Insight Global is seeking a Senior Software Engineer (AI Platform) to join the Infrastructure and Platform Services organization at a leading AAA game company. This team serves as the backbone of the company’s global ecosystem, enabling the creation of exceptional games and immersive player experiences.
The AI Platform team delivers centralized AI and Generative AI capabilities across all game franchises, providing shared infrastructure and tooling for data modeling, model training and fine‑tuning, inference, and agent development. The platform supports a modern, cloud‑native tech stack designed to scale across game development, marketing, sales, and live player experiences.
As a Senior Software Engineer, you will play a key role in architecting and building a scalable, production‑grade AI platform that supports live‑service games at global scale. You will report to the Engineering Director, AI Platform.
Key Responsibilities
Platform Architecture & DevelopmentLead the design and development of next‑generation AI platforms supporting the full AI lifecycle, including data ingestion, feature stores, model training and validation, deployment, monitoring, and feedback loops in a live‑service gaming environment.Architect scalable, secure, and high‑performance multi‑cloud platforms supporting real‑time analytics, low‑latency inference, and high availability.Production Integration & MLOpsOwn the integration of AI/ML solutions into real‑time production game environments.Partner closely with game engineers, ML engineers, data scientists, producers, and live‑ops teams to ensure reliable deployments, performance monitoring, rollback strategies, drift detection, and lifecycle management.Drive end‑to‑end automation, including MLOps CI/CD pipelines, model versioning, A/B testing, feature‑pipeline orchestration, and self‑service tooling for internal users.Standards, Reliability & GovernanceDefine and enforce platform‑wide standards for reliability, scalability, security, cost optimization, observability, and operational excellence.Establish governance practices aligned with industry best practices for AI and ML systems.Leadership & CollaborationMentor and guide junior engineers, providing technical leadership on architecture, cloud infrastructure, observability, and operating live systems.Partner with game studios, artists, data science, analytics, and live‑ops teams to translate business and gameplay challenges into AI platform solutions.Lead proof‑of‑concepts and pilots for reusable AI capabilities such as personalization, recommendations, generative content, player engagement, and anti‑cheat.Strategic ImpactAct as a bridge between game‑service priorities and platform delivery.Translate player experience and business requirements into platform features, clearly articulating trade‑offs across cost, latency, risk, and security to drive cross‑functional alignment.
Required Skills & Experience
Master’s degree (or equivalent) in Computer Science, AI, ML, or a related field, with 5+ years of professional experience in:AI/ML systemsPlatform or infrastructure developmentData and analytics platformsLive‑service or real‑time systemsStrong programming skills in Python, plus experience with at least one additional language (e.g., Java, C++, Go).Hands‑on experience with deep learning frameworks such as PyTorch, and exposure to Generative AI technologies (LLMs, diffusion models, agentic systems) in production.Proven experience building and operating cloud‑based, production‑grade ML platforms at scale.Expertise with major cloud providers (AWS, GCP, or Azure) and cloud‑native tooling, including:Infrastructure as code (Terraform, CloudFormation)Containers (Docker)Orchestration (Kubernetes)CI/CD pipelinesMonitoring, logging, and observabilityStrong experience deploying and operating ML models in real‑time or near‑real‑time environments.Demonstrated ability to deliver self‑service platform capabilities supporting developer productivity, governance, compliance, model monitoring, drift detection, and performance management.Excellent leadership and communication skills, with the ability to collaborate across engineering, data science, game development, product, and operations teams, and to present technical trade‑offs to non‑technical stakeholders.
Nice‑to‑Have Experience
Experience working in live‑service games or large‑scale real‑time entertainment platformsExperience building multi‑tenant or internal SaaS platformsHands‑on experience integrating Generative AI in games (e.g., procedural content, conversational NPCs, AI agents)Deep understanding of performance and latency trade‑offs in large‑scale gaming systemsExperience with change management or enabling partner teams to adopt AI platforms
