Senior Software Engineer, AI Developer Experience

Build the systems, infrastructure, and developer workflows that make AI-powered engineering more useful, reliable, and easy for Vanta engineers to adopt.

The AI DX team is building the foundations for a more autonomous software development experience at Vanta, including background agents, agent evaluation systems, and tooling that helps engineers work more effectively with AI. The team combines software engineering, developer experience, AI systems, and product thinking to turn emerging capabilities into reliable workflows used in real engineering work.

As a Senior Software Engineer on the AI DX team, you’ll help shape these systems from the ground up. You’ll work directly with engineers to understand friction in their workflows, build practical solutions, and use evidence from real usage to continuously improve quality, reliability, and adoption.

Visit our Vanta Engineering Blog to learn more about what our team is working on!

What you’ll do as a Senior Software Engineer at Vanta

• Plan, build, and improve background-agent infrastructure that enables reliable, trackable, and repeatable automated engineering work.
• Develop systems for evaluating agent performance using task outcomes, quality measures, human intervention, cost, and other signals.
• Create evaluation sets and feedback loops that help AI systems improve over time through regular review, tuning, and correction.
• Improve how engineers discover, understand, and use shared AI tools and workflows.
• Evaluate AI development tools, including code generation, AI-assisted review, and testing, against real engineering needs, and help integrate the ones that prove useful.
• Develop visibility into which tools and workflows are useful, where they create friction, and how they should evolve.
• Create clear guidance and documentation that helps engineers adopt new AI-enabled development practices.
• Improve code review workflows by using feedback from real engineering work to identify and address recurring friction.
• Influence the foundations of an autonomous software factory, including systems that help agents complete bounded engineering tasks safely and effectively.
• Work directly with engineers and internal users to understand their needs, validate solutions, and make thoughtful product tradeoffs.
• Help the team move ambiguous, dependency-heavy projects from early exploration through reliable delivery.
• Raise the quality bar through thoughtful code reviews, technical design discussions, testing, observability, and attention to reliability and security.
• Partner closely with engineers and cross-functional stakeholders while contributing as a dependable, collaborative teammate.

How to be successful in this role

• Substantial industry software engineering experience.
• Experience taking technical leadership roles on teams or complex projects.
• Experience improving AI systems, creating evaluation sets, and driving quality hill-climbing through measurement and iteration.
• Strong software engineering fundamentals and experience designing, building, testing, and operating reliable systems.
• Experience with developer tooling, AI-enabled workflows, agentic systems, infrastructure, or related technical domains.
• A track record of working through ambiguity, decomposing complex problems, managing dependencies, and helping projects reach completion.
• Experience working in rapidly scaling startups or larger companies, particularly in environments with a strong bias for action.
• An action-oriented approach and a willingness to engage directly with users and contribute hands-on.
• Product judgment and curiosity: you bring strong technical opinions while staying focused on building platforms that meet users where they are.
• Strong written and verbal communication, with the ability to explain technical concepts clearly and create guidance that helps others adopt new tools.
• A collaborative approach and a demonstrated ability to make meaningful contributions as part of a team.
• Uses AI in day-to-day work to amplify their skills and strengthen their outcomes, applying it across routine workflows, actively building fluency through experimentation, and exercising sound judgment to ensure AI-assisted work meets a high quality bar.