Staff Software Engineer, Audiences

Fetch•US - Remote,

About The Position

Fetch is building capabilities to turn purchase insights into a scalable audience business, enabling advertisers to reach known buyers and prospective customers through predictive and lookalike audiences. The product combines Fetch purchase data with licensed identity and attribute data to expand reach beyond existing users. The Staff Software Engineer will lead hands-on engineering for these products, partnering with Data Science, Product, and Data Platform to turn audience models from prototypes into reliable products that advertising partners can activate. The role can be based at a Fetch office in the United States or worked remotely within the United States.

Requirements

12+ years of professional software engineering experience, including ownership of data-intensive products from design through production adoption.
Strong coding, API design, data modeling, and distributed-systems skills.
Experience operationalizing ML or predictive systems, including data dependencies, evaluation workflows, deployment, batch scoring, and monitoring.
Demonstrated experience setting technical direction for an engineering domain, aligning teams around architecture and priorities, and leading complex initiatives from ambiguous requirements through production adoption.
Experience making and evolving architectural decisions for production systems while balancing near-term delivery with long-term reliability, scalability, operating cost, and maintainability.
Ability to explain technical tradeoffs, build agreement across teams, and resolve dependencies and ownership boundaries.
Experience increasing the effectiveness of other engineers through design reviews, mentoring, technical standards, and breaking complex initiatives into work multiple engineers can deliver.
Track record of delivering measurable outcomes and using production results to guide improvements.
Experience with identity resolution, audience activation, adtech, or partner data integrations.

Responsibilities

Develop services and workflows for the audience lifecycle, including defining seed audiences, incorporating identity and attribute data, scoring eligible populations, validating membership, refreshing segments, and delivering audiences to partners and DSPs.
Partner with Data Science to productionize predictive and lookalike models through repeatable training, evaluation, deployment, and batch-scoring workflows; make it straightforward to introduce and compare models and refresh audiences as data and behavior change.
Integrate identity mappings and partner-specific delivery requirements; track audience coverage through matching and delivery, diagnose losses, and build repeatable integrations for additional partners.
Build product quality and operational controls, including versioning datasets, models, and audience definitions; implementing monitoring, quality checks, safe retries, corrections, and access controls; and enforcing data-use restrictions.
Shape the audience engineering roadmap, make architecture and build-versus-reuse decisions, and guide engineers through delivery.
Build on shared ingestion, storage, orchestration, and governance capabilities in partnership with the core Data Platform team.