Software Engineer 5 - Ads Media Planning

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next.

The Ads Platform Engineering org builds advertising systems and integrations that power the delivery of ads using our world-class content delivery ecosystem. We use a number of Netflix investments and innovations to power our ads — a unique mix of client and server-side ad insertions, state-of-the-art content delivery systems, ad encoding recipes, content understanding and metadata, etc. We respect the viewing experience while driving great outcomes for advertisers.

We also ensure advertiser brand safety during serving, and that members only see the most appropriate ads for them.

The Media Planning team is at the heart of designing and delivering state-of-the-art media planning solutions that power Netflix's advertising business. We develop innovative, in-house ad tech systems that enable advertisers and internal partners to plan, allocate, and optimize media investments across Netflix's platform. Our technology translates advertiser objectives into actionable media plans, ensuring seamless integration, automation, optimization, compliance, and management of media strategies  work closely with cross-functional teams to deliver capabilities that serve our advertisers, members, and Netflix's broader business goals.

Our team's core focus areas in media planning include:

• Building applications and APIs that support every stage of the media planning process, from initial plan creation and inventory allocation through to campaign activation and completion.
• Delivering transparency on media plan performance and providing users with actionable insights to optimize their strategies.
• Partnering closely with our applied-science colleagues to bring optimization, forecasting, and LLM/agentic capabilities into production as reliable, observable, and performant services.
• Building the shared services and data pipelines that keep those capabilities dependable and well-understood in production.
• Partnering with stakeholders across the Ads Platform (Engineering, Product, Data Science, and Design) to develop scalable, impactful media planning solutions that drive business value.

Our team is new and yet faced with the enormous ambitions of building highly performant advertising systems and delivering high impact to our business by monetizing our incredible slate of content. As one of the newest entrants in the Connected TV advertising space that's rapidly growing, we seek to build unique value propositions that help us differentiate from the competition and become a market leader in record time.

We are looking for highly motivated engineers working in the advertising space who are excited to join us on this journey.

• Experience building modern backend and frontend applications on cloud / AWS using Java, Spring Boot, GraphQL or equivalent technologies.
• Experience with distributed systems and microservices, modern databases, queues, and workflow orchestration.
• Solid understanding of CI/CD pipelines and Dev Ops practices.
• Advertiser facing / demand-side experience: familiarity with key concepts including, but not limited to Media Planning, Audiences, Creatives, Measurement, Forecasting, Optimization, Ad Serving, Reporting, Billing, and Campaign or Order Management.
• Proven track record of championing AI adoption within a team, building standardized workflows that leverage generative AI.
• Ability to thrive in a fast-paced, dynamic environment and manage multiple priorities effectively.
• Broad knowledge of ad tech and advertising landscape, programmatic advertising, and digital marketing trends.
• Excellent communication, negotiation, and relationship-building skills.

• Applied ML / Gen AI engineering — hands-on experience applying AI, ML, or Gen AI to product…