Staff Applied AI Engineer

By bringing together next-gen technology and the finest live data available, Genius Sports is enabling a new era of sports for fans worldwide, delivering experiences that are more immersive, interactive and personalized than ever before. Learn more at geniussports.com. 

About the Role  

We are looking for a Staff Software Engineer, Applied AI to own the architecture of our multi-agent LLM reasoning layer that turns multimodal evidence (audio + video context + transcripts + rules) into validated outputs across our products. You will define how agents are decomposed, orchestrated, evaluated, and safely promoted into real-time production while balancing accuracy, latency, and cost.

You will be trusted to take on complex, ambiguous problems and drive them to successful outcomes, applying best practices in Agile software development along the way. We value engineers who can adapt quickly, learn new technologies as needed, and focus on delivering meaningful impact rather than being constrained by specific languages or frameworks.

We will lean on your technical leadership, pragmatic decision-making, and ability to balance short-term delivery with long-term system health. You will work in an environment that prioritizes Agile principles, continuous improvement, and data-driven decision-making. You are comfortable forming and testing hypotheses, validating assumptions through experimentation, and using evidence to guide architectural and product decisions.  

Key Responsibilities 

• Own the end-to-end technical direction for the multi-agent, multimodal platform that converts broadcast/radio inputs into validated, structured outputs from prototype to production.
• Design and evolve the agent architecture (agent boundaries, interfaces, and orchestration patterns), including evidence fusion, traceability/provenance, and schema-first outputs with versioning and backward compatibility.
• Define reliability standards for probabilistic systems: confidence scoring and gating, escalation paths for low-confidence segments (including optional human-in-the-loop), and safe correction/overwrite semantics for live outputs.
• Drive performance and cost optimization, selecting routing strategies (lightweight vs heavy models), and implementing batching/caching/retries that keep quality stable under real-time constraints.
• Partner across product, platform, and domain experts to translate ambiguous sport scenarios into system logic.
• Champion continuous improvement by evaluating new technologies, tools, and approaches where they provide clear value.
• Mentor and coach engineers across teams, supporting technical growth and raising the overall engineering bar.  

Qualifications   

• 10+ years of software engineering experience, including owning architecture for complex distributed or data-intensive systems.
• Proven ability to lead through influence: align stakeholders, set technical direction, and drive ambiguous projects to outcomes.
• Deep experience with agentic/LLM application architecture (tool use, structured outputs, routing)
• Proven experience with different LLM platforms, including but not limited to ChatGPT, Gemini and Claude.
• Strong understanding of MCP and RAG with production implementation experience.
• Extensive experience designing and working with RESTful APIs and distributed services.
• Experience using version control systems (e.g. Git) in collaborative, multi-team environments.
• Proven ability to solve complex problems and make sound technical decisions in ambiguous situations.
• Ability to work independently while also leading and influencing teams without formal authority.
• Excellent communication skills, with the ability to explain complex technical concepts to diverse audiences.

Preferred Qualifications   

• Hands-on experience with multimodal systems (audio/video/text).
• Background in reliability engineering / test engineering applied to ML/LLM systems.
• Experience with multiple architectural and software frameworks.
• Experience working in container based environments (e.g. Docker, Kubernetes) 
• Knowledge of modern build pipelines and tools. 
• Familiarity with Agile development methodologies. 
• Experience with testing frameworks. 
  

The salary for this role is based on an annualized range of $230,000 - $270,000 USD. This role will also be eligible to take part in Genius Sports Group's benefits plan.

We enjoy an ‘office-first’ culture and maximize opportunities to collaborate, connect and learn together. Our hybrid working models differ depending on your role and location. Occasional travel may be required.

As well as a competitive salary and range of benefits, we’re committed to supporting employee wellbeing and helping you grow your skills, experience and career. Learn more about how rewarding life at Genius can be at Reward | Genius Sports. One team, being brave, driving change 

We strive to create an inclusive working environment, where everyone feels a sense of belonging and the ability to make a difference. Learn more about our values and culture at Culture | Genius Sports.

Let us know when you apply if you need any assistance during the recruiting process due to a disability.