Engineering Manager, Search & Consumer AI

About the Team

Fanatics Core is the engineering organization building the shared capabilities, including search, AI, and customer intelligence, that every product across the Fanatics ecosystem builds on. We are seeking an Engineering Manager to lead the team that owns Search and Consumer AI. This leader will own some of the most leveraged surfaces we build: how fans find what they’re looking for, how AI shows up inside our apps, and how AI powers an excellent customer experience.

You will lead a team of software engineers spanning two closely connected charters:

• Consumer AI: customer support AI, including LLM-powered assistants, conversational analytics, sentiment analysis, predictive troubleshooting, and the tooling that lets customer success teams act on AI-generated insights; and (2) embedded AI experiences in the fan journey, such as AI commentary, recommendations, summaries, and in-app assistance.
• Search: native search, including query understanding, relevance and ranking, autocomplete, and personalization; and (2) AI search, including natural-language and conversational search that lets fans ask for what they want in their own words and get answers, not just results.

Success in this role requires strong partnership with Product, Data Science, Customer Operations, and product teams across the ecosystem to shape the roadmap, make smart trade-offs, and deliver outcomes fans feel. You’ll work on complex, high-scale challenges as part of a team that values innovation, collaboration, and excellence.

Responsibilities

Delivery & Ownership

• Lead the team to deliver against commitments across Search and Consumer AI, owning delivery plans end to end: scope and sequence work, remove blockers, and manage risk.
• Set a high bar for reliability, performance, and relevance quality, with observability in place for AI and search services.
• Ensure the team’s work meets Fanatics standards for data governance, security, compliance, and responsible AI.
• Own on-call, incident response, and operational health for the team’s systems.

Strategy & Roadmap

• Partner with Product and engineering leadership on planning and roadmap building, using technical insight and fan impact to influence priorities.
• Connect day-to-day execution to team strategy and Fanatics business goals so engineers understand why their work matters.
• Partner with product teams across the ecosystem to embed AI experiences into their surfaces, agreeing on shared ownership, interfaces, and quality bars.
• Guide how LLMs and ML models are evaluated, integrated, and rolled out in production.

Communication & Collaboration

• Coordinate across engineers, adjacent teams, and cross-functional partners to drive end-to-end delivery.
• Represent the team’s plans, progress, and risks in planning and review forums.
• Keep the team informed on goals, trade-offs, and decisions, and create space for two-way feedback.

People & Ways of Working

• Hire, onboard, and grow a high-performing team; give candid, timely feedback and invite the same.
• Mentor engineers on craft, ownership, and collaboration, and support their career growth.
• Build team processes (planning, reviews, retros, experimentation) that help the team learn fast and ship reliably.

Must be open to occasional travel to Fanatics offices and other locations for conferences, events, meetings, and team building.

Qualifications

We value aptitude over experience, but here are some key skills that will make you successful on this team:

• 1-3+ years managing a software engineering team, or significant tech-lead experience with people-leadership responsibilities, delivering complex, high-scale systems.
• Experience in a Java / AWS ecosystem; familiarity with AWS Bedrock or equivalent managed AI services preferred.
• Experience shipping consumer-facing AI/ML or NLP features to production, including integrating LLMs and building the pipelines and evaluation practices that keep them reliable.
• Strong understanding of search, discovery, or relevance systems, including how traditional search and LLM-based approaches complement each other.
• Strong technical judgment and clear, confident communication with engineers, Product partners, and leadership.
• Proven ability to mentor engineers and build a healthy, high-performing team culture.

Preferred

• Background in customer support AI or embedded consumer AI experiences (assistants, conversational analytics, AI commentary, recommendations).
• Familiarity with Kafka, Airflow, dbt, OpenSearch, Kotlin, and Salesforce.
• Experience building shared platforms consumed by multiple product teams.

Depending on the role, your interview and onboarding experience may include in-person components, such as onsite interviews or Launching into Better: LIVE—a multi-day cultural immersion in New York City for full-time, non-seasonal hires. These sessions are designed to build connection and bring our culture to life, though specific travel and participation requirements will be confirmed based on your role and location. Your recruiter will provide clear guidance at each stage of the process.

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