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# Forward Deployed Engineer

- **Company:** WITH COVERAGE INC.
- **Location:** New York, NY, United States
- **Experience:** Experienced
- **Salary:** $140,000.0 - $170,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Software Debugging, Systems Integration, Application Enhancement Tool, Large Language Models, Prompt Engineering, Software Coding, Automation Anywhere
- **Published:** October 8, 2026
- **Apply:** https://startup.jobs/forward-deployed-engineer-growth-withcoverage-10221852

## About the Role

* 4+ years of technical experience, ideally including time in an AI or analytics practice at a consulting firm (QuantumBlack, BCG X, Bain Vector, Accenture, or similar) or in a forward-deployed / solutions engineering role
 * You've built AI-powered things that real people used. Prompt engineering, retrieval, agents, evals. It doesn't need to have been at a massive scale, but it needs to have been real.
 * You can explain how an LLM works to someone who has never written code, and they leave feeling capable rather than lectured to. This is the single most important qualification.
 * Genuinely strong client instincts. You can read a room, handle a skeptical executive, tell someone their idea won't work without losing them, and know when to stop talking.
 * You want to be on calls and in rooms. This is a people-facing job that happens to require an engineer, and roughly half your week looks like that.

## Description

We're looking for a customer-facing engineer to build AI-powered tools and workflows on WithCoverage's Growth team and help prospective customers put AI to work in their businesses.

You'll partner closely with Product, which will define and scope much of the work, and own the engineering execution: writing code, connecting systems, testing behavior, and getting working tools into people's hands. You should be comfortable taking a defined problem and independently making the technical decisions needed to build a practical, reliable solution.

You'll also be a technical resource our Growth and Sales teams can bring directly into prospect conversations. As an AI-native insurance brokerage, we can offer operators something valuable: access to an engineer who can answer their questions, demonstrate useful approaches, and help them apply AI to their own workflows.

Hands-on building and prospect conversations are both substantial parts of the job. We're looking for someone who enjoys writing software and can bring that same confidence and clarity to a room of nontechnical operators.

What You'll Do

 * Own engineering execution. Partner with Product on defined projects and take responsibility for implementation. Build AI-powered tools, applications, scripts, and integrations; make technical decisions; and own debugging, testing, deployment, and iteration.
 * Build AI workflows that work in practice. Connect LLMs, APIs, and business data to solve concrete workflow problems. Evaluate outputs against real examples, handle errors and edge cases, and improve reliability as people use what you build.
 * Help Sales secure the next call. Join prospect conversations and email threads to answer technical questions, work through specific problems, and demonstrate useful applications of AI. Help Sales turn that value into a concrete next step: a working session, a tailored demonstration, or a deeper conversation about WithCoverage.
 * Teach in plain language. Give nontechnical operators practical advice they can apply to their businesses. Walk them through tools, demonstrate approaches using relevant examples, and help them understand how to use AI effectively and check its work.
 * Be the technical expert on the call, and build after it. Understand enough of a prospect's workflow to give sound technical guidance. When follow-up calls for a working example, build a prototype, script, or lightweight tool using relevant sample data and documents.
 * Keep the work useful and maintainable. Document what you build, reuse components where it makes sense, and communicate technical constraints and implementation tradeoffs to Product and Core Engineering.