Staff Software Engineer, Applied AI (IC)

PrizePicks is hiring a Staff Software Engineer on its Applied AI team to build reliable, scalable AI capabilities, including an agent platform and internal tooling. The role will operationalize AI across the software development lifecycle, deliver AI features from prototype to production, and establish engineering standards while mentoring colleagues.

Responsibilities:

• Design and implement primitives like orchestration, tool/function calling, evaluation harnesses, prompt/version management, tracing/observability, and safety/guardrails
• Support patterns like retrieval-augmented generation (RAG), structured extraction, and production inference workflows
• Work with application engineering teams to embed AI into day-to-day engineering workflows (code review assist, test generation, incident support, developer copilots), with clear quality gates and measurable impact
• Own the judgment call of what to delegate to agents vs. keep as human work — scope tasks so agents are set up to succeed, and adapt that boundary as team skill levels and tooling maturity vary
• Given an agent run, diagnose whether it did its job well from the trace itself — not just the final diff. Debug agent behavior the way you'd debug a distributed system: inputs, intermediate steps, failure points
• Treat AI output as a claim to verify, not a result to trust — including tests the agent writes for its own code
• Own projects from prototype → production: data needs, system design, model/vendor selection, rollout plans, monitoring, and iteration
• Partner closely with product, design, and data/ML stakeholders to deliver customer-facing outcomes (not just demos)
• Assess where AI adoption is working and where it isn't — identify bottlenecks and failure modes across teams, not just within your own code
• Build what's missing, teach what's already built, and make the case for adoption to skeptical or hesitant engineers
• Establish best practices for reliability, evaluation, incident response, privacy/security, and "how we build AI here."
• Coach other engineers through design reviews, pairing, and pragmatic technical leadership — including how to critically review AI-generated code rather than rubber-stamp it

Requirements:

• 6+ years of professional software engineering experience (or equivalent), including shipping production systems
• Direct experience on an Applied AI / product AI team building LLM- or ML-powered features
• Demonstrated judgment in agent-driven development: knowing what to delegate, how to scope/context an agent, and how to verify its output before trusting it
• Strong backend/system design skills: APIs, distributed systems, queues/workflows, observability, and performance
• Comfort navigating ambiguity and driving outcomes with cross-functional partners (product, design, data/ML, platform)
• Track record of mentoring peers and leveling up engineering quality — including helping others build critical judgment around AI-assisted output, not just AI literacy
• You must be authorized to work for any employer in the U.S
• We are unable to sponsor or take over sponsorship of an employment Visa at this time
• agents/tooling strongly preferred
• Experience building "platform" capabilities for other engineers (SDKs, internal frameworks, developer tooling)
• Practical experience with embeddings, search/retrieval, evaluation methodologies, and model monitoring (offline + online)
• Experience building AI-powered tooling/products like agents and assistants at scale
• Familiarity with inference constraints (latency, cost, caching), vendor/model tradeoffs, and deployment patterns