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At Teradata, we believe that people thrive when empowered with better information. That’s why we built the most complete cloud analytics and data platform for AI. By delivering harmonized data, trusted AI, and faster innovation, we uplift and empower our customers—and our customers’ customers—to make better, more confident decisions. The world’s top companies across every major industry trust Teradata to improve business performance, enrich customer experiences, and fully integrate data across the enterprise.
Job Responsibility:
Design and build cloud-native platform and compute services used by self-service and AI-driven workloads
Develop backend services and APIs that enable provisioning, lifecycle management, and runtime orchestration of compute environments
Build control-plane systems for managing scale, upgrades, state, and lifecycle of distributed compute components
Implement workflow orchestration and stateful systems for complex, multi-step platform operations
Partner closely with product, AI/ML, and UI teams to deliver cohesive end-to-end user experiences
Apply distributed systems fundamentals to ensure systems are scalable, reliable, and resilient
Improve developer and consumer experience through clean APIs, well-defined contracts, and extensibility
Debug and resolve complex issues across platform services and compute subsystems
Contribute to technical design and architectural discussions shaping future platform capabilities
Requirements:
Strong experience building backend, platform, or infrastructure-aware software systems
Proficiency in Python, Java, Go, or similar backend languages
Experience designing and implementing distributed systems or platform services
Solid understanding of cloud computing concepts with hands-on experience in AWS, Azure, or GCP
Experience building service-based or RESTful APIs consumed by other teams or products
Ability to reason about scalability, state management, fault tolerance, and failure modes
Strong analytical and problem-solving skills with a product-oriented mindset
Bachelor’s degree in Computer Science, Engineering, or related field with 4+ years of industry experience
Advanced degree with 3+ years of experience
Nice to have:
Experience working on self-service platforms or product-led experiences
Experience supporting AI/ML workloads or data/analytics platforms
Familiarity with distributed compute systems
Experience with event-driven or workflow-based architectures
Experience building internal platforms used across multiple product teams