Senior AI Infrastructure Engineer

The Senior AI Infrastructure Engineer will serve as a technical cornerstone of VideoAmp's AI Infra team, driving the design and execution of agentic workflow systems that bridge VideoAmp's platform APIs and AI-powered customer experiences. This is a high-impact individual contributor role at the intersection of LLM infrastructure, API design, production reliability, and developer enablement. You will architect and own production-critical systems serving live customers, operate in a rigorous evaluation-driven culture, and help VideoAmp safely scale its agentic platform to direct enterprise consumers.

Responsibilities

Own multi-tenant tool layers. Design and implement multi-tenant isolation, rate limiting, and caller-attribution systems as direct enterprise customers use MCP tools; Extend A2A interfaces and experiences. Enable customer and internal agents to invoke other agents in support of new initiatives; Build and own durable agent runtimes, including long-running execution, task lifecycle management, and failure recovery; Lead evaluation-driven development. Design golden scenario suites, automated CI/CD evaluation pipelines, and regression detection across all workflows. Evaluation is a parallel engineering workstream, not an afterthought; Implement progressive discovery strategies for context, tools, agents, and skills, using deferred loading, search, categorization, and semantic filtering; Design the agent harness and orchestration loop, leveraging isolated context, shared memory, and multi-agent coordination; Drive new agentic capabilities from design to launch for customer experiences, owning production rollouts; Participate in on-call rotation for customer-facing production systems; contribute to incident response, postmortems, and reliability improvements. This team practices full-lifecycle ownership; Partner with internal engineering teams to negotiate and promote API-first designs that serve both programmatic and agentic consumers; Contribute to multi-provider LLM abstraction layers, ensuring flexibility among LLM providers; Facilitate AI office hours and cross-team enablement, serving as the internal expert on LLM tooling, agentic patterns, and tool configuration for teams across VideoAmp engineering; Author, review, and drive clear technical requirements documentation for new solutions: design docs, architecture diagrams, and postmortems.

Requirements

6+ years of software engineering experience, with 1+ years in AI/ML infrastructure, LLM platform engineering, or agentic system development; Strong Go (Golang) engineering skills; backend systems are Go-first. Proficiency in Python and SQL is also expected; Production API design and operations: strong background in resource-based API design and experience building or consuming developer-facing platform APIs at scale, including on-call and incident response; Multi-tenant system design: experience implementing rate limiting, caller attribution, tenant isolation, and external support surfaces for shared production APIs; Deep experience with LLM APIs such as Anthropic or OpenAI, including prompt engineering and tool use/function calling; Practical experience designing agent loops for production systems, including context and state management across turns, prefix caching for latency and cost, and coordinating multi-step task execution; Experience with MCP or equivalent tool-layer abstractions for exposing platform capabilities to AI agents, or for building agents that consume them; Familiarity with A2A protocols and long-running, durable workflows; Experience building automated test and evaluation suites for LLM-based systems, including golden scenarios, regression detection, and quality gates in CI/CD; Track record of working across engineering, product, and operations teams to drive alignment and rollout of shared infrastructure and capabilities; Ability to produce design documents, postmortems, and system diagrams that create shared understanding across technical and non-technical stakeholders.

Nice to have

AdTech or media measurement familiarity, including linear TV, OTT, CTV, and digital video; Open-weights model experience such as Llama or Mistral; Fine-tuning experience such as LoRA or PEFT; Familiarity with Rust.

Benefits

Equity participation included; Discretionary & flexible PTO + Spring, Summer & Winter company breaks; Inclusive and comprehensive medical, dental & vision; 401(k) with matching · HSA & FSA; Paid Maternity & Parental Leave for all family additions; Cell phone & wifi reimbursement · Commuter benefits