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.
Scientific Games is looking for a senior hands-on leader to build and run a centralized AI-enabled process re-engineering capability.
This leader will help SG improve important work across a focused portfolio of high-value domains. Early areas may include RFP processing, IT / DevOps / integration, software engineering, game art and design, data science, and shared service operations. The role starts with business outcomes and process diagnosis, then moves into workflow redesign, AI-enabled pilots, evaluation, adoption, and scale.
The right person will be strong at understanding how work actually happens. They will be able to sit with teams, map the value chain, identify bottlenecks, clarify decision points, and redesign workflows. They will also understand modern AI well enough to decide when to use retrieval, drafting, summarization, orchestration, review support, simulation, or bounded agentic execution.
This is a senior leadership role with hands-on expectations. The person should be able to operate as a high-impact individual contributor, build a small team, coordinate domain sponsors, direct TPM support, manage external partners where useful, and create reusable methods for SG.
Success will be measured by improved business outcomes, stronger workflows, reusable methods, safer AI adoption, and measurable gains in selected high-value processes.
Core Responsibilities
Build SG’s method for AI-enabled process re-engineering.
Select and shape high-value opportunities with executive sponsors.
Lead current-state diagnostics, constraint analysis, and target workflow design.
Determine where AI should support retrieval, drafting, orchestration, review, decision support, or bounded execution.
Lead controlled pilots with baselines, evaluation plans, human review models, and rollout criteria.
Create reusable templates, governance patterns, architecture patterns, and playbooks.
Partner with leaders across product, engineering, IT, data science, creative, sales, finance, legal, and operations.
Select and manage external partners where they accelerate the work or add specialized capability.
Communicate progress, risks, decisions, and results clearly to senior leadership.
Experience that Fits
The role should require substantial experience across process improvement, operations, product, engineering, consulting, AI transformation, or enterprise technology. A reasonable target is 12+ years, with evidence of leading cross-functional change and delivering measurable results.
The person should understand value-stream thinking, bottleneck analysis, workflow redesign, operating model change, and adoption. They should be credible with modern AI concepts including LLMs, retrieval, agentic workflows, orchestration, human-in-the-loop design, evaluation, observability, and guardrails. They do not need to be the deepest engineer in the room, but they must be technical enough to challenge architecture, vendor claims, and implementation plans.
They should be able to write clearly. This matters because the work will involve ambiguous problems, cross-functional decisions, and senior stakeholders. A leader who cannot turn complexity into clear language will struggle to create alignment.
Candidate Profile
The strongest candidate will probably come from one of several backgrounds.
One possible profile is a senior process transformation leader who has modern AI depth. This person may have led operational excellence, business process re-engineering, product operations, or enterprise transformation work and has learned how to apply LLMs, agents, workflow automation, and AI evaluation in real systems.
Another possible profile is an AI product / solution leader with deep business process instincts. This person may have built AI-enabled workflows, internal platforms, or agentic systems and has enough operating experience to avoid tool-first thinking.
A third possible profile is a senior consultant or former consultant who has led practical transformation work and can operate inside a company with accountability for outcomes. This person should be willing to own results, not only recommendations.
Across backgrounds, the required traits are the same: clear thinking, curiosity about work, strong writing, practical AI fluency, process discipline, executive influence, comfort with ambiguity, and the ability to turn messy problems into operating plans.
First-Year Success Profile
By the end of the first year, the right leader should have established SG’s method for AI-enabled process re-engineering, completed serious diagnostics in the first-wave domains, launched controlled pilots with baselines and evaluation plans, delivered at least one measurable improvement in a high-value workflow, and created reusable templates and governance patterns.
The best evidence of success will be that SG leaders start bringing better-framed problems to the team. Instead of asking for a bot, they should begin asking where the constraint sits, how the workflow should change, and what role AI should play.
Physical Requirements
The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. While performing the duties of this job, the employee is regularly required to sit, stand, walk, bend, use hands, operate a computer, and have specific vision abilities to include close and distance vision, and ability to adjust focus working with computer and business equipment.
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.
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.