Senior Software Engineer, Docker Agents (London)
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.
Join Docker's AI engineering team to build the future of containerized AI agents. Docker containers are the perfect vehicle to host and run AI agents - providing isolation, portability, and reproducibility.
You’ll be working on Docker Agent, our open-source project (https://github.com/docker/docker-agent) and expanding on it to enable developers to build, deploy, and scale intelligent agents using Docker’s container technology.
This is a greenfield opportunity to shape how developers leverage containers for AI agents at massive scale. You'll work alongside a team of seasoned engineers, collaborating with our sister teams working on Ask Gordon and Docker's broader AI platform. This is a unique opportunity to combine cutting-edge AI techniques with container technology to solve real-world developer problems.
Please note: this role is only available to candidates currently located in London (or reasonable commuting distance to London). *We are unable to make exceptions to this location requirement. This role is remote-first, with a flexible hybrid schedule. *
Responsibilities- Build Containerized Agent Systems: Design and implement systems that leverage Docker containers as the ideal runtime for AI agents, ensuring isolation, scalability, and portability
- Expand cagent: Maintain and evolve the open-source cagent project, adding new capabilities for containerized agent deployment and orchestration
- Agent Runtime Development: Build robust infrastructure for packaging, deploying, and managing agents in containers
- RAG Integration: Enhance agent capabilities with Retrieval-Augmented Generation systems to provide contextual knowledge and domain expertise (secondary focus)
- Evaluation & Testing: Design robust evaluation frameworks to measure agent performance, reliability, and containerized deployment effectiveness
- Rapid Prototyping: Iterate quickly on new agent capabilities and deployment patterns, moving from concept to production efficiently
- Open Source Community: Engage with the cagent community, review contributions, and help grow the ecosystem
- Cross-functional Collaboration: Work closely with product managers, designers, and engineers across Docker's AI teams to integrate containerized agent capabilities into Docker's developer experience
- On-Call Rotation: Take part in on-call rotation for your team; respond to incidents, debug production issues, and drive continuous improvement of system reliability
What to expect
First 30 days
- Integrate into our dynamic AI engineering team building containerized agent infrastructure
- Deep dive into Docker Agent's architecture and our containerized agent deployment roadmap
- Contribute your first enhancements to Docker Agent with the help of your team
- Understand our technical stack and begin collaborating with sister AI teams
First 90 days
- Lead significant features or improvements to Docker Agent and our containerized agent platform
- Enhance agent deployment capabilities and container-based orchestration patterns
- Collaborate with the open-source community on Docker Agent development
- Help other new team members onboard
- Regularly interact with internal stakeholders and analyze user feedback
One Year Outlook
- Drive major architectural decisions for our containerized agent platform that will impact millions of Docker users
- Continue to help grow the team and develop efficient agent development processes
- Contribute to evaluation frameworks and performance optimization across our agent systems
- Lead initiatives to expand containerized agent capabilities for enterprise use cases
- Grow your skills in enterprise-grade containerized AI system architecture and deployment
- Shape the future direction of cagent and Docker's agent ecosystem
Perks
- Freedom & flexibility; fit your work around your life
- Designated quarterly Whaleness Days plus end of year Whaleness break
- Home office setup; we want you comfortable while you work
- 16 weeks of paid Parental leave (after 6 months of employment)
- Technology stipend equivalent to $100 USD net/month
- PTO plan that encourages you to take time to do the things you enjoy
- Training stipend for conferences, courses and classes
- Equity; we are a growing start-up and want all employees to have a share in the success of the company
- Docker Swag
- Medical benefits, retirement and holidays vary by country
- Remote-first culture, with offices in Seattle and Paris
Qualifications
- Go Expertise: Strong proficiency in Go is highly desired (if you're not proficient, then we will look for your ability/willingness to ramp up and work in Go - this is Docker's primary language for backend systems)
- AI/ML Knowledge: Practical experience with large language models (LLMs) and agent development
- System Architecture: Proven ability to design scalable, distributed systems
- Container Technology: Deep understanding of Docker, containerization best practices, and container orchestration
- RAG Systems: Experience building Retrieval-Augmented Generation systems (secondary focus)
- Rapid Iteration: Demonstrated ability to prototype quickly and iterate based on feedback
- AI Frameworks: Experience with CrewAI, AGNO, ADK, LangChain/LangGraph or similar AI orchestration frameworks (peferred)
- Python Proficiency: Experience with Python for AI prototyping and tooling (prefered)
- Experience with Kubernetes or container orchestration platforms (preferred)
- Open source contributions and community engagement (preferred)
- Experience with agent evaluation, reliability, and observability techniques (preferred)
