Impress employers and recruiters.
Choose from hundreds of resume examples.

Impress employers and recruiters.
Choose from hundreds of resume examples.

Target Resume Now

About the Role

Catapult is building the future of sports performance technology by developing AI that can reason across athlete data to provide actionable intelligence for coaches and performance practitioners. We are seeking an Agentic AI Engineer with experience shipping production AI systems to contribute to this mission.

Responsibilities

• Design and ship specialist AI agents that use memory, tools, data, and multi-step reasoning.
• Build multi-agent orchestration that routes work between specialist agents, manages dependencies, and synthesizes conflicting outputs.
• Develop systems that evaluate confidence, uncertainty, and consequence before recommendations reach a practitioner.
• Build human-in-the-loop escalation for the system to know when to answer, ask for more information, or defer to a human.
• Create workflows that turn sport scientist expertise into validated, versioned, and testable agent capabilities.
• Build evaluation, observability, and regression testing to measure and improve agent performance in production.
• Work with domain experts to ensure AI outputs are grounded, traceable, and actionable.

Requirements

• Shipped a production agentic AI system used by real users.
• Hands-on experience with memory or persistent state.
• Hands-on experience with tool use or tool calling.
• Hands-on experience with multi-step reasoning or workflows.
• Hands-on experience with production deployment and operation of AI systems.
• Built or substantially contributed to a production multi-agent system.
• Understand agent routing and orchestration.
• Understand specialist agent composition.
• Understand dependency-aware workflows.
• Understand parallel and sequential execution.
• Understand conflicting agent outputs.
• Understand response synthesis.
• Hands-on experience calibrating probabilistic ML or AI systems.
• Comfortable with Platt scaling.
• Comfortable with Isotonic regression.
• Comfortable with Expected Calibration Error (ECE).
• Comfortable with reliability and calibration curves.
• Comfortable with confidence and uncertainty estimation.
• 5+ years of professional experience in applied ML, AI, or software engineering.
• Strong Python skills.
• Strong software engineering fundamentals.
• Experience building and operating production systems.
• Experience with production RAG and reranking.
• Experience with foundation-model fine-tuning or domain adaptation.
• Experience with LoRA, PEFT, or similar techniques.
• Experience with LLM observability and drift detection.
• Experience with evaluation harnesses and automated regression testing.
• Experience with human-in-the-loop architectures.
• Experience with confidence thresholds and escalation models.
• Experience with causal or counterfactual reasoning.
• Experience with Go/Golang.
• Experience with AWS, including ECS, EC2, Lambda, SNS, or SQS.
• Experience with GraphQL, REST, or gRPC.
• Experience with PostgreSQL or MongoDB.
• Demonstrated experience in production agentic AI.
• Demonstrated experience in production multi-agent orchestration.
• Demonstrated hands-on confidence calibration experience.

Skills

• Python
• Software engineering fundamentals
• Production RAG
• Reranking
• Foundation-model fine-tuning
• Domain adaptation
• LoRA
• PEFT
• LLM observability
• Drift detection
• Evaluation harnesses
• Automated regression testing
• Human-in-the-loop architectures
• Confidence thresholds
• Escalation models
• Causal reasoning
• Counterfactual reasoning
• Go/Golang
• AWS
• ECS
• EC2
• Lambda
• SNS
• SQS
• GraphQL
• REST
• gRPC
• PostgreSQL
• MongoDB
• Memory
• Tool use
• Multi-step reasoning
• Agent routing
• Agent orchestration
• Agent composition
• Dependency-aware workflows
• Parallel execution
• Sequential execution
• Response synthesis
• Platt scaling
• Isotonic regression
• Expected Calibration Error (ECE)
• Reliability curves
• Calibration curves
• Confidence estimation
• Uncertainty estimation

Location

• Remote

Work Type

• Full-time

Experience Level

• Senior

Salary/Compensations

• $107,250 - $214,500 per year

Benefits

• Generous paid leave
• Recognized company holidays
• Comprehensive benefits package
• Health insurance
• Dental insurance
• Vision insurance
• 401(k) retirement plan with company match

About the Company

• Catapult is building the future of sports performance technology.
• Since 2006, we’ve helped more than 5,000 teams use data, science and technology to improve athlete health, readiness and performance.
• Our customers include teams across the NFL, NBA, NHL, MLS, EPL, AFL, NRL, NCAA and many more.
• We're building the next layer of our platform: AI that can reason across everything we know about an athlete and turn it into intelligence a coach or performance practitioner can trust.
• We are building the future of sports performance.
• Our priority is to find the brightest talent who can add to our team culture, actively contribute, and be excited about what they do.

Equal Opportunity

• Research shows that while men apply for jobs when they meet an average of 60% of the criteria, women and other marginalized groups tend only to apply when they check every box. So if you have what it takes, but don't meet every single point in our job ad, please still get in touch! We would love to have a chat and see if you could be a great addition to our team.
• All offers of employment are subject to Catapult's positive prehire check.