Principal AI Engineer

November 4

Apply Now

Receive Emails with Similar Jobs

Jump

WebsiteLinkedInAll Job Openings

Sports • SaaS • B2B

Jump is a company that offers an end-to-end fan experience platform specifically designed for sports teams and their fans. It helps sports clubs grow revenue by nurturing lifelong relationships with fans through software solutions that include primary ticketing and fan engagement apps. Jump's solutions are designed in collaboration with over 70 professional sports teams from major leagues such as the NBA, NHL, NFL, MLS, and MLB. They offer tools to manage event inventory and access control, providing a seamless and personalized fan experience to increase fan engagement, attendance, and revenue for sports teams.

11 - 50 employees

Founded 2021

⚽ Sports

☁️ SaaS

🤝 B2B

📋 Description

• Architect, build, and maintain Jump’s internal AI platform — including model evaluation frameworks, experimentation, context and prompt management systems, and fine-tuning pipelines. • Standardize and automate internal tooling: from Claude code org wide setup to orchestration frameworks for AI agents and workflows. • Design and deploy RAG systems, vector databases and other foundational components for production-grade AI systems. • Define best practices for evaluation and benchmarking of models and agentic workflows (including quality, reliability, latency, cost, and safety). • Develop templates and libraries for agentic workflows, memory, and tool use. • Partner with the engineering organization to integrate AI agents and features into Jump’s products. • Ensure reliability, observability, and scalability of AI systems across environments. • Act as an AI subject matter expert — running workshops, demos, and internal talks to help every function apply AI to their workflows. • Lead rapid experimentation initiatives — identify and prototype high-impact internal AI use cases, then scale successful ones. • Partner cross-functionally with HR, Finance, and Client Services to design and deploy AI automations that save time and increase quality. • Maintain an internal AI playbook — a living repository of best practices, design patterns, and how-to guides for prompt engineering, context design, agent building, and evaluation. • Mentor engineers and product teams on effective use of LLMs, model selection, and architecture design.

🎯 Requirements

• 10+ years in software engineering or systems architecture, with 1+ years focused on AI/ML, LLMs, and agentic systems. • Full stack development experience. • Deep technical expertise with modern AI systems and frameworks — including Foundational models APIs, AWS Bedrock, N8N, Open Source Models, LangChain or similar. • Proven experience building and deploying AI infrastructure, including evaluation frameworks, monitoring, and agentic workflows. • Hands-on experience with vector databases, RAG systems, and context management for LLMs. • Strong proficiency in Python and TypeScript, with experience integrating APIs and orchestration tools. • Familiarity with cloud infrastructure (AWS), containerization (Docker, Kubernetes), and IaC (Terraform, CloudFormation). • Experience fine-tuning LLMs. • Excellent communication and presentation skills — comfortable leading demos, training sessions, and internal talks for both technical and non-technical audiences. • A passion for teaching, experimentation, and scaling organizational impact through AI.

🏖️ Benefits

• Remote first • Competitive salary and equity • Flex PTO policy • 401(k) • Generous medical, dental and vision plans • 16 weeks paid parental leave for primary and secondary caregivers • $1,000 reimbursement for work-from-home tech setup • Company-paid sustainability subscription to ensure carbon neutrality is maintained for employee activities, such as travel