Fanduel Staff Data Architect role at FanDuel focused on building the social layer of the sportsbook experience. Responsible for leading multiple pods, setting direction, and driving initiative-level execution across priority streams.
Responsibilities
Own the architectural vision for applying AI across the data platform
Architect an agentic, AI-assisted data pipeline factory
Design and evolve AI-native tools and services
Define architecture and scope for advanced ML and deep learning workloads
Establish reference architectures, contracts, and standards for ML and AI data flows
Prevent fragmentation and duplication across AI and ML efforts
Partner with data, ML, and engineering teams to translate AI and data ideas into architecture
Evaluate emerging AI, ML, and data technologies and recommend adoption
Oversee performance, cost, and reliability of AI and ML data systems
Communicate value and direction to stakeholders
Qualification
Deep
Required
Deep, hands-on security engineering experience embedded in the software development lifecycle, from design and code review through CI/CD, deployment, and production.
Hands-on AI/LLM and agentic security experience: you understand how these systems fail in practice (prompt injection, jailbreaking, insecure output handling, data and model poisoning, excessive agency, tool-use exploits) and have strong, defensible opinions on how to secure them.
Working knowledge of the AI-specific security frameworks (OWASP LLM Top 10, MITRE ATLAS, NIST AI RMF), and a pragmatic view on how established frameworks (NIST, ISO 27001, OWASP, MITRE ATT&CK, SOC 2) extend to AI systems.
Experience securing AI or agent infrastructure such as API gateways, agent orchestration platforms, or MCP/tool-registry architectures is strongly preferred.
Familiarity with LLM red-teaming and adversarial testing tooling (e.g., Garak, PyRIT, Rebuff, Lakera Guard, or equivalent) and LLM eval/observability platforms, or a real eagerness to build depth here.
A demonstrated track record of defining and delivering multi-year security strategy in ambiguous, fast-moving environments.
Strong experience building and scaling reusable security patterns and assets across an engineering organization.
A track record of building automation and tooling that scales security capabilities and reduces manual toil.
Familiarity with modern cloud infrastructure (AWS, GCP, or Azure), CI/CD pipelines, and software development environments at scale.
Solid coding skills in at least one modern programming language (Python, Go, or similar).
Experience mentoring senior engineers and shaping technical culture across an organization.
Comfortable partnering closely with a platform engineering org (not just application teams) to embed controls at the infrastructure level.
