Staff Software Engineer - Developer Experience

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Software Engineer - Developer Experience based in the United States. This is a high-impact technical leadership role focused on transforming the software development lifecycle through AI-native engineering workflows. You will architect intelligent automation, validation guardrails, and closed-loop systems that help AI agents accelerate development while keeping engineers and product managers in control of critical decisions. Working across planning, design, development, testing, deployment, and maintenance, you will help establish scalable practices that improve engineering productivity and software quality. You will champion adoption across teams, mentor developers, and collaborate with platform, research, and security stakeholders to modernize how software is built and maintained. The role offers significant autonomy and the opportunity to shape the future of developer experience in a complex, data-driven engineering environment. Accountabilities: - Lead grassroots adoption of AI-native development workflows, coaching engineers to orchestrate parallel AI agent sessions and subagents. - Collaborate with platform engineering, R&D, and security teams to streamline traditional handoffs and replace manual approval processes with automated, governed workflows. - Design and operationalize Markdown-driven artifact pipelines that provide transparent, auditable records throughout the software development lifecycle. - Architect deterministic build-time and deployment hooks that establish reliable safety boundaries for AI-assisted development. - Integrate AI-powered code review into pull request workflows, using structured policies and CI runners to support multi-pass reviews and automated resolution of review comments. - Build verification frameworks and visual feedback loops that enable AI agents to test, identify defects, iterate, and validate results before human review.

- Develop continuous evaluation suites within CI to assess AI configurations against real engineering tasks and detect regressions when prompts or models change. - Implement production monitoring and automated triage workflows to identify reliability issues, performance degradation, and control breaches, feeding insights back into continuous improvement. Requirements: - Deep conceptual and hands-on expertise in integrating AI into the software development lifecycle, from planning through production maintenance. - Strong programming skills in Python, Java, JavaScript, or similar languages, with a focus on clean, maintainable, production-grade tools. - Extensive practical experience with modern CI/CD orchestration platforms such as GitHub Actions or Jenkins. - Strong knowledge of infrastructure-as-code tools such as Terraform and containerization technologies including Docker and Kubernetes. - Demonstrated ability to use data and engineering metrics, particularly DORA metrics, to improve delivery performance and framework reliability. - High autonomy, initiative, and comfort navigating ambiguity, identifying engineering friction, and developing practical solutions without waiting for assigned tasks. - Excellent technical leadership, communication, collaboration, and mentoring skills across multidisciplinary engineering teams. - Preferred: Experience managing complex software states and isolating or reproducing environments at enterprise scale. - Preferred: Experience building internal applications, wrappers, or developer plugins around large language models (LLMs). - Preferred: Technical leadership or close collaboration across distributed engineering teams in North America and India. - Preferred: Familiarity with service integration and contract testing tools, as well as developer catalog platforms such as Backstage.