Forward Deployed Engineering Manager

This isn’t a professional services hire. It’s the person who builds a new function from zero and sets the standard every deployment after them has to meet. Coder is self-deployed into customer environments. Global 2000 enterprises run it on their own infrastructure, not ours. That means every implementation carries real production weight from day one. Forward Deployed Engineering exists to prove Coder works at that weight, in the account, then turn what worked into something the rest of the company can reuse.

The mission is pattern-first, not project-first. A deployment isn’t done when it’s live. It’s done when it’s been codified into a reusable asset, including a code kit, a playbook, and known failure modes, that makes the next deployment faster, cheaper, and more predictable. The first deployment might take 90 days. The fifth should take 30. That compression is the job.

Forward Deployed Engineering starts in post-sales and works back into pre-sales. Your engagements take place at production-grade scale, where customers are building AI-native development workflows on Coder’s infrastructure. What you build there becomes the proof that pre-sales references are more than theories. CSMs inherit a pattern instead of a bespoke one-off.

Success will be measured by pattern reuse rate across accounts, revenue influenced per FDE headcount, and FDE-to-field handoff rate. We are not looking for an everything-is-custom orientation. If your instinct on a hard problem is always to build a bespoke solution rather than ask whether this maps to, or should become, a reusable pattern, this isn’t the right seat. We’re hiring a pattern builder, not a services engineer.

What you’ll do here

• The pattern system. Four engagement types: Win, Onboard, Health/Get-Well, and Long-Term Partnership. One governing principle across all four: investment equals TAM. High-TAM accounts get deep, human-led FDE engagement. Lower-TAM accounts get served through the pattern and intelligence layer instead.

• The build. Discovery, technical scoping, solution design, hands-on implementation, and early production rollout on lighthouse accounts. You write the workflows, integrations, and glue code yourself when that’s what removes the blocker.

• The exit. Every engagement is time-boxed with defined exit criteria from day one. You decide the handoff path before the build starts, not after the pilot ends. This is not a permanent delivery function.

• The IC search. You are the founding hire for this function. You shape who comes in behind you, set the architectural standards, and own the pattern system going forward. Without this seat filled, FDE drifts back into services. That’s the risk this role exists to prevent.

• The judgment calls. Deciding when a use case is genuinely ready for production versus when the economics, data readiness, or sponsorship don’t support continued investment. Saying no to the wrong engagement is as much the job as saying yes to the right one.

• Three non-negotiables:

  • Cloud implementation depth. Real production infrastructure work, not adjacent exposure to it.

  • Application development expertise. You’ve built and shipped, not advised on someone else’s build.

  • An AI-first mindset with production agentic systems shipped. Not a demo. Not a POC. Something running in production, with the failure modes to show for it.

What we’re looking for

• You’ve led or helped build technical customer-facing teams such as professional services, forward deployed engineering, solution architecture, or implementation.

• You like operating as both a builder and a leader.

• You can work directly with customers while also designing the systems, patterns, and operating model behind the work.

• You’re comfortable with ambiguity and energized by defining a new category of work rather than inheriting a finished playbook.

• You care about customer outcomes, product feedback loops, and practical organizational change.

• You have enough technical depth to engage credibly with cloud-native platforms, developer workflows, and AI-enabled development practices.

Bonus tacos if you have

• (Tacos? If you need an ice-breaker, ask how we say thanks by giving tacos!)

• Terraform, platform engineering, developer infrastructure, or cloud development environments

• Experience in regulated or large enterprise environments

• A track record of introducing new operating models into post-sales or GTM teams

About Coder

Coder is an AI software development company leading the future of autonomous coding. We empower teams to build software faster, more securely, and at scale through the collaboration of AI coding agents and human developers. Our mission is to make agentic AI a safe, trusted, and integral part of every software development lifecycle.

Our self-hosted AI Development Environment is the foundation for deploying agentic AI in the enterprise. It provides a secure, standardized, and governed workspace to deploy autonomous coding agents alongside human developers, accelerating innovation while maintaining control and compliance. Coder’s isolated, policy-driven environments improve productivity, cut cloud costs, and reduce data risks. Developers transition to AI at their own pace using their own tools. Platform and security teams can govern, audit, and manage a great developer experience at scale.

Interview process

We believe that the interview process should be transparent, consistent, and enjoyable. We value your time and hope to complete the interview process in two to four weeks, if schedules allow. Through your interviews, you will meet a mix of individual contributors, managers, and senior leaders.

AI use during the interview process

As an AI company, Coder embraces the use of AI tools, and we want to be transparent about our expectations as you navigate our interview process.

Not permitted: Using AI assistance during conversational interviews.

Permitted: Using AI tooling for take-home assessments. Please flag where and to what extent it was used in your take-home. Your submission will not be penalized for using AI as long as it is done honestly.

Our use of AI in hiring

We use AI tools to help manage our recruitment process efficiently and fairly. Specifically:

• Ashby helps us review inbound applications by surfacing candidates who best match the role requirements we’ve defined. This tool does not make hiring decisions – it helps our team prioritize which applications to review first.

• Granola takes notes during our interview calls so our team can focus on the conversation with you.

All hiring decisions are made by humans. Our team reviews applications, conducts interviews, and makes final selections. AI tools assist us but never replace human judgment, and these practices are conducted in compliance with applicable data protection, AI governance, and labor laws. Your data is not used to train AI models.

In accordance with New York City Local Law 144, an independent bias audit has been conducted on “Automated Employment Decision Tools”; results are available for Ashby.

If you’re applying for a role at Coder and have questions about how we use AI in our process, or if you’d like to request information about the data we collect, please contact careers@coder.com.

Coder is a proud Equal Opportunity Employer

We are committed to providing equal employment opportunities to qualified applicants and do not discriminate on the basis of race, color, ancestry, religion, sex, pregnancy, gender, gender identity, gender expression, sexual orientation, national origin, age, marital status, genetic information, disability, protected veteran status or any other characteristic protected by federal, state, or local laws.