Lead product engineering for strategic new business opportunities, from problem framing through prototype, validation, production readiness, and scale.
Partner with product and business leaders to decide what is worth building, what should be built first, and how success will be measured.
Build and lead a small, high-performance engineering team with strong technical judgment, product judgment, ownership, and learning speed.
Establish an AI-first development model grounded in clear specs, TDD / ATDD, automated testing, fast feedback loops, CI/CD, observability, and production-safe release practices.
Move quickly inside legacy systems while improving the parts of the platform the team touches: cleaner interfaces, better tests, stronger automation, and less future drag.
Model a faster, safer product engineering motion for SG by showing how AI-assisted development, strong specs, strong tests, and low cycle time can work together at enterprise scale.
Experience That Fits
12+ years of experience across software engineering, product engineering, platform engineering, or technical product development
5+ years leading high-performing engineering teams or technical pods
Proven track record of building and delivering real software in fast-paced, high-ownership environments
Experience operating effectively within large, complex systems, including legacy platforms
Strong understanding of customer commitments, security, compliance, and production reliability requirements
Required Experience Includes:
Leading end-to-end product engineering: problem framing, technical design, implementation, testing, release, production operation, and iteration.
Building new products, platforms, or capabilities from early ambiguity to production use.
Working in or around legacy systems while improving architecture, testability, operability, and delivery speed.
Using modern AI-assisted software development practices, including coding assistants, agentic workflows, AI-assisted code generation and review, test generation, documentation support, migration support,
Requirements
What Success Looks Like
This person will lead a team that turns ambiguity into working software quickly and safely. The team operates close to the customer and uses AI effectively to accelerate delivery-while maintaining strong engineering fundamentals.
Additional Information
Scientific Games:
Scientific Games is the global leader in lottery games, sports betting and technology, and the partner of choice for government lotteries. From cutting-edge backend systems to exciting entertainment experiences and trailblazing retail and digital solutions, we elevate play every day. We push game designs to the next level and are pioneers in data analytics and iLottery. Built on a foundation of trusted partnerships, Scientific Games combines relentless innovation, legendary performance, and unwavering security to responsibly propel the global lottery industry ever forward.
Position Summary
Scientific Games is seeking a VP, Product Engineering to lead a small, high-impact team focused on building new products and advancing strategic business opportunities. This leader will tackle ambiguous problems, partner closely with product and business stakeholders, and deliver high-quality software quickly-without compromising platform stability.
This is a hands-on builder-leader role, responsible for driving the full product engineering lifecycle-from shaping ideas to delivering production-ready solutions. The team will operate as a lean, senior group leveraging modern AI-assisted development practices to move fast, maintain quality, and continuously improve the systems they touch.
Success in this role means balancing speed and discipline-shipping impactful solutions, enhancing legacy systems, and establishing scalable, AI-driven engineering practices that can influence the broader organization.
What This Person Will Own
Building new products, capabilities, prototypes, and production systems from zero to one.
Moving quickly and safely inside existing legacy codebases and platforms.
Helping decide which opportunities deserve engineering investment.
Creating an AI-first software delivery model based on clear specifications, acceptance criteria, automated tests, fast feedback, and low cycle time.
Using current AI development tools and emerging agentic workflows to generate code, write and improve tests, explore legacy systems, document behavior, accelerate migrations, support review, and reduce manual toil.
Establishing specification-driven development, test-driven development, acceptance-test-driven development, automated testing, CI/CD, observability, release discipline, security review, and production ownership as the foundation for speed.
Building a small, high-performance team with a strong bar for technical judgment, product judgment, learning speed, and follow-through.
Modeling agentic AI development patterns that can influence engineering practice across SG.
Sglottery · Alpharetta, GA