1

Ai Game Developer Jobs in Georgia (NOW HIRING)

Working alongside our team of product managers and software developers, you will help design and ... This team believes that what we are doing is a game-changer in the industry * Coffee bar with cold ...

Showing results 41-60

Ai Game Developer information

See Georgia salary details

$27.4K

$91.6K

$152K

How much do ai game developer jobs pay per year?

As of Aug 9, 2026, the average yearly pay for ai game developer in Georgia is $91,591.00, according to ZipRecruiter salary data. Most workers in this role earn between $68,800.00 and $104,700.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an AI game developer?

To thrive as an AI Game Developer, you need a solid background in computer science, programming (especially Python, C++, or C#), machine learning, and game development principles—often supported by a relevant degree or portfolio. Experience with game engines like Unity or Unreal Engine, proficiency in AI libraries (such as TensorFlow or PyTorch), and knowledge of version control systems are typical requirements. Creativity, problem-solving, teamwork, and strong communication skills are important soft skills that set top candidates apart. These abilities enable developers to design engaging, intelligent gameplay experiences while collaborating effectively within multidisciplinary teams.

What is an AI game developer?

An AI Game Developer designs and implements artificial intelligence systems in video games to create intelligent, responsive, and adaptive behaviors for NPCs, enemies, and other in-game elements. They use machine learning, decision trees, behavior trees, and other AI techniques to enhance gameplay experiences. Their role involves coding AI logic, optimizing performance, and collaborating with designers and engineers to create immersive and dynamic game worlds.

What are some of the main challenges faced by AI game developers during the game development process?

AI Game Developers often encounter challenges related to balancing sophisticated artificial intelligence behaviors with real-time performance constraints and ensuring a fun player experience. Creating adaptive, believable non-player characters (NPCs) that enrich gameplay without overwhelming system resources can require ongoing iteration and optimization. Additionally, collaborating closely with designers, artists, and other programmers to integrate AI seamlessly into the game’s vision is a common aspect of the role. Overcoming these challenges not only enhances technical skills but also contributes to more dynamic and engaging games.

What are the most commonly searched types of Ai Game Developer jobs in Georgia? The most popular types of Ai Game Developer jobs in Georgia are:
Infographic showing various Ai Game Developer job openings in Georgia as of August 2026, with employment types broken down into 2% Internship, 78% Full Time, 9% Part Time, and 11% Contract. Highlights an 82% In-person, 3% Hybrid, and 15% Remote job distribution, with an average salary of $91,591 per year, or $44 per hour.

Senior Advanced Product Engineer

Scientific Games, LLC

Alpharetta, GA • On-site

$100 - $130/hr

Other

Re-posted 28 days ago


Scientific Games rating

8.3

Company rating: 8.3 out of 10

Based on 25 frontline employees who took The Breakroom Quiz

5th of 15 rated gambling companies


Job description

Scientific Games is the global leader in lottery games, sports betting and technology. From cutting‑edge backend systems to exciting entertainment experiences, we are 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 will deliver high‑quality software quickly, make sound technical decisions, and leave systems better than you found them.

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.
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.

Scientific Games, LLC and its affiliates (collectively, “SG”) are engaged in highly regulated gaming and lottery businesses. Certain SG employees may be required to obtain a gaming or other license, undergo background investigations, or meet specific regulatory standards as a condition to hiring and continued employment. SG requires all employees to meet the necessary requirements to fulfill their roles, as permitted by law.

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, or disability. If you’d like more information about your equal employment opportunity rights as an applicant under the law, please consult the EEOC poster.

#J-18808-Ljbffr

What Scientific Games employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom