and deployments into elite law firms, alongside a senior Forward Deployed Engineer.

Required Qualifications

Backend as your center of gravity, with comfort in SQL, API design, and debugging services you did not write.
Comfort working closely with the customer by asking precise questions and clearly stating what information is still needed.
The instinct to turn an ambiguous problem into a model.
Interest in LLMs and their limits.
High ownership and low ego.

Technologies

Postgres
OpenSearch
Graph database
AWS
TypeScript
React
Microsoft Word
Claude Code

Benefits

Meaningful equity package for every engineer, so you own a part of what you build.
Joining at Series A, with work that continues to shape the company’s trajectory.

Nice to Have

Project or internship experience involving retrieval systems, evaluation harnesses, or agent frameworks.
Experience working with customers, including consulting, support, or solutions work.
Exposure to legal, financial, or other document-heavy domains.
Anything shipped to real users, including personal projects.

Interview Process

Intro call with the hiring manager.
Technical conversation on a system you have built.
Screen share coding exercises of about an hour on backend, data modeling, and debugging.
Take-home project of about 3 hours on a self-contained problem using the company stack and AI tools you would use on the job; the rate and evaluation criteria are shared in advance.
Final conversation with a founder.

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