Principal AI Engineer

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

Requirements

• 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

Tech stack

Benefits