Own the platform's most complex subsystems and hardest design problems: reliability under non-determinism, integration across heterogeneous data sources, and progressive automation with appropriate human-in-loop gates.
Establish clear system boundaries and integration contracts with adjacent platforms. Design interfaces that are resilient to schema evolution and organizational change.
Ship consistently. Turn ambiguous requirements into working software that users see and trust. Bias toward iteration and measurable progress over extended design phases.
Mature the platform's AI systems from early-stage to production-grade: systematic validation, feedback loops that improve accuracy over time, and principled cost management.
Raise the engineering bar through code review, design discussions, and pairing. Provide clear technical analysis when leadership needs to understand trade-offs, feasibility, or risk.
Your Background
Core Qualifications (Must-Haves)
8+ years of software engineering experience, with demonstrated ability to own and deliver complex systems end-to-end — from design through production operation.
Deep expertise in distributed systems design, fault tolerance, and building reliable systems from unreliable components.
Strong full-stack engineering fundamentals. Our stack: Node.js/TypeScript (backend, Express), React/TypeScript (frontend), PostgreSQL with Drizzle ORM, Python for ML pipeline components, OpenAI and Google Gemini APIs.
Demonstrated bias toward shipping. Track record of turning ambiguous problems into working systems on a reasonable timeline — not just designs or proposals.
Good technical judgment under uncertainty. Pragmatic trade-offs, knowing when "good enough" is right, and not over-engineering when the problem doesn't call for it.
Preferred Qualifications (Nice-to-Haves)
Experience designing systems that handle non-deterministic or probabilistic outputs (ML models, LLM pipelines, or similar) with appropriate confidence scoring and fallback strategies.
Familiarity with LLM application patterns: prompt engineering, multi-model orchestration, agentic tool use, and cost optimization for high-volume LLM workloads.
Experience with document AI or structured data extraction from unstructured sources (documents, image, natural language) at scale.
Background in ad tech, revenue operations, or media operations — order management, pricing logic, deal lifecycle.
Experience building over heterogeneous enterprise data sources with varying freshness, schemas, and access patterns.
The AI Mandate
Tubi expects engineers at all levels to leverage AI tools (Claude Code, Codex, Cursor, MCP integrations) to accelerate delivery, testing, and documentation. For this role specifically, AI goes further — it is not a feature on this platform but the reason the platform exists. You don't need to arrive as an AI expert, but you need to develop deep fluency quickly and apply it with production-grade discipline:
Trust Engineering: Building systems where human operators can progressively delegate to AI — and where the blast radius is contained when AI is wrong.
AI as Leverage: Thinking about AI as a force multiplier for a small team. The systems you build should measurably expand what the team can accomplish.
Cost Discipline: Treating AI spend as an engineering problem — optimizing for accuracy per dollar, not just accuracy alone.
Pragmatic Adoption: Evaluating new capabilities with a builder's eye — what to use now, what's hype, what to wait for.
#LI-SL4
#LI-Hybrid
Pursuant to state and local pay disclosure requirements, the pay range for this role, with final offer amount dependent on education, skills, experience, and location is listed annually below. This role is also eligible for an annual discretionary bonus, long-term incentive plan, and various benefits including medical/dental/vision, insurance, a 401(k) plan, paid time off and other benefits in accordance with applicable plan documents.
High cost labor markets such as but not limited to Los Angeles, New York City, and San Francisco
$227,200—$324,500 USD
Tubi is a division of Fox Corporation, and the FOX Employee Benefits summarized here, covers the majority of all US employee benefits. The following distinctions below outline the differences between the Tubi and FOX benefits:
For US-based non-exempt Tubi employees, the FOX Employee Benefits summary accurately captures the Vacation and Sick Time.
For all salaried/exempt employees, in lieu of the FOX Vacation policy, Tubi offers a Flexible Time off Policy to manage all personal matters.
For all full-time, regular employees, in lieu of FOX Paid Parental Leave, Tubi offers a generous Parental Leave Program, which allows parents twelve (12) weeks of paid bonding leave within the first year of birth, adoption, surrogacy, or foster placement of a child in addition to applicable government leave program(s) and FOX’s short-term disability policy. This time is 100% paid through a combination of any applicable state, city, and federal leaves and wage-replacement programs in addition to contributions made by Tubi.
For all full-time, regular employees, Tubi offers a monthly wellness reimbursement.
About Tubi
Boldly built for every fandom, Tubi is a free streaming service that entertains over 100 million monthly active users. Tubi offers the world's largest collection of Hollywood movies and TV shows, thousands of creator-led stories and hundreds of Tubi Originals made for the most passionate fans. Headquartered in San Francisco and founded in 2014, Tubi is part of Tubi Media Group, a division of Fox Corporation.
We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, gender identity, disability, protected veteran status, or any other characteristic protected by law. We will consider for employment qualified applicants with criminal histories consistent with applicable law.
