Teams at Scientific Games

Lead a small team to accelerate software engineering productivity across a global organization by improving developer workflows, tooling, testing, code review, documentation, and AI-enabled development practices. Identify bottlenecks, drive scalable engineering systems and reusable patterns, and measure productivity gains across polyglot teams and legacy platforms.

Lead a small engineering team to turn ambiguous opportunities into production software quickly and safely. Establish AI-first development, specification-driven practices, strong automated testing, CI/CD, observability, and production ownership while improving legacy systems and influencing enterprise engineering practices.

Build and run a centralized AI-enabled process re-engineering capability: diagnose current workflows, design AI-assisted solutions (retrieval, drafting, agents, orchestration), run controlled pilots with evaluation and human review, create reusable playbooks/governance, partner cross-functionally, manage vendors and TPMs, and deliver measurable business outcome improvements.