Coder

Senior Forward Deployed Engineer (North America)

Remote Solutions Architecture role with clear candidate location fit.

PostedJun 12, 2026

Eligible countries3 accepted countries

Seniority signalSenior

Work settingRemote

Accepted candidate locations

CanadaMexicoUSA

AWS Azure CI/CD Kubernetes

Role overview

Senior Forward Deployed Engineer (North America)

Requirements and responsibilities

Readable role content extracted into sections for faster review.

Details

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
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
(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

Our use of AI in hiring

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