Major League Soccer has built Fan Genome, a 360° fan intelligence platform that unifies demographic, behavioral, transactional, and engagement data across the league. Fan Genome is evolving from a data platform into an AI-native intelligence foundation that enables semantic understanding, real-time fan context, and autonomous data-driven reasoning.

We are seeking a Senior Director, AI Data Architect to own the technical architecture and evolution of MLS’s next-generation data and intelligence platform. This is a deeply technical and hands-on leadership role focused on building the foundations for knowledge graphs, semantic layers, and context engineering that power AI systems, autonomous agents, and advanced fan intelligence at scale.

This role is oriented toward the next generation of data and intelligence platforms, emphasizing semantic understanding, contextual modeling, and AI-driven capabilities.

Platform and Architecture Leadership

• Own the end-to-end architecture of MLS’s cloud-native Fan Genome platform, ensuring scalability, reliability, and extensibility for AI-native workloads.
• Lead the evolution from analytical data models toward semantic and graph-based representations of fan, content, commerce, and engagement domains.
• Define architectural patterns that support real-time, batch, and hybrid data processing for both human and machine consumption.

Knowledge Graphs and Semantic Layer

• Design and operate enterprise knowledge graphs modeling fan identity, relationships, behaviors, and interactions.
• Build and maintain a semantic layer that encodes business meaning, context, and logic for consistent use across systems and AI agents.
• Define ontologies, taxonomies, and metadata standards that support reasoning, inference, and explainability.
• Integrate graph systems with Lakehouse storage, APIs, and downstream AI platforms.

AI-Native and Agentic Data Systems

• Lead development of context engineering frameworks enabling AI models and autonomous agents to understand fan state, intent, and history.
• Enable agentic workflows for data exploration, insight generation, anomaly detection, and feature discovery.
• Partner with applied AI and ML teams to integrate feature stores, embeddings, vector search, and retrieval-augmented generation pipelines.
• Establish guardrails for AI-safe data access, grounding, and governance.

Streaming, Compute, and Data Foundations

• Own and optimize real-time ingestion and event-driven processing using Apache Kafka, Amazon Kinesis, and Apache Flink.
• Manage distributed compute with Apache Spark for feature engineering, graph construction, and ML-adjacent workloads.
• Oversee open table formats such as Apache Hudi and Apache Iceberg to ensure ACID compliance, schema evolution, and incremental processing.
• Drive performance and cost optimization for low-latency analytical and AI workloads, including federated and zero-copy query patterns.

APIs, Identity, and Fan Context

• Maintain and evolve data and intelligence APIs supporting batch access and low-latency per-fan queries.
• Advance identity and entity resolution to support unified fan profiles and graph-based reasoning.
• Ensure Fan Genome serves as the authoritative source of fan context for personalization, marketing, and AI-driven experiences.

Governance, Security, and Quality

• Establish enterprise-grade governance with frameworks such as AWS Lake Formation, including lineage, access control, and compliance.
• Define data and semantic contracts to ensure stability and trust for downstream systems and AI agents.
• Implement observability, data quality, and cost governance across data, graph, and AI pipelines.

Leadership and Team Building

• Build, mentor, and scale a high-performing team of data and platform engineers.
• Foster a culture of technical rigor, systems thinking, and experimentation.
• Act as a technical leader and partner to product, platform, and AI stakeholders across MLS.

Qualifications

• Bachelor’s degree in Computer Science or a related field required. Advanced degree preferred.
• 10+ years of experience in data engineering, platform engineering, or AI-adjacent systems.
• 8+ years of experience leading highly technical teams delivering production-grade platforms.

Required Skills and Experience

Core Platform Engineering

• Deep experience designing and operating cloud-native data platforms on AWS, Azure, or GCP.
• Strong computer science fundamentals with proficiency in Python, Scala, or Java.
• Expertise in distributed systems, real-time streaming, and large-scale data processing.

Knowledge Graphs and Semantics

• Proven experience building knowledge graphs, semantic layers, or graph-based data platforms.
• Experience with graph databases, RDF or property graph models, and graph processing frameworks.
• Strong understanding of ontologies, metadata modeling, and semantic consistency.

AI-Native Data Platforms

• Experience designing data platforms optimized for AI and agent consumption.
• Familiarity with embeddings, vector databases, retrieval-augmented generation, and context pipelines.
• Experience supporting autonomous or semi-autonomous agents for analytics or intelligence use cases.

Data Foundations and Tooling

• Expertise with Lakehouse architectures and open table formats such as Apache Hudi or Apache Iceberg.
• Strong experience with Apache Spark, Apache Flink, Kafka, and real-time pipelines.
• Proficiency with Infrastructure-as-Code, CI/CD, containers, and observability tooling.

Governance and Trust

• Experience implementing fine-grained access control, lineage, and compliance frameworks.
• Ability to design data and semantic contracts that support stable integrations.

Desired Skills

• Experience with fan or customer 360 platforms and identity resolution systems.
• Background in personalization, experimentation, or AI-driven engagement platforms.
• Experience combining graph-based reasoning with vector search or embedding-based systems.
• Knowledge of soccer or sports media ecosystems.
• Spanish language proficiency.
• Willingness to travel and work non-traditional hours when required.

Total Rewards

Major League Soccer offers a competitive starting base salary of $200,000 - $230,000, based on individual qualifications, market financials, and operational business needs. We are committed to providing a Total Rewards package that attracts, supports, engages, and retains talent. Our benefits package includes comprehensive medical, dental, and vision coverage, a $500 wellness reimbursement, and generous Holiday and PTO schedule to promote work-life balance. We also prioritize career and professional development, offering on-the-job training, feedback, and ongoing educational opportunities.

We believe in the power of in-person collaboration to fuel creativity, strengthen connections, and cultivate a vibrant workplace. As a result, employees are required to work from an MLS office at least four days a week. We understand the value of balance, so employees also have the flexibility of working remotely on Fridays, along with the option to take up to two additional remote flex days each month.

At Major League Soccer, we are proud to be an equal opportunity employer. We value diversity and inclusion and believe that a diverse workforce enhances our ability to compete in the marketplace. We are committed to providing equal employment opportunities to all individuals regardless of race, color, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, disability status, genetic information, protected veteran status, or any other characteristic protected by law.

We are dedicated to ensuring that individuals with disabilities are provided reasonable accommodation throughout the job application or interview process, essential job functions, and other benefits and privileges of employment. If you require accommodation, please contact us to request it.

Join our team and be part of the Major League Soccer family, where we elevate the game and inspire greatness!