Source Job

• Design, build, and operate production AI agents for developer productivity, from code review to incident response.
• Build self-service platform infrastructure enabling teams to prototype, deploy, and scale their own AI developer tools.
• Integrate LLM providers, agent orchestration frameworks, and MCP servers into reliable, loved developer tools.

Docker is a developer tooling company trusted by over 20 million monthly users for building, sharing, and running applications. We are a globally distributed, remote-first team building AI-powered tools that shape how software gets built and delivered.

• Embed with customer engineering teams to design, build, and ship production solutions using Docker products and custom integrations.
• Own the technical journey from discovery and architecture through prototyping, implementation, and production rollout.
• Partner with Solutions Architects, Product, and Engineering to turn field learnings into reusable patterns and influence the roadmap.

Docker makes developer tools for building, sharing, and running applications, including Docker Desktop, Docker Hub, and Docker Scout. The company is a globally distributed, remote-first team trusted by over 20 million monthly users and 20 billion container pulls.

• Build and maintain internal CLIs, SDKs, and services in Python or Go for deploying and debugging AI agents.
• Deploy, scale, and tune LLM inference with vLLM, including GPU scheduling and cost/latency trade-offs.
• Own MLOps workflows, Kubernetes operators, and CI/CD to take AI agents from laptop to production.

Tessera Labs builds multi-agent AI systems that automate complex enterprise workflows across platforms like SAP, Salesforce, and Snowflake. Backed by Foundation Capital, the startup operates with extreme ownership and a fast-moving culture at the frontier of applied AI.

• Architect core vCluster Platform features, diving deep into Kubernetes internals.
• Write high-performance, resilient Go code for the platform and open-source projects.
• Own features end-to-end from design to release, solving hard systems challenges.

We're the #1 platform for AI infrastructure, trusted by the world's fastest-growing AI cloud builders. We're a venture-backed startup of 40+ engineers, remote-first, powering 100K+ GPUs across 50+ AI clouds and Fortune 500 companies.

• Define the technical direction and architecture for a rapidly expanding GPU cluster platform.
• Lead and mentor a team of senior infrastructure engineers while staying hands-on with complex systems.
• Establish security strategies and operational practices to ensure reliable, efficient AI experiments.

This organization powers cutting-edge AI research through large-scale GPU cluster infrastructure. It fosters a collaborative, fast-moving environment where engineers work closely with researchers.

• Build the APIs, controllers, operators and automation that extend Kubernetes
• Improve platform reliability, observability and performance
• Diagnose production issues across the application, Kubernetes, network and compute layers

They are a late-stage AI cloud company backed by NVIDIA that runs AI compute from global data centers and is building a managed Kubernetes platform. The company is valued in the billions, and the culture emphasizes early ownership and end-to-end impact.

• Design, build, and ship new features and services for Chainguard Containers, from design through production.
• Own trade-offs on scope, sequencing, and when to ship, working directly with product managers and customers.
• Collaborate with AI coding agents, maintain system health, and communicate clearly in a remote team.

Chainguard delivers hardened, secure, and production-ready builds of open source software, helping organizations build faster, stay compliant, and eliminate risk. The company serves Fortune 500 enterprises, is venture-backed by leading investors, and fosters a remote-first, flexible culture.

• Design and build platform subsystems for Stacklok Enterprise, from design through production.
• Write production Go code for Kubernetes-native commercial software.
• Work directly with enterprise customers to onboard them and turn feedback into product features.

Stacklok builds open, Kubernetes-native infrastructure for enterprise AI agents, enabling secure and scalable execution. It is a startup led by Kubernetes co-creators, with a culture that values openness, AI integration, and customer collaboration.

• Set technical direction and own architecture for AI-powered developer tools and the self-service platform.
• Design and build production AI agents, LLM integrations, and platform infrastructure for developer productivity.
• Mentor engineers, lead design reviews, and drive cross-team technical delivery across Docker.

Docker provides developer tools for building, sharing, and running applications, trusted by over 20 million monthly users. They are a globally distributed, remote-first team focused on AI-native software development and platform engineering.

• Partner with product, design, and data science to deliver reliable, low-latency technical solutions.
• Own the full software lifecycle from design docs to rollout for major infrastructure initiatives.
• Drive engineering best practices, mentor teammates, and leverage AI-integrated tools for efficiency.

Reddit is a community of communities built on shared interests and trust, hosting open and authentic conversations. With 100,000+ active communities and ~130 million daily active users, it is one of the internet's largest sources of information.

• Architect and deliver major features for Chainguard Containers from concept to production.
• Stay hands-on writing code and lead small sub-teams of engineers.
• Work across teams and with AI agents to build secure container infrastructure.

Chainguard is the trusted source for open source, delivering hardened, secure, and production-ready builds of open source software. It is a venture-backed company with Fortune 500 customers and a remote-first culture.

• Plan, configure, test, and roll out deployments across customer VPC and on-premises environments.
• Partner with customer IT, security, and platform teams to resolve infrastructure issues.
• Build monitoring, telemetry, and automation for scalable processes.

• Design, build, and ship secure container technologies from design through production.
• Develop image pipelines, registry infrastructure, and developer tooling for security and performance.
• Collaborate with product, customers, and engineers while integrating AI-assisted development.

Chainguard develops secure container technologies and open-source tools to help organizations build and deploy software safely. It is a remote-first, fast-growing company with a small autonomous engineering team that values ownership, transparency, and continuous improvement.

• Design and own critical features for Kubernetes data management and backup recovery.
• Enhance internal tools and streamline sprint release processes.
• Collaborate with cross-functional, distributed teams across global time zones.

We specialize in data resilience and security, helping organizations protect their data and AI at scale. With over 550,000 customers and offices in 30+ countries, we foster a culture of trust and innovation.

• Design, develop and maintain backend services and applications using Go.
• Build and improve Kubernetes-based solutions, including controllers, operators and APIs.
• Take ownership of technical components and contribute to architectural decisions.

We help IT teams automate Kubernetes and cloud native operations across multi-cloud, edge, and on-prem. As a top contributor to Kubernetes, we are a technology start-up that values personal growth and ideas over structure.

• Act as the technical bridge between enterprise customers and core engineering, designing APIs, SDKs, and workflows.
• Architect production-ready AI infrastructure for LLM inference, RAG pipelines, and GPU-accelerated workloads.
• Write production-grade Go, Python, and TypeScript while shaping product strategy and mentoring engineers.

The hiring partner builds modern developer platforms and AI infrastructure that help enterprises ship AI-native applications. The team culture emphasizes hands-on technical excellence and collaboration; company size is not disclosed in the posting.

• Troubleshoot and resolve incidents in production Kubernetes clusters on-premises and at scale.
• Deploy, upgrade, and maintain cluster lifecycle, improving the platform through automation and GitOps.
• Work directly with customers to deploy workloads and diagnose problems, then take on-call rotation after onboarding.

Software Mind develops impactful solutions for companies around the globe. They build cross-functional engineering teams in a culture that embraces openness, respect, grit, and enjoyment.

• Collaborate with engineering and customer delivery teams to design and maintain reliable Kubernetes-based infrastructure.
• Perform credential and certificate lifecycle management and develop automation tools to streamline operations.
• Build and maintain observability with Prometheus, Grafana, and other tools to ensure system reliability.

Kubermatic helps IT teams automate Kubernetes and cloud native operations across multi-cloud, edge, and on-prem environments. They are a remote-first company with a small, dynamic team that values community involvement and open-source contributions.

• Define SLIs and SLOs based on signals across Kubernetes, bare-metal, and NVIDIA infrastructure.
• Design and build the API that exposes SLIs and reliability state to Platform Administrators.
• Establish alerting and error-budget practices and partner with infrastructure teams to ensure correct instrumentation.

Mirantis is the Kubernetes-native AI infrastructure company enabling scalable, secure infrastructure for AI and data-intensive applications. It is a leader in container management with a distributed team committed to openness and technical excellence.

• Design and build scalable cloud infrastructure spanning Kubernetes, distributed systems, and CI/CD pipelines.
• Develop and deploy AI agents for infrastructure management with safeguards, observability, and reliability.
• Provide staff-level technical leadership, mentoring engineers and driving architectural decisions.

The company builds enterprise AI applications and infrastructure, with a focus on AI-native engineering practices. It operates as a remote-first, globally distributed team spanning more than 15 countries, valuing technical excellence, inclusion, and continuous improvement.