Top Tech Jobs & Startup Jobs in Austin, TX

The Digital Account Manager builds relationships with lottery customers, enhances player engagement, oversees loyalty programs, and manages financial performance and operational efficiency.

The PostgreSQL Database Administrator will manage large-scale databases, perform operational activities, implement best practices, and ensure security and performance. They will support production databases and collaborate with teams for documentation and reporting.

Support and operate customer-facing iLottery and loyalty platforms with focus on Kubernetes (on-prem and cloud), GitOps-driven CI/CD (ArgoCD), container management, observability (Graylog, New Relic, ELK, Prometheus/Grafana), infrastructure automation (Ansible, Terraform), incident response, SLOs, capacity/resiliency planning, security remediation, documentation, and 24x7 on-call support.

The Managing Director will oversee P&L accountability, drive growth strategies, manage client relationships, and lead sales cycles for Scientific Games' lottery and sports betting products.

The Managing Director drives strategic success across the lottery jurisdiction with full P&L accountability, develops account plans, manages client relationships, and ensures project delivery while maximizing profitability and growth.

Build, operate, and modernize scalable data pipelines and warehouse environments for lottery reporting, analytics, and AI readiness. Improve ingestion, transformations, data models, contracts, observability, lineage, and onboarding patterns. Automate operations, troubleshoot production issues, mentor engineers, and support migration from legacy to cloud architectures while ensuring data quality, reliability, and regulatory continuity.

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.

Build and run a centralized AI-enabled process re-engineering capability: diagnose current workflows, design AI-assisted solutions (retrieval, drafting, agents, orchestration), run controlled pilots with evaluation and human review, create reusable playbooks/governance, partner cross-functionally, manage vendors and TPMs, and deliver measurable business outcome improvements.

Lead a small engineering team to turn ambiguous opportunities into production software quickly and safely. Establish AI-first development, specification-driven practices, strong automated testing, CI/CD, observability, and production ownership while improving legacy systems and influencing enterprise engineering practices.