You and the process

With a person
Anna, in-house recruiter
9 years hiring engineers
30 minutes with a real recruiter
They read your CV with you, on a call, and say where the offers are being lost.
Didn’t find what you were looking for? Tell us what to build
Fanatics Inc.

Applied AI Engineer

  • Office
  • 3-6 years

Salary

$150,000 - 200,000/ year

AI summary

For members

The whole posting in a few lines. Sign up to read it here and on every role you open.

Sign Up to Read

Description

Fanatics is building a leading global digital sports platform. We ignite the passions of global sports fans and maximize the presence and reach for our hundreds of sports partners globally by offering products and services across Fanatics Commerce, Fanatics Collectibles, and Fanatics Betting & Gaming, allowing sports fans to Buy, Collect, and Bet. Through the Fanatics platform, sports fans can buy licensed fan gear, jerseys, lifestyle and streetwear products, headwear, and hardgoods; collect physical and digital trading cards, sports memorabilia, and other digital assets; and bet as the company builds its Sportsbook and iGaming platform. Fanatics has an established database of over 100 million global sports fans; a global partner network with approximately 900 sports properties, including major national and international professional sports leagues, players associations, teams, colleges, college conferences and retail partners, 2,500 athletes and celebrities, and 200 exclusive athletes; and over 2,000 retail locations, including its Lids retail stores. Our more than 22,000 employees are committed to relentlessly enhancing the fan experience and delighting sports fans globally.

Responsibilities

  • Are you a builder who has already shipped AI that changed how a business runs? Fanatics wants you.
  • We're hiring full-time Applied AI Engineers to join a small, senior team that sits at the center of how Fanatics transforms itself with AI. Our goal is simple and ambitious: make Fanatics a faster, more automated company. Each Applied AI Engineer works like a tiger team: embed with a business function, find its biggest bottlenecks, replace slow, manual work with AI agents and workflows that actually run in production, then move on to the next challenge.
  • This is a doer's role, not an advisory one. You'll own problems end to end: define them, design the solution, build it, prove it works, and drive adoption. You'll have real autonomy, executive visibility, and a direct line to leadership, with joint reporting to the CFO and Corporate AI Transformation Lead.
  • We're looking for someone with prior experience doing applied AI work at a startup or fast-growing company, who is used to moving quickly with limited resources and is ready to bring that pace to a global brand.
  • Embed within corporate functions across the business, find the workflows where AI can remove the most manual effort or unlock the most growth, fix them, then rotate to the next function.
  • Design, build, and deploy production-grade agents and agentic workflows using frontier models (Claude, GPT, Gemini) and the modern agent stack: MCP servers, agent SDKs, orchestration tools, browser and computer use, and evals.
  • Move fast: take a high-impact use case from concept to working solution in weeks, not quarters, and prove it with measurable results.
  • Think in systems and bias toward solving the problem, not toward building for its own sake. Sometimes the right answer is a custom agent; sometimes it's configuring an existing tool.
  • Partner with business leaders to be accountable for outcomes, and help them rethink how their teams operate in an AI-first way.
  • Call balls and strikes: pressure-test whether a problem is worth automating, what "good" looks like, and how to measure ROI.
  • Help set the bar for AI across the company, including tool evaluation, security and InfoSec coordination, governance, and best practices.
  • Spread the practice: document and showcase wins, coach colleagues, and help build a company culture that automates by default.

Requirements

  • 3+ years of experience in applied AI or software engineering, including time at a startup or fast-growing company where you shipped AI-powered products or automations to real users.
  • A track record of building and deploying custom agents or agentic workflows with frontier LLMs that solved real business problems, not just prototypes.
  • Fluency with the modern AI stack: LLM APIs, MCP, agent frameworks (Claude Agent SDK, OpenAI Agents SDK, LangGraph, or similar), prompt engineering, RAG, and evaluation methods.
  • Strong coding skills (Python preferred) and the judgment to pick the right tool for the job, including buying or configuring instead of building.
  • Comfort operating independently in ambiguity, with a high bar for speed, ownership, and follow-through.
  • A strategic mindset paired with a "get it done" attitude; you can tell the difference between a cool demo and a business outcome.
  • Excellent written and verbal communication, with the ability to earn trust and drive change with senior business leaders.
  • Bachelor's degree in Computer Science, AI/ML, Software Engineering, or a related field preferred; equivalent practical experience welcome.
  • Bonus points if you're a fan of sports, collectibles, or fandom culture (because we're a little obsessed).
  • Why You'll Love It Here
  • Real ownership of high-visibility problems, with exposure to every part of Fanatics and direct access to senior leadership.
  • A chance to be part of a small, hand-picked team shaping how a global sports and collectibles company becomes AI-first.
  • Backing for your work: dedicated headcount, budget, and executive sponsorship to get things done.
  • Competitive salary and comprehensive medical, dental, and vision coverage.
  • 401(k) plan with company match.
  • Generous paid time off, paid holidays, and parental leave.
  • Wellness benefits and a learning & development stipend.
  • NYC office with daily in-person collaboration.
  • Employee discount on Fanatics products and (yes) some sweet Fanatics swag.
  • Final Word
  • If you've built AI that moved a business and you're ready to do it at global scale, let's talk. This is where the doers build.
  • The salary range represents base pay only and does not include short-term or long-term incentive compensation. When determining base pay as part of a final compensation package, we consider several factors such as location, experience, qualifications, and training. For information about our benefits, please visit https://benefitsatfanatics.com/

Conditions

$150,000 - $200,000 USD

Fanatics will never ask candidates for money, banking information, or other sensitive personal information as part of the interview process. If you receive a suspicious message claiming to be from Fanatics recruiting, please do not respond and report it here .

Where you’d work

From the office

About the company

Fanatics Inc.

  • Industry: E-commerce

Office in New York, United States

6 of their 8 open roles are remote

Your chances

Worth a look before you spend an evening tailoring a CV for it.

  • 21 checks run
  • 2 red flags

Still hiring?

14 checks

1 red flag

How crowded?

7 checks

1 red flag

Fits Me

How well does this role fit you?

Answer a few questions or drop your CV, and every role gets a fit score with the reasons, this one first.

  • Your field
  • Level
  • Stack
  • Work model
  • Salary floor
  • Must-haves
Details11 facts · Role, Location, Compensation, Employment, Company
Tech stack
  • Python
  • LLMs
  • RAG
  • LangChain
Type
Full-time
Industry
E-commerce
Specialty
ML
Region
United States
Pay period
Annual
Show 5 more factsShow less

Role

Category
Data & Analytics
Specialty
ML
Experience
3+ years
Tech stack
  • Python
  • LLMs
  • RAG
  • LangChain

Location

Work model
Office
Region
United States
Office
  • New York, United States

Compensation

Salary
$150,000 - 200,000 / year
Pay period
Annual

Employment

Type
Full-time

Company

Industry
E-commerce

Something wrong with this vacancy?

Similar vacancies

Share this vacancy

What's wrong with it?

The employer never sees who reported.

Reason