Principal Software Engineer

Fetch

87d • Remote

About The Position

Fetch is entering its AI-first era, and we’re looking for a Principal Software Engineer to design, scale, and evolve the intelligent systems that power personalized consumer and advertising experiences for millions of users.
You will design and evolve the platforms that unify data, real-time learning, inference, and delivery, enabling Fetch to serve more relevant, trustworthy, and high-performing Ads while supporting a rapidly scaling consumer business. This role requires a combination of architectural depth, Ads systems expertise, and the ability to influence technical strategy across teams.
Operating at the intersection of ad intelligence, experimentation, and large-scale distributed systems, you will be a key technical force advancing Fetch’s monetization engine. You’ll collaborate with Product, Data Science, Platform, and ML teams to drive clarity, define architectural standards, and ensure our Ads systems become more adaptive, more measurable, and more efficient over time.
This is a hands-on, high-impact technical leadership role with influence across multiple engineering collectives. Your work will shape how Fetch evolves its Ads stack: relevance, ranking, performance, measurement, and revenue integrity at scale.
This role can be based in one of our US offices or remotely within the United States.

Requirements

• Experience with Ads or performance marketing systems (ranking, pacing, delivery, incrementality, attribution).
• Proven ability to design high-scale ad-serving or recommendation pipelines with strict relevance, latency, and reliability requirements.
• Deep expertise designing or scaling intelligent, data-intensive systems used for personalization, ranking, targeting, bidding, or real-time optimization.
• Strong intuition for data quality, attribution accuracy, and revenue-integrity metrics.
• Demonstrated leadership of cross-org technical initiatives that improved reliability, velocity, monetization performance, or intelligence.
• Experience bringing ML-driven systems to production: feature pipelines, inference, safety validation, and model governance.
• Fluency in modern software ecosystems (Kubernetes, event streaming, CI/CD, observability tooling, AI-assisted development workflows).
• Ability to influence technical strategy and explain architectural decisions in business terms.
• Growth mindset: thrives in high-velocity environments, with a relentless focus on measurable outcomes and system evolution.

Nice To Haves

• Experience with learning-to-rank, bidding, pacing, or real-time feedback optimization systems.
• Familiarity with LLM agent frameworks (LangChain, Semantic Kernel, Haystack) or RAG systems.
• Demonstrated experience improving observability, latency, or cost efficiency in intelligent systems.
• Exposure to multi-modal intelligence or contextual ranking models using structured and unstructured data.
• Strong judgment around AI integration: where it drives meaningful Ads performance versus where classical optimization is more effective.

Responsibilities

• Architect for Scale, Intelligence, and Ads Quality: Design and evolve the platforms supporting Ads selection, targeting, ranking, pacing, creative optimization, delivery, and measurement. Build systems that prioritize relevance, transparency, trust, and measurable advertiser and user value.
• Advance Intelligence in Production: Partner with ML and Data Science teams to operationalize models for ranking, bidding, feedback optimization, and pacing. Define architectural patterns for online inference, model safety, explainability, and low-latency, high-throughput decision-making.
• Evolve the Ads Platform: Advance the core systems powering Fetch’s Ads: attribution, incrementality measurement, real-time signals, brand safety, fraud mitigation, and revenue integrity. Pioneer new approaches that raise both advertiser ROI and user experience quality.
• Define System and Experience Quality: Establish company-wide standards for ad and user experience quality, integrating performance, reliability, and relevance metrics. Establish platform-wide standards for performance, reliability, trust, and relevance.
• Lead Through Influence and Product Partnership: Drive architectural alignment across Ads, Data, Platform, and Product teams. Translate tradeoffs into measurable business outcomes: improved ROI, latency reduction, yield lift, and better developer velocity.
• Scale Experimentation & Learning Systems: Improve experimentation frameworks, incrementality infrastructure, and rapid-iteration tooling. Enable faster learning loops across Ads algorithms, UX surfaces, and delivery pipelines.
• Accelerate Innovation Velocity: Champion AI-assisted development, scenario testing, simulation environments, and feedback-driven observability. Enable engineering teams to iterate faster while protecting user trust, system integrity, and revenue signals.
• Mentor & Multiply Engineering Impact: Coach senior engineers and rising technical leads, elevating standards for architectural clarity, AI-driven design, measurement rigor, and thoughtful system evolution. Amplify impact through reusable frameworks and technical patterns.
• Model Technical Excellence & Responsible AI: Promote principles of responsible AI, transparency, model accountability, and safety-by-design. Shape the engineering culture around intelligent system build practices.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed