Scientific Games Corporation

Senior Advanced Product Engineer

Scientific Games Corporation$100K — $130K *
Information Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • 10+ years of Software Engineering experience
  • Experience with full software lifecycle: design, implementation, testing, release
  • Proficient in modern AI-assisted development tools
  • Strong automated testing discipline, including TDD and regression tests
  • Ability to collaborate effectively across teams and with stakeholders

Responsibilities

  • Build new products and prototypes tied to business opportunities
  • Enhance existing legacy systems while improving quality and maintainability
  • Leverage AI tools for accelerated code generation and testing
  • Transform ambiguous product intents into clear technical specs
  • Implement disciplined automated testing practices to ensure code reliability
  • Establish fast feedback loops through CI/CD and deployment automation
  • Collaborate with cross-functional teams to align on project goals

Benefits

  • Opportunity to work in a high-impact, agile environment
  • Engage in strategic product initiatives and new business opportunities
  • Access to state-of-the-art AI tools for enhanced development practices
  • Chance to refine and improve legacy systems creatively
  • Collaboration with diverse teams, fostering a holistic understanding of product-impact
Full Job Description
Position Summary

Scientific Games is hiring two Senior Product Engineers to join a small, high-impact team focused on strategic product initiatives and new business opportunities.

This role is ideal for experienced builders who can flex across product and engineering from zero-to-one development to enhancing complex, legacy systems. You’ll be expected to deliver high-quality software quickly, make sound technical decisions, and leave systems better than you found them.

The team operates like a fast-moving product engineering pod, leveraging AI to accelerate development while maintaining long-term quality through clear specs, strong testing, and production-safe releases.

Successful candidates are product-minded, pragmatic, and technically strong. They focus on building the right solutions, earn trust through outcomes, and deliver work that is scalable, maintainable, and impactful.

What You Will Do

  • Build new products, prototypes, integrations, and production capabilities tied to strategic business opportunities.

  • Work inside existing legacy codebases while improving testability, interfaces, observability, automation, and maintainability.

  • Use AI coding tools and agentic workflows to accelerate code generation, test creation, documentation, refactoring, migration work, debugging, and review.

  • Turn ambiguous product intent into clear specs, acceptance criteria, interface contracts, examples, test plans, and release criteria.

  • Practice disciplined automated testing, including TDD, ATDD, unit tests, integration tests, contract tests, regression tests, and production validation where appropriate.

  • Create fast feedback loops through CI/CD, feature flags, preview environments, observability, deployment automation, and production-safe release patterns.

  • Partner with product, architecture, QA, DevOps, security, operations, and domain experts to make practical tradeoffs and get work into use.

  • Reduce cycle time by removing ambiguity, waiting, brittle test paths, slow reviews, unclear ownership, and avoidable rework.

  • Help define how this team works: engineering standards, technical decisions, AI-assisted development patterns, test strategy, and production readiness.

  • Share useful patterns with other engineering teams so the work improves more than one product or codebase.

Qualifications

What Success Looks Like

  • Turn ambiguous product or technical problems into clear, working solutions aligned to business outcomes

  • Move quickly without overengineering—making progress while improving code quality, tests, and system reliability

  • Work effectively in legacy systems, leaving codebases cleaner, safer, and easier to build on

  • Use AI tools to accelerate validated delivery, structuring work for fast feedback and strong testing

  • Stay focused on product impact—understanding users, workflows, and measurable results

  • Earn trust across the business for solving real problems and within engineering for high-quality, maintainable work

Experience That Fits

  • 10+ years of Software Engineering experience

  • Experience building production software across the full lifecycle: product framing, design, implementation, testing, release, operations, and iteration.

  • Experience working in large or legacy codebases while improving architecture, testability, observability, and delivery speed.

  • Hands-on fluency with modern AI-assisted development tools, including coding assistants, agentic workflows, AI-assisted code generation and review, test generation, documentation support, refactoring, migration support, and debugging.

  • Strong automated testing discipline, including TDD, ATDD, unit testing, integration testing, contract testing, regression automation, and production validation.

  • Experience building fast feedback loops with CI/CD, automated test suites, feature flags, preview environments, observability, deployment automation, and progressive release practices.

  • Strong engineering judgment across software design, APIs, integration patterns, data flows, reliability, security, and production readiness.

  • Ability to work directly with product leaders, business stakeholders, domain experts, QA, DevOps, architecture, security, and operations teams.

  • Clear written and verbal communication; able to turn ambiguity into an implementation path others can understand.

Especially Useful Backgrounds

  • Product engineering in a startup, growth-stage company, incubation team, platform team, or strategic product pod.

  • Experience bringing modern development practices into older systems without stopping delivery.

  • Regulated, high-reliability, transactional, gaming, lottery, payments, or customer-facing platform environments.

  • Cloud-native development, platform engineering, infrastructure as code, APIs, event-driven systems, distributed systems, or integration-heavy architectures.

  • Experience helping other engineers adopt better AI-assisted development, testing, release, or observability practices.


Work Conditions

Scientific Games, LLC and its affiliates (collectively, “SG”) are engaged in highly regulated gaming and lottery businesses.   As a result, certain SG employees may, among other things, be required to obtain a gaming or other license(s), undergo background investigations or security checks, or meet certain standards dictated by law, regulation or contracts.   In order to ensure SG complies with its regulatory and contractual commitments, as a condition to hiring and continuing to employ its employees, SG requires all of its employees to meet those requirements that are necessary to fulfill their individual roles.  As a prerequisite to employment with SG (to the extent permitted by law), you shall be asked to consent to SG conducting a due diligence/background investigation on you.

This job description should not be interpreted as all-inclusive; it is intended to identify major responsibilities and requirements of the job. The employee in this position may be requested to perform other job-related tasks and responsibilities than those stated above. 

Education

Masters degree preferred.


Years of Related Experience

10+ Years

About Scientific Games Corporation

Light & Wonder, Inc., formerly Scientific Games Corporation, is an American corporation that provides gambling products and services. The company is headquartered in Las Vegas, Nevada, with lottery headquarters and production plant in Alpharetta, Georgia. Light & Wonder's gaming division provides products such as slot machines, table games, shuffling machines, and casino management systems. Its brands include Bally, WMS, and Shuffle Master.
Learn more about Scientific Games Corporation
Size
9,500 employees
Market Cap
$5.6 billion
Industry
Net Income
-$569 million
Founded
1973
5 Year Trend
-5.7%
Revenue
$2.7 billion
NASDAQ

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