Senior Software Engineer - Developer Tools & AI

CloudBees is seeking a Senior Software Engineer for its Developer Tools & AI team in Chennai, India (Hybrid). The team builds the software, tools and automation that CloudBees engineers use to develop and deliver software, including developer tooling, shared engineering services and the AI Software Factory. This is fundamentally a software engineering role focused on designing and building production software, developer tools, APIs, integrations and automation. Senior engineers are expected to have an established AI development practice that goes materially beyond prompt completion, code generation and small-scale edits. No machine learning background is required.

Responsibilities

Design, build and operate production software that improves how engineers develop, test, integrate and deliver software; Build developer-facing tools, services, APIs, CLIs and integrations with a focus on usability, sensible defaults and useful feedback; Automate repetitive or error-prone engineering work by building maintainable systems; Integrate with systems across the engineering lifecycle, including source control, CI/CD, identity, issue tracking, build systems, deployment systems and AI agents; Own the software shipped from design through production, including testing, security, observability, reliability and ongoing improvement; Use modern AI coding agents as a normal part of professional software development; Decompose substantial engineering work into problems that humans and AI agents can execute effectively; Use higher-order AI automation such as agentic workflows and automated validation; Review plans, designs and code produced by AI with the same engineering judgement applied to human contributions; Improve feedback loops, tools, context and guardrails that make AI-assisted development more reliable; Evaluate new models, tools and techniques based on demonstrated engineering outcomes; Turn ambiguous engineering problems into coherent technical designs and executable increments; Design robust integrations between independently evolving systems; Participate in architecture reviews and make pragmatic build, buy and integrate decisions; Treat other engineers as users and improve their developer experience; Mentor other engineers and contribute to shared engineering patterns, practices and tooling; Identify and remove unnecessary complexity and manual work in the software delivery lifecycle

Requirements

Senior software engineering capability: designed, built, shipped and maintained substantial production software; Strong programming experience in at least one modern structured programming language such as Go, Python or Java (Python used primarily for scripting, glue code or infrastructure automation does not meet this requirement); Strong system design fundamentals: reasoning about architecture, APIs, state, data, concurrency, failure modes, security, performance and operational characteristics; Demonstrated higher-order AI development practice beyond prompt completion and small-scale edits, including decomposing and executing complex work, coordinating or automating development workflows, validating results and improving reliability of AI-assisted engineering; Engineering judgement around AI: constraining work, reviewing plans and implementations, detecting drift and subtle errors, and remaining accountable for outcomes; Developer-oriented product thinking: caring about APIs, CLIs, workflows, documentation, defaults, error messages and the engineer experience; Automation mindset; Production ownership: building software that can be tested, secured, observed, diagnosed and operated

Nice to have

Experience building developer tools, internal developer platforms or shared engineering services; Experience building agentic systems, AI-powered developer tooling or automated software development workflows; Experience with CI/CD systems, source-control integrations, workflow engines or build tooling; Experience designing APIs and integrations across multiple independently evolving systems; Experience with cloud platforms, containers and Kubernetes sufficient to develop and operate your own software; Familiarity with modern AI application concepts such as tool use, context management, evaluation, structured outputs, permissions and agent orchestration; Experience with technologies such as MCP, Tekton, Jenkins, GitHub, GitLab, Argo, LangGraph or similar systems