Senior Software Engineer, AI Platform

At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it.

AI Platform builds the shared foundations that help teams across Vanta ship trustworthy AI products. We own SDKs, model integrations, agent infrastructure, and tools for evaluating and debugging AI behavior. Our work spans quality and evaluations, data and context, and the foundations behind Vanta’s agentic experiences.

We partner closely with AI product engineers to solve real customer problems, turn successful experiments into reusable capabilities, and operate them reliably in production.

How does the team impact the business?

We help teams deliver AI capabilities faster, improve customer outcomes, and manage reliability, latency, and cost across Vanta’s AI products.

What gaps will this hire fill?

This hire will expand our ability to turn applied AI experiments into reliable, reusable platform capabilities. They will combine hands-on implementation with evaluation, operational ownership, and close product-team partnership.

Why join this team?

Your work can improve AI experiences across Vanta. Challenges include reliable agent execution, useful retrieval and context, reproducible evaluations, and tools that help engineers investigate and fix AI failures.

Growth trajectory

Grow from owning a platform capability end to end to leading broader technical initiatives, mentoring engineers, and shaping capabilities adopted across teams.

Visit our Vanta Engineering Blog https://www.vanta.com/all-categories/engineering to learn more about what our team is working on!

What you’ll do as a Senior Software Engineer, AI Platform at Vanta:

• Build shared SDKs, APIs, and infrastructure for AI features and agentic workflows.
• Integrate durable execution infrastructure for long-running agent workflows, including checkpointing, retries, human-in-the-loop steps, and recovery from partial failures.
• Evolve our agent harness, the runtime for tool calling, context management, memory, and model orchestration.
• Develop evaluation and debugging tools that turn production failures into measurable improvements and regression coverage.
• Improve model integrations, retrieval, and context delivery to support accurate, useful AI behavior.
• Own platform capabilities through rollout and operation, including reliability, observability, performance, and secure handling of customer data.