Senior Forward Deployed Engineer (North America)

We are looking for a Senior Forward Deployed Engineer to join the Customer Solutions team. You will be the technical authority embedded with our most complex customers, guiding them through deployment, architecture, onboarding, and the adoption of agentic development workflows. You bring deep hands-on experience from prior roles and use that depth to advise, design repeatable patterns, and drive customer outcomes end to end. You operate autonomously, own the technical success of your customers, and bring their experience back to shape how Coder builds and delivers. This is not an execution-only role. You are equally comfortable doing deep technical work with a customer and stepping back to design the repeatable pattern behind it. You are energized by ambiguity, motivated by customer outcomes, and capable of influencing organizational change alongside the technical work. What You'll Do Serve as the primary technical authority for post-sales customers, guiding deployment architecture, environment design, and adoption of Coder across both human and AI development workflows Own onboarding engagements end to end, ensuring customers move from contract to productive adoption with speed and confidence Lead Get Well engagements where architecture decisions, rollout patterns, or organizational dynamics are limiting customer health or growth Help customers implement the technical and organizational changes required to adopt agentic development practices at scale Design and document repeatable delivery patterns across onboarding, architecture, and adoption that can scale across customer segments Design and recommend reference architectures tailored to each customer's cloud environment, security posture, and organizational constraints Translate customer environment complexity into clear guidance on networking, ingress, identity, and infrastructure patterns Anticipate technical and operational risks, escalate to the right internal stakeholders, and track issues through to resolution Contribute to technical documentation, architecture guides, how-to resources, and statements of work that extend your impact across the customer base Capture structured product feedback from customer deployments and advocate directly with engineering and product teams for roadmap and usability improvements What We're Looking For 5 or more years of experience in a Forward Deployed Engineering, Solutions Architect, Platform Engineering, or equivalent post-sales technical role, with a demonstrated track record of guiding enterprise customers through complex technical deployments Proven hands-on experience from a prior role designing and deploying cloud infrastructure on at least one major provider: AWS, Google Cloud, or Microsoft Azure; you have done the work and can speak to it with specificity 2+ years experience deploying or operating AI coding agents in a production or near-production environment: you understand how agent loops execute, where credentials live, and what governance and audit requirements look like in an enterprise context Ability to articulate the architectural difference between workspace-local agent tooling and a centralized agentic harness, and to explain why that distinction matters to a security or compliance stakeholder 2 or more years of production experience with Kubernetes: cluster design, workload scheduling, networking, storage, and operational lifecycle 2 or more years of experience with Terraform or equivalent infrastructure-as-code tooling; you understand how enterprise teams’ structure, version, and maintain IaC at scale Solid understanding of Linux systems administration, including networking fundamentals: ingress controllers, proxies, load balancers, and DNS resolution in cloud-native environments Familiarity with CI/CD pipeline design and DevOps practices; you understand how code moves from commit to running workload in an enterprise context Working knowledge of cloud security and identity: IAM patterns, network segmentation, secrets management, and compliance-relevant controls Understanding of observability practices including logging, metrics, and tracing across distributed systems Demonstrated ability to design repeatable delivery patterns, not just solve one-off problems Comfort working through organizational and workflow change alongside technical change with customers Strong verbal and written communication skills: you can hold a room with a senior infrastructure team and produce a clear architecture document without those being separate skills High customer empathy: you understand that the best technical solution does not always fit a customer's constraints, timeline, or organizational reality Self-directed, analytically minded, and comfortable operating with full autonomy in a startup environment Bonus tacos if you have (Tacos? If you need an ice-breaker, ask how we say thanks by giving tacos!) Experience at both early-stage startups and larger software organizations Background as a Software Engineer, DevOps Engineer, or Platform Engineer before moving into a customer-facing role Familiarity with regulated environments: air-gapped deployments, network isolation, SOC 2, ISO 27001, GDPR, or DORA requirements Experience with disaster recovery design and multi-region availability patterns Cloud cost optimization experience, including rightsizing, reserved capacity, and FinOps practices Experience with Tailscale or similar overlay networking tools Kubernetes certification (CKA, CKAD, or CKS) Open-source contributions Experience with Backstage.io or similar internal developer portals and platform tooling Prior work on or alongside a developer platform or platform engineering team Experience introducing new operating models or delivery patterns across post-sales or go-to-market teams Experience with LLM gateway or proxy infrastructure (LiteLLM, OpenRouter, or equivalent) in a multi-team or enterprise context Familiarity with AI governance frameworks, session audit requirements, or SIEM integration for AI workloads Experience designing human-in-the-loop breakpoints or escalation patterns for autonomous agent workflows 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 View email address on click.appcast.io. 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.