Principal Forward Deployed Engineer

Docker•San Jose, CA

1d•$198,000 - $319,000•Remote

About The Position

Docker Forward Deployed Engineers (FDE) embed directly with our most strategic customers to solve important, complex technical problems and turn ambitious ideas into production outcomes. FDEs take on the most challenging technical challenges using existing Docker products and patterns when possible, and work across customer, Docker Product and Engineering teams to realize new approaches when required. As a Docker FDE, you will work side-by-side with customer engineering teams to deeply understand their goals, problems, constraints, and technical landscape; identify the highest-leverage opportunities; and design, build, and ship solutions with them. You own the technical journey from discovery and architecture through prototyping, implementation and production rollout. The solutions you build may use existing Docker products, extend Docker into new environments, integrate deeply with customer and third-party systems, or reveal capabilities that Docker should build next. You work closely with Docker Solutions Architects to evolve existing patterns, and Docker Product and Engineering to turn new learnings into reusable patterns and product capabilities.

Requirements

10+ years of software engineering experience, including 4+ years in a customer-facing technical role such as Forward Deployed Engineer, Solutions Engineer, Professional Services Engineer, or Software Engineer with consulting or technical founder experience.
Technical leadership across multiple engagements, teams, or domains, with a proven ability to set delivery standards, define repeatable patterns, and influence product direction through field evidence.
Expert production coding skills in Go, Python, or TypeScript, with a track record of shipping and operating software that other people depend on and of leading technical design reviews.
Deep, hands-on Docker expertise: Dockerfiles and multi-stage builds, Docker Compose, image and registry operations, container networking and storage, and container security fundamentals.
Hands-on experience building with LLMs and agents in production, including tool use and function calling, the Model Context Protocol (MCP server and client implementation), prompt and context engineering, and evaluation of agent behavior.
Working knowledge of software supply chain security: SBOMs, image signing and attestation, vulnerability management, minimal and hardened base images, and secure CI/CD.
Experience integrating with enterprise systems: identity providers (Okta, Entra ID, LDAP/Active Directory), federated identity protocols (OIDC, SAML), secrets managers, Kubernetes, and at least one major cloud platform (AWS, Azure, GCP).
Ability to scope and deliver complex work in ambiguous, fast-moving customer environments, making sound trade-offs between scope, speed, and quality.
Excellent communication skills with engineers, security and platform teams, and executive stakeholders, with a low-ego, collaborative approach and the ability to lead through influence rather than authority.
Proven track record of technical mentorship and of raising the bar for the engineers around you.
High agency and comfort operating autonomously in distributed, remote-first teams.
Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
Travel to customer sites to build in person with customer teams, estimated at up to 50%.

Nice To Haves

Experience with Docker Hardened Images, Docker Scout, MCP Gateway, MCP Toolkit, Docker Sandboxes, or Docker Model Runner.
Experience deploying and operating coding agents (Claude Code, Codex, Gemini CLI, Cursor, or similar) in team or enterprise settings.
Experience with air-gapped, regulated, or compliance-driven environments in financial services, healthcare, government, or similar sectors.
Contributions to open source projects in the container, Kubernetes, or MCP ecosystems.
Prior experience founding or scaling a Forward Deployed Engineering or Professional Services practice.

Responsibilities

Build in Production with Customers: Embed with customer engineering teams to design, build, and ship solutions from first prototype through stable production rollout. Use existing Docker products and patterns when possible, invent, prototype and validate innovative solutions when necessary.
Deliver working technical artifacts to customers: custom MCP servers with tightly integrated Docker Sandbox environments for coding agents and containerized agents; Docker Compose definitions for multi-agent harnesses and model-backed applications; Hardened Image standardization and migration; New tools that unblock customer progress.
Integrate Docker's AI platform with the customer's existing stack, including identity providers (OIDC/SAML/SSO), secrets management, private and air-gapped registries, Kubernetes, CI/CD pipelines, and observability tooling.
Own technical delivery on your engagements: scope the work, sequence it, make trade-offs between speed and quality, remove blockers early, and contribute directly to code whenever progress depends on it.
Make AI Adoption Safe and Governable: Translate customer security, compliance, and platform requirements into concrete plans and see those plans through from ideation to production.
Help customers define controls to enable them to adopt agentic AI to solve their unique business problems without compromising security, compliance, data sovereignty or end-user experience.
Establish quality and performance standards for customers and work closely with Docker Product and Engineering to quickly address issues that fall outside of established thresholds
Partner with customer security and platform teams to get agentic workloads through architecture review, threat modeling, and change control.
Partner with Solutions Architecture and the Field: Work closely with Solutions Architects to enable off-the-self solutions when possible and provide technical experience and leadership when a bespoke solution is necessary.
Feed implementation learnings back into reference architectures, SOW templates, and success patterns so that FDE innovations become standard features and implementation patterns.
Support the field with technical depth during proofs of concept, escalations, and expansion conversations when a working build is the fastest path to a customer adoption.
Close the Loop with Product and Engineering: As part of Docker Engineering FDEs work closely with Product and Engineering teams to fold FDE innovations, learnings, and design patterns into existing or new products and services.
Work with Customers, Product and Engineering to establish quality and performance thresholds, ensuring customer environments meet them consistently, and responding quickly and decisively when they don’t.
Be the voice of the customer. Deliver data-driven and actionable feedback to Product and Engineering: what works well; what does not; what customers are asking for; and what blocks their adoption and forward progress. FDE experience directly influences the roadmap.
Shape the Practice: Define the FDE engagement model, delivery standards, and quality bar, and codify them so that engagements are consistent across customers, regions, and delivery partners.
Mentor and lead other Forward Deployed Engineers, and participate in hiring loops to grow the team.
Act as the senior technical escalation point on the hardest problems impacting your customers. Every incident is an opportunity to improve Docker products and services.
Maintain deep, current knowledge of the agentic AI stack: LLMs, APIs, MCP, coding agents, model and harness evaluation approaches, performance and quality thresholds, deployment patterns.
This role may require participation in an on-call rotation to provide support outside of standard business hours, including evenings, weekends, and holidays, as needed.

Benefits

Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration.
Flexibility that fits your life – We trust you to manage your schedule while delivering great work.
Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break.
Home office support – Set up your workspace for comfort and success.
Technology stipend – Equivalent to US$100 net per month to help support your work.
Learning & development – Annual stipend for conferences, courses, certifications, and continued learning.
Parental leave – 16 weeks of paid parental leave after six months of employment.
Equity for all full-time employees – Share in Docker's long-term success as we continue to grow.
Comprehensive benefits – Medical, retirement, and paid holidays vary by country.
Docker swag – Because representing the whale never gets old.