Scientific Games Logo

Scientific Games

Senior Advanced Product Engineer

Reposted 24 Days Ago
Be an Early Applicant
In-Office or Remote
Hiring Remotely in United States
Senior level
In-Office or Remote
Hiring Remotely in United States
Senior level
Senior Product Engineer will build new products and prototypes, improve legacy systems, use AI-assisted tools to accelerate development, define specs and tests, enforce strong automated testing and CI/CD, partner across product and ops, and drive production-ready, observable, and maintainable releases.
The summary above was generated by AI
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 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

SG is an Equal Opportunity Employer and does not discriminate against applicants due to race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state or local protected class. If you’d like more information about your equal employment opportunity rights as an applicant under the law, please click here for EEOC Poster.

Similar Jobs

An Hour Ago
Easy Apply
Remote or Hybrid
USA
Easy Apply
140K-170K Annually
Senior level
140K-170K Annually
Senior level
Artificial Intelligence • Big Data • Logistics • Machine Learning • Software • Transportation
Sell FourKites SaaS supply chain and logistics solutions to new and existing Fortune 1000 accounts. Manage 15-25 accounts, exceed quota, develop strategic account plans, map solutions to customer SOPs, coordinate cross-functional GTM efforts, update Salesforce, and leverage internal AI tools to drive growth and expanded ARR.
Top Skills: Fourkites Ai ToolsLinkedin Sales NavigatorSaaSSalesforceZoominfo
An Hour Ago
Remote or Hybrid
San Francisco, CA, USA
147K-278K Annually
Senior level
147K-278K Annually
Senior level
Cloud • Software
Design, deploy, and operate large-scale, multi-region cloud-native services to improve reliability, performance, and security. Partner with application teams to build automation, run SLO-driven incident response and on-call rotations, leverage Kubernetes and CNCF tooling, and implement scalable operations, chaos and scale testing, and infrastructure-as-code for a resilient SaaS platform.
Top Skills: ArgocdAWSGoKubernetesLinux/UnixOpentelemetryPrometheusPythonService Mesh
An Hour Ago
Easy Apply
Remote or Hybrid
United States
Easy Apply
101K-153K Annually
Senior level
101K-153K Annually
Senior level
Artificial Intelligence • Cloud • Computer Vision • Hardware • Internet of Things • Software
Drive pre-sales services for enterprise accounts by positioning and selling Samsara professional services, scoping and producing SOWs, owning services ARR attach quota, forecasting pipeline, and partnering with Sales, Sales Engineering, and Customer Success through implementation and executive engagement.
Top Skills: Salesforce (Sfdc)

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account