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NBCUniversal

Produces TV, film, and streaming content

Senior Software Engineer - Automation Engineering

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeNew York, NY, USA

About the Job

Requirements

  • A bachelor’s degree or equivalent practical experience in Computer Science, Information Systems, Software Engineering, Electrical Engineering, Electronics Engineering, or a related technical field.
  • At least 5 years of experience building production-grade software using Python, including libraries, services, testing, CI/CD, and code reviews.
  • Hands-on experience building applications using large language models, retrieval-augmented generation, vector databases, prompt engineering, or frameworks such as LangChain, LangGraph, LlamaIndex, or similar tools.
  • Experience designing AI-enabled workflows, reasoning agents, tool-using agents, or complex automation systems.
  • At least 3 years of hands-on experience with cloud data platforms such as Snowflake, Databricks, or similar technologies.
  • Strong understanding of production system design, including observability, reliability, scalability, performance tuning, and operational support.

Responsibilities

  • Design and build internal AI agents and automation workflows using technologies such as Snowflake Cortex, LangChain, LangGraph, or similar frameworks to support planning, tool use, retrieval, validation, and human-in-the-loop execution where appropriate.
  • Develop reusable tools, APIs, and components that engineers can compose into new agentic workflows.
  • Implement retrieval-augmented generation workflows, context management strategies, and prompt patterns that improve accuracy, reliability, latency, and cost efficiency.
  • Build evaluation harnesses, regression tests, and monitoring patterns for AI-agent behavior.
  • Define and track metrics such as task completion, groundedness, response accuracy, latency, cost, and failure rate.
  • Design guardrails and validation patterns to reduce hallucinations, unsafe outputs, and unreliable automation behavior.
  • Partner with engineering and operations teams to move AI workflows from prototype to production-ready systems.
  • Design, build, and maintain production-grade Python applications, libraries, and services.
  • Champion object-oriented design principles, including encapsulation, abstraction, inheritance/composition, reusable interfaces, and clean separation of concerns to improve maintainability and extensibility.
  • Champion software engineering best practices including modular design, automated testing, continuous integration and continuous delivery, code reviews, observability, and documentation.
  • Create reusable engineering patterns that reduce bespoke development effort and improve consistency across partner engagements.
  • Collaborate with product, engineering, operations, and data platform teams to translate repeatable business needs into scalable technical solutions.
  • Build reusable Python libraries that support clean room capabilities across first-party audience workflows and core measurement use cases, including audience onboarding, ingestion, indexing, activation, campaign and impression delivery analysis, reach and frequency, attribution, and incrementality.
  • Abstract complex analytical and data collaboration workflows into repeatable, self-service components for internal teams and external partners.
  • Enable configurable feature deployment so new audience and measurement capabilities can be delivered quickly and consistently across partners.
  • Mentor engineers through code reviews, technical design discussions, and operational best practices.
  • Help establish engineering standards for AI-assisted workflows, agentic system design, reusable libraries, and production automation.
  • Promote a culture of reliability, maintainability, and continuous improvement.

Desired Qualifications

  • Exposure to data clean room concepts or platforms such as Snowflake Clean Rooms, Databricks Clean Rooms, LiveRamp, Habu, or similar technologies.
  • Experience with advertising technology, audience activation, campaign delivery, reach and frequency, attribution, incrementality, or reporting workflows.
  • Snowflake SnowPro Core Certification, Databricks Certified Data Engineer Associate, or similar cloud/data platform certification.

About the Company

NBCUniversal

Produces TV, film, and streaming content

NBCUniversal operates as a global media and entertainment powerhouse with a portfolio spanning television, film, streaming, theme parks, and news under Comcast. It creates and distributes content across multiple platforms, including NBC for primetime and daytime TV, Telemundo for Spanish-language programming, NBC News for global coverage, film releases, streaming services, and park experiences at Universal Orlando and other properties. Revenue comes from advertising, subscriptions, box office, theme park tickets, and licensing of content to other outlets. The company differentiates itself through a large, cross-platform library and monetization network, plus integrations with Comcast to reach a wide audience. Its goal is to produce and distribute compelling content while growing audience reach and revenue across television, digital, film, streaming, and experiential channels.

Company size
10,001+
Company stage
Private
Total funding
$30.5B
Headquarters
New York City, New York
Founded
1926

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