{"id":952217,"url":"https://alion.io/job/videoamp-principal-ai-infrastructure-engineer","title":"Principal AI Infrastructure Engineer","company":{"id":685155,"name":"VideoAmp","domain":"videoamp.com","url":"https://alion.io/company/videoamp","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":null},"role":"DevOps","role_family":"DevOps","seniority":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":184000,"max":210000,"currency":"USD","period":"year","gross":null,"usd_annual":210000},"salary_estimate":null,"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A2A","optional":false},{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Anthropic","optional":false},{"name":"CI/CD","optional":false},{"name":"Function Calling","optional":false},{"name":"Go","optional":false},{"name":"LLM","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"OpenAI","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Tool Use","optional":false},{"name":"Fine-tuning","optional":true},{"name":"Llama","optional":true},{"name":"LoRA","optional":true},{"name":"Mistral","optional":true},{"name":"PEFT","optional":true},{"name":"Rust","optional":true},{"name":"Transformers","optional":true},{"name":"Wi-Fi","optional":true}],"status":"live","first_seen_at":"2026-07-28T01:48:48Z","employer_posted_date":"2026-09-15","last_verified_at":"2026-10-01T07:27:51Z","board_verified":true,"closed_at":null,"days_open":65,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":65},"description":"Principal AI Infrastructure Engineer\nRemote, United States | Remote | $184,000 to $210,000 + Equity + Benefits\nAbout VideoAmp\nVideoAmp is on a mission to create the best employee and workplace experience where people can bring their whole self to work everyday. We believe that accomplishing something great requires a special group of people who work hard, drive results and have a blast while doing it - people who challenge the status quo and embody our values. People who say \"I'll find a way\" instead of saying \"it can't be done.\"\nAt VideoAmp, we're rebuilding advertising technology and infrastructure so everyone, not just the biggest, can compete.. We do this by enabling companies to execute on business outcomes across their media investment instead of more traditional media metrics. VideoAmp is the software and data solutions company powering the convergence of linear TV and digital video advertising. This enables marketers and content owners to holistically plan, transact, and measure deduplicated audiences across digital video, OTT, connected and linear TV advertising.\nThe Role\nThe Principal 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.\nYou 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.\nWhat You'll Do\nThe AI Infrastructure team owns the production-critical stack that powers VideoAmp's agentic experiences. At the core, agent runtimes leverage MCP tools and specialized agents to deliver end to end experiences and workflows. A comprehensive observability layer acts as the basis for replay, analysis, and supervised learning. Quality is ensured via an evaluation framework that provides automated workflow testing with quality gates wired into release pipelines.\nThe team is actively building the next phases of the platform, including A2A APIs, multi-agent delegation, durable long-running agent task runtimes, reusable skills, workflows, agent memory, and agent knowledge. You will have the opportunity to shape how these systems scale, how they interoperate, and how the next generation of VideoAmp's agentic platform is designed from the ground up.\nKey Responsibilities\nOwn multi-tenant tool layers. Design and implement multi-tenant isolation, rate limiting, and caller-attribution systems as direct enterprise customers use MCP tools.\nExtend A2A interfaces and experiences. Enable customer and internal agents to invoke other agents in support of new initiatives.\nBuild and own durable agent runtimes, including long-running execution, task lifecycle management, and failure recovery.\nLead 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.\nImplement progressive discovery strategies for context, tools, agents, and skills, using deferred loading, search, categorization, and semantic filtering.\nDesign the agent harness and orchestration loop, leveraging isolated context, shared memory, and multi-agent coordination.\nDrive new agentic capabilities from design to launch for customer experiences, owning production rollouts.\nParticipate in on-call rotation for customer-facing production systems; contribute to incident response, postmortems, and reliability improvements. This team practices full-lifecycle ownership.\nPartner with internal engineering teams to negotiate and promote API-first designs that serve both programmatic and agentic consumers.\nContribute to multi-provider LLM abstraction layers, ensuring flexibility among LLM providers.\nFacilitate 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.\nAuthor, review, and drive clear technical requirements documentation for new solutions: design docs, architecture diagrams, and postmortems.\nWhat You'll Bring\nRequired\n7+ years of software engineering experience, with 1+ years in AI/ML infrastructure, LLM platform engineering, or agentic system development. \nStrong Go (Golang) engineering skills; backend systems are Go-first. Proficiency in Python and SQL is also expected.\nProduction 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.\nMulti-tenant system design: experience implementing rate limiting, caller attribution, tenant isolation, and external support surfaces for shared production APIs.\nDeep experience with LLM APIs such as Anthropic or OpenAI, including prompt engineering and tool use/function calling.\nPractical 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.\nExperience with MCP or equivalent tool-layer abstractions for exposing platform capabilities to AI agents, or for building agents that consume them.\nFamiliarity with A2A protocols and long-running, durable workflows.\nExperience building automated test and evaluation suites for LLM-based systems, including golden scenarios, regression detection, and quality gates in CI/CD.\nTrack record of working across engineering, product, and operations teams to drive alignment and rollout of shared infrastructure and capabilities.\nAbility to produce design documents, postmortems, and system diagrams that create shared understanding across technical and non-technical stakeholders.\nNice to Have\nAdTech or media measurement familiarity, including linear TV, OTT, CTV, and digital video.\nOpen-weights model experience such as Llama or Mistral.\nFine-tuning experience such as LoRA or PEFT.\nFamiliarity with Rust.\nCompensation & Benefits\nBase Salary\n$184,000 to $210,000 (commensurate with experience)\nEquity\nEquity participation included\nTime Off\nDiscretionary & flexible PTO + Spring, Summer & Winter company breaks\nHealth\nInclusive and comprehensive medical, dental & vision\nFinancial\n401(k) with matching · HSA & FSA\nFamily\nPaid Maternity & Parental Leave for all family additions\nPerks\nCell phone & wifi reimbursement · Commuter benefits\nOur Values\n01 One VideoAmp\nWe win together\nWe operate as one team, prioritizing shared success over individual wins. We collaborate across functions, support one another, and assume positive intent, because when one of us succeeds, we all do.\n02 Own the Outcome\nAccountability + Empowerment\nWe take full responsibility for results, not just tasks. We act with urgency, make decisions with confidence, and own both successes and setbacks while continuously improving.\n03 Raise the Bar\nQuality · Trust · Excellence\nWe hold ourselves and each other to a high standard. We deliver thoughtful, high-quality work, build trust through consistency and integrity, and continuously push for better outcomes.\nReady to build what's next in AI-powered media measurement?\nVideoAmp is an equal opportunity employer committed to building an inclusive, diverse team. We celebrate different perspectives, experiences, and backgrounds, because that's how we build something great.\nvideoamp.com\nRemote, United States","description_format":"text","description_chars":7668,"description_truncated":false,"requirements":{"experience_years_min":7,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Equity","Parental leave"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Marketing Analytics & Attribution","Media & Audience Measurement"],"lifecycle":[{"event":"open","at":"2026-09-16T01:48:12Z"}],"liveness":{"score":13,"band":"cold","label":"Long shot","p_open":1,"p_active":0.462,"p_room":0.28,"age_days":65,"expected_fill_days":24,"reasons":["conf:11","win:tail","crowd:"],"computed_at":"2026-10-01T05:45:00Z"},"pay":{"stated_usd_annual":210000,"is_top_pay":true},"html_url":"https://alion.io/job/videoamp-principal-ai-infrastructure-engineer","json_url":"https://alion.io/job/videoamp-principal-ai-infrastructure-engineer.json","meta":{"generated_at":"2026-10-01T18:36:14Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":912,"day_limit":5000,"remaining_today":4088,"minute_limit":60,"resets_at":"2026-10-02T00:00:00Z"}}}