Principal Software Engineer, AI Tools and Security (US West Coast)

Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout.

We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default.

Docker’s AI Tools & Security team is building the foundation for the next generation of secure, developer-friendly AI infrastructure. Our flagship product, the MCP Gateway, empowers developers to connect, observe, and secure AI agents and tools across the entire lifecycle—from prototype to production. We’re defining how developers safely harness the power of the Model Context Protocol (MCP) in real-world environments.

We’re looking for a Principal Backend Engineer who thrives at the intersection of AI, security, and developer experience. You’ll lead the technical direction of the Gateway and related services, collaborating closely with Product, Design, and Security to deliver elegant frameworks and APIs that developers love to use. This is a high-velocity, high-ownership environment: you’ll ship fast, iterate constantly, and help shape the future of secure agent-based development.

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  Define the technical solution for a new product

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  Help shape the product with peers in Product and Design

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  Mentor other technical team members

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  Be the technical point of contact for the team

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  Take part in on-call rotation for your team; respond to incidents, debug production issues, and drive continuous improvement of system reliability

• 10+ years of backend engineering experience, including extensive work on production-grade, distributed systems at scale.

• Technical leadership across multiple teams or domains, with a proven ability to drive architectural vision, set technical direction, and influence long-term product strategy.

• Exceptional product and platform mindset—you think beyond implementation details to how technology shapes developer and business outcomes.

• Expertise in designing and evolving large-scale, cloud-native systems, with deep knowledge of distributed computing, service-oriented architecture, and performance optimization.

• Demonstrated experience building secure, resilient, and high-throughput backend services, with a strong grasp of reliability engineering principles (SLOs, observability, incident response).

• Fluency in Go (preferred) or another modern systems language (Rust, Java, C++, etc.), with the ability to lead technical design reviews and mentor others in language-specific best practices.

• Strong grasp of software engineering fundamentals—CI/CD, testing strategy, source control, and deployment automation—applied in complex, multi-service environments.

• Proven track record of technical mentorship and cross-functional collaboration, enabling teams to deliver high-impact, high-quality software efficiently.

• Deep experience with major cloud platforms (AWS, Azure, GCP) and infrastructure-as-code tooling.

• Ownership mentality with a bias for action and iterative delivery, balancing short-term impact with long-term architectural health.

• Excellent communication skills, with the ability to clearly articulate complex technical concepts to both technical and non-technical audiences.

• Comfortable operating autonomously in distributed, remote-first teams, and leading through influence rather than authority.

• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

• Experience with Kubernetes, Docker, and microservices architecture

• Prior experience with OpenAI, Anthropic, or similar LLM APIs, and the MCP specification
  

• Meet team members

• Build context about the problem space and prior art

• Provide feedback on current exploration and propose next steps in line with Product and Design

• Work with Product and Design on defining the product

• Attend customer calls

• Meet people across the company

• Help grow the team by participating in hiring loops

• Bring the product to market

We use Covey as part of our hiring and / or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on April 13, 2024.

Please see the independent bias audit report covering our use of Covey here.