Principal AI Engineer

About VideoAmp

VideoAmp is the tech-first measurement company transforming how advertising is valued, bought, and sold. Powered by currency-grade big data and a best-in-class technology stack, our platform gives advertisers, publishers, and agencies the ability to plan, optimize, and measure media investments across every screen — from linear TV and OTT to CTV and digital video.

VideoAmp is accelerating investment in agentic AI and intelligent optimization technologies — helping clients drive measurable, real-world outcomes in an increasingly complex media landscape. With 880% year-over-year measurement growth, 98% coverage of the TV publisher ecosystem, and partnerships with 11 agency groups and 1,000+ advertisers, we're not just keeping pace with the industry — we're defining what comes next.

We believe great work requires great people — people who say "I'll find a way" instead of "it can't be done."

The Role

The Principal AI Engineer will serve as a technical cornerstone of VideoAmp's AI Infra team, driving the design and execution of agentic workflow systems that bridge the gap between VideoAmp's platform APIs and AI-powered experiences. This is a high-impact, senior individual contributor role at the intersection of LLM infrastructure, API design, and developer enablement.

While acting as a collaborative guide and mentor for cross-functional teams adopting AI-native development patterns, you will architect and own critical systems — including MCP servers, scenario evaluation frameworks, and agentic workflow tooling. You thrive in a fast-moving, evaluation-driven environment and are equally comfortable whiteboarding a distributed system design, leading a working group, and shipping production-quality code.

What You'll Do

• Design, build, and operate VideoAmp's AI infrastructure and its universal tool layers supporting both customer and internal workflows.
• Lead the development of scenario evaluation frameworks, including golden scenario design, automated CI/CD evaluation pipelines, and regression detection to ensure agentic workflow quality.
• Architect and implement efficient tool discovery systems (deferred loading, search-tools, tool categorization, semantic filtering) enabling scalable, multi-step agentic workflows.
• Partner with internal engineering teams to negotiate and promote API-first designs that serve both programmatic and agentic consumers.
• Own full SDLC of new Agent APIs from design through production, testing, releases, and enhancement.
• Facilitate weekly AI office hours, serving as the internal expert on LLM tooling, agentic patterns, and tool configuration.
• Contribute to multi-provider LLM abstraction layers ensuring flexibility of LLM provider (Anthropic, Snowflake, Databricks, etc.).
• Author, review, and drive clear, technical requirements documentation for new solutions.

What You'll Bring

• Bachelor's degree in Computer Science, Engineering, or a related field preferred; equivalent practical experience considered.
• 8+ years of software engineering experience, with 3+ years in AI/ML infrastructure, LLM platform engineering, or agentic systems.
• Deep hands-on experience with LLM APIs (Anthropic, OpenAI, or equivalent) and familiarity with prompt engineering, tool use / function calling, and multi-step agent orchestration.
• Strong background in resource-based API design, and experience building or consuming developer-facing platform APIs at scale.
• Experience with MCP or equivalent tool-layer abstractions for exposing platform capabilities to AI agents.
• Proficiency in Golang, Python, and SQL; comfort working across backend services, CI/CD pipelines, and cloud infrastructure.
• Experience designing and operating evaluation frameworks or automated testing pipelines for non-deterministic systems (LLMs, probabilistic models).
• Strong cross-functional collaboration skills with a track record of working across engineering, product, and operations teams to drive alignment on shared infrastructure.
• Excellent written and verbal communication skills; able to produce design documents, postmortems, and system diagrams that create unanimous understanding.

✨ Bonus Points

• Familiarity with the AdTech / media measurement landscape (linear TV, OTT, CTV, digital video).