Senior Manager, Enterprise AI Engineering
The Role
The Senior Manager, Enterprise AI Engineering will lead a team focused on turning rapidly evolving AI capabilities into practical solutions for teams across Match Group.
You will partner with functions including Finance, Legal, People, Marketing, Communications, and Operations to identify high-value opportunities, rapidly build and deploy AI-powered solutions, and scale what works across the organization.
This is a hands-on leadership role for a builder who can move comfortably between business problems and technical solutions. You’ll work with functional leaders, domain experts, Engineering, Data, IT, Security, and Privacy to take ideas from prototypes to reliable, reusable enterprise capabilities.
What You'll Do
Lead design and development of AI powered tools, agents, retrieval systems, automations, and services
Own and evolve core AI architecture - LLM Gateway, MCP Gateway, native and custom integrations, centralized app and dashboard deployment, and model access management
Shepherd solutions from prototype through production in close partnership with Engineering, Data, IT, Legal, Security, and Privacy
Partner with brand AI leads and engineering leads across teams to establish shared infrastructure and avoid duplicated effort
Define engineering practices and technical standards for building reliable, secure, and scalable AI applications
Connect related AI initiatives and actively share technology and learnings across teams
Evaluate, pilot, and roll out new models, tools, and platform feature in collaboration with legal and Security
Build frameworks to measure quality, reliability, adoption, and business impact
Manage vendor relationships and internal stakeholder expectations
Partner with functional leaders and domain experts to identify and prioritize high-impact AI opportunities and ensure solutions are grounded in real business needs
Lead and grow a team of AI engineers focused on delivering high-impact enterprise solutions across the organization.
Build and own AI infrastructure
Drive adoption and standardization
Evaluate and expand capabilities
Be the connective tissue
Who You Are
A hands-on technical leader who enjoys building as much as leading.
Experienced with modern AI technologies, including LLMs, agents, RAG, evaluations, model selection, and workflow automation.
Comfortable with APIs, data, integrations, cloud architectures, security, and enterprise systems.
Able to translate ambiguous business problems into practical technical solutions.
Pragmatic and outcome-oriented. You care about solving meaningful problems rather than using AI for its own sake.
Effective at building trust and driving complex initiatives across technical, business, and executive stakeholders.
Curious, adaptable, and comfortable operating in a field where capabilities and best practices evolve rapidly.
Qualifications
5+ years of relevant engineering and management experience, including meaningful hands-on experience building and deploying AI-powered products or systems and managing teams of engineers.
Experience building applications using modern generative AI technologies, including LLMs, agentic workflows, RAG, evaluations, and model APIs.
Strong software engineering fundamentals and experience building production systems, APIs, integrations, and data-driven applications.
Experience taking AI or emerging technologies from prototype through production and adoption.
Experience leading engineers and complex, cross-functional technical initiatives.
Demonstrated ability to work directly with business stakeholders and domain experts to translate problems into working solutions.
Excellent communication skills across technical, business, and executive audiences.
Experience building enterprise AI products or platforms used across multiple business functions.
Experience with enterprise AI architecture, cloud infrastructure, security, data integration, and governance.
Experience designing evaluation and monitoring frameworks for generative AI systems.
Experience creating reusable platforms, services, or components from initially specialized use cases.
Experience scaling emerging technologies within a large organization.