AI Engineer Jobs in Alpharetta, GA

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

What You'll Own

Finance Data Architecture. Partner with the data team and finance leadership to finish building out the finance domain of our central data warehouse. Define source-of-truth datasets, semantic models, and data contracts. Drive accuracy, freshness, and trust as non-negotiables.

In-House Dashboarding Platform. Lead the design, development, and ongoing maintenance of our homegrown HTML-based dashboarding tool. We're building in-house to keep costs low and retain full control over UX and AI integration. You'll set the technical direction, ship self-service dashboards that finance partners and executives actually use, and ensure every number ties out.

AI Coordination & Agent Design. Design the AI layer that turns our warehouse into a conversational, self-service experience. Spec and build AI agents that help users explore data, generate commentary, automate variance analysis, and answer ad-hoc finance questions. Own the prompts, the retrieval architecture, the evaluation framework, and the deployment pipeline.

Finance Hub & Forecasting Application. Build a new forecasting and budgeting hub in collaboration with operators and business owners. The application will support a structured workflow — input gathering, stage-gated review, approvals, and final commit — and memorialize every scenario in the data warehouse for full historical traceability. We'll take a hybrid build approach: a custom UI tailored to our processes, layered on top of an existing modeling engine.

Team Leadership. Manage and grow the inherited team. Coach, hire, and set the bar for both engineering rigor and finance fluency.

Cross-Functional Partnership. Work daily with the finance/FP&A team, the data/analytics engineering team, and the executive team. Translate ambiguous business questions into durable data products.

Who You Are

This role calls for a rare hybrid — someone equally comfortable in a data warehouse, a Python notebook, and an FP&A review meeting. We expect candidates to bring strength in at least two of the three areas below, with working knowledge of the third:

• Data & analytics engineering. You've built and maintained production data pipelines and semantic models. SQL is second nature.
• Finance / FP&A. You understand how a P&L is built, how forecasts are constructed, and how operators think about driver-based planning.
• Internal tool building. You've shipped internal finance or analytics tools — not just dashboards, but real applications people depend on.

Must-Have Skills

• Expert SQL and hands-on experience with a modern cloud data warehouse (Snowflake, BigQuery, Databricks, or equivalent)
• Strong Python and modern data modeling tooling (dbt or equivalent)
• Demonstrated experience building with AI/LLM tooling — APIs, agents, RAG architectures, evals
• Track record of designing, shipping, and operating internal data products or applications used by non-technical stakeholders
• People management experience and the ability to coach a team across the data/finance spectrum
• Strong written and verbal communication, especially in executive settings

Nice to Have

• Prior experience in an FP&A, strategic finance, or finance systems role
• Experience with forecasting / EPM platforms (Pigment, Anaplan, Cube, Workday Adaptive, etc.) as a build-on-top layer
• Front-end development experience (HTML/CSS/JavaScript) — relevant to our in-house dashboarding platform
• Experience standing up data governance, data contracts, or finance close automation

What Success Looks Like

• First 90 days: Establish trust with the finance, data, and executive teams. Audit the current state of the finance data layer, dashboarding tool, and forecasting process. Deliver a sequenced roadmap.
• First 6 months: Complete the finance domain of the data warehouse. Ship the first generation of AI-enabled self-service dashboards. Stand up the v1 of the forecasting hub for at least one business unit.
• First 12 months: Forecasting hub adopted company-wide with full stage-gating, approvals, and scenario memorialization in the warehouse. AI agents are a routine part of how finance and operators interact with data. Team is operating with clear ownership and a strong delivery cadence.

Qualifications

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.