Docker, Inc
Software Engineer II (AI Developer Tools)
Join Docker, Inc.
Docker is the #1 tool for building, sharing, and running apps – trusted by startups and Fortune 100s alike.
We are building the future of AI‑powered developer productivity.
In this role, you will work on cutting‑edge AI agents and tools that transform how developers write code, debug issues, deploy applications, and respond to incidents both internally and for our customers worldwide.
Base Pay Range $128,000–$181,500 per year.
Responsibilities
Build AI developer tool features such as code review assistants, test generators, deployment diagnostics, and on‑call assistance tools.
Implement LLM integrations (OpenAI, Anthropic, etc.) with prompt engineering, response handling, error management, and performance optimization.
Contribute to the self‑service platform (deployment pipelines, observability, security controls, operational tooling).
Support AI‑native development adoption across Docker’s engineering organization.
Write well‑tested, high‑quality code and participate in code reviews.
Maintain production AI systems – monitoring, alerting, troubleshooting, incident response.
Collaborate closely with senior engineers on technical designs and continuously improve your skills.
Create clear technical documentation for features you build.
Engage in design discussions, sprint planning, retrospectives, and team activities.
Continuously learn about AI/ML technologies, developer tooling best practices, and platform engineering.
Qualifications – Required
2+ years building backend systems, APIs, or developer‑facing tools with strong software engineering fundamentals.
Proficiency in Go (preferred), Rust, Java, or Python; understanding of data structures, algorithms, and design patterns.
Basic understanding of AI/ML concepts with eagerness to learn LLM APIs, prompt engineering, and AI agent development.
Experience with cloud platforms (AWS, GCP, or Azure) and distributed systems or microservices.
Familiarity with CI/CD pipelines, automated testing, version control (Git), and modern development workflows.
Strong problem‑solving skills and ability to work through technical challenges with guidance from senior engineers.
Good communication skills in remote, asynchronous environments and ability to document technical decisions.
Collaborative mindset with eagerness to learn from code reviews and feedback.
Self‑motivated with ability to work autonomously while knowing when to ask for help.
Passion for developer tools and user experience.
Preferred
Internship or project experience with AI/ML technologies, LLM APIs, or chatbots.
Exposure to AI agent frameworks (LangChain, LangGraph, CrewAI) or similar tools.
Experience with developer productivity tools, DevOps practices, or platform engineering.
Contributions to open‑source projects or personal projects involving AI tools.
Familiarity with Kubernetes, Docker, or container technologies.
Knowledge of infrastructure‑as‑code tools (Terraform, Pulumi) or GitOps patterns.
Understanding of observability tools (Prometheus, Grafana) and monitoring best practices.
Computer Science degree or equivalent technical education.
What to Expect – Overview First 30 days: onboarding, meet the team, learn Docker’s tooling landscape, get up to speed on the AI Developer Tools vision, and begin small code contributions.
First 90 days: own and deliver your first meaningful feature, contribute regularly, participate in code reviews, establish monitoring and collaboration with product teams.
One‑year outlook: own significant features, ship multiple AI agent features or platform improvements, develop deep proficiency in AI/LLM integration patterns, mentor newer team members, and demonstrate growth toward Senior Engineer.
Perks
Freedom & flexibility, fit your work around your life.
Designated quarterly Whaleness Days and end‑of‑year Whaleness break.
Home office setup support.
16 weeks of paid parental leave.
Technology stipend equivalent to $100 net/month.
PTO plan encouraging time off to do what you enjoy.
Training stipend for conferences, courses, and classes.
Equity in a growing startup.
Docker swag.
Medical benefits, retirement and holidays vary by country.
Equal Opportunity Statement Docker embraces diversity and equal opportunity.
We are committed to building a team that represents a variety of backgrounds, perspectives, and skills.
The more inclusive we are, the better our company will be.
Due to the remote nature of this role, we are unable to provide visa sponsorship.
#J-18808-Ljbffr
Docker is the #1 tool for building, sharing, and running apps – trusted by startups and Fortune 100s alike.
We are building the future of AI‑powered developer productivity.
In this role, you will work on cutting‑edge AI agents and tools that transform how developers write code, debug issues, deploy applications, and respond to incidents both internally and for our customers worldwide.
Base Pay Range $128,000–$181,500 per year.
Responsibilities
Build AI developer tool features such as code review assistants, test generators, deployment diagnostics, and on‑call assistance tools.
Implement LLM integrations (OpenAI, Anthropic, etc.) with prompt engineering, response handling, error management, and performance optimization.
Contribute to the self‑service platform (deployment pipelines, observability, security controls, operational tooling).
Support AI‑native development adoption across Docker’s engineering organization.
Write well‑tested, high‑quality code and participate in code reviews.
Maintain production AI systems – monitoring, alerting, troubleshooting, incident response.
Collaborate closely with senior engineers on technical designs and continuously improve your skills.
Create clear technical documentation for features you build.
Engage in design discussions, sprint planning, retrospectives, and team activities.
Continuously learn about AI/ML technologies, developer tooling best practices, and platform engineering.
Qualifications – Required
2+ years building backend systems, APIs, or developer‑facing tools with strong software engineering fundamentals.
Proficiency in Go (preferred), Rust, Java, or Python; understanding of data structures, algorithms, and design patterns.
Basic understanding of AI/ML concepts with eagerness to learn LLM APIs, prompt engineering, and AI agent development.
Experience with cloud platforms (AWS, GCP, or Azure) and distributed systems or microservices.
Familiarity with CI/CD pipelines, automated testing, version control (Git), and modern development workflows.
Strong problem‑solving skills and ability to work through technical challenges with guidance from senior engineers.
Good communication skills in remote, asynchronous environments and ability to document technical decisions.
Collaborative mindset with eagerness to learn from code reviews and feedback.
Self‑motivated with ability to work autonomously while knowing when to ask for help.
Passion for developer tools and user experience.
Preferred
Internship or project experience with AI/ML technologies, LLM APIs, or chatbots.
Exposure to AI agent frameworks (LangChain, LangGraph, CrewAI) or similar tools.
Experience with developer productivity tools, DevOps practices, or platform engineering.
Contributions to open‑source projects or personal projects involving AI tools.
Familiarity with Kubernetes, Docker, or container technologies.
Knowledge of infrastructure‑as‑code tools (Terraform, Pulumi) or GitOps patterns.
Understanding of observability tools (Prometheus, Grafana) and monitoring best practices.
Computer Science degree or equivalent technical education.
What to Expect – Overview First 30 days: onboarding, meet the team, learn Docker’s tooling landscape, get up to speed on the AI Developer Tools vision, and begin small code contributions.
First 90 days: own and deliver your first meaningful feature, contribute regularly, participate in code reviews, establish monitoring and collaboration with product teams.
One‑year outlook: own significant features, ship multiple AI agent features or platform improvements, develop deep proficiency in AI/LLM integration patterns, mentor newer team members, and demonstrate growth toward Senior Engineer.
Perks
Freedom & flexibility, fit your work around your life.
Designated quarterly Whaleness Days and end‑of‑year Whaleness break.
Home office setup support.
16 weeks of paid parental leave.
Technology stipend equivalent to $100 net/month.
PTO plan encouraging time off to do what you enjoy.
Training stipend for conferences, courses, and classes.
Equity in a growing startup.
Docker swag.
Medical benefits, retirement and holidays vary by country.
Equal Opportunity Statement Docker embraces diversity and equal opportunity.
We are committed to building a team that represents a variety of backgrounds, perspectives, and skills.
The more inclusive we are, the better our company will be.
Due to the remote nature of this role, we are unable to provide visa sponsorship.
#J-18808-Ljbffr