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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. You will work with Vantage Cloud Platform Engineering team, you’ll design and implement services that use AI and data-driven insights to manage, optimize, and scale infrastructure across Google Cloud, AWS, and Azure. You’ll work in a fast-paced environment focused on innovation, automation, and reliability—contributing directly to Teradata’s next generation of self-managing cloud systems.
Job Responsibility:
Accountable for the design, development, and deployment of features, enhancements, bug-fixes, applications, and services for the Microsoft Azure and/or Amazon AWS Platform and/or Google Cloud Platform
Leverage agentic AI capabilities to automate routine development tasks, optimize workflows, and proactively identify areas for improvement across cloud engineering processes
Develop, debug code, and write unit and end-to-end test cases
Participate in team Scrum meetings and interact with various stakeholders
Maintain the level of reliability required from a high-volume, high-availability platform
Analyze and solve (complex) issues in existing and new code
Work with all development process contributors, e.g., Product Owners, Architects, Scrum Masters, Developers, and DevOps to establish and execute a flawless development process
Integrate AI-driven decision-making and autonomous agents to enhance CI/CD pipelines, improve resource allocation, and accelerate delivery timelines
Deliver first-class results by handling your tasks with enthusiasm and personal commitment
Apply Agile Software Engineering principles and DevOps model for continuous delivery
Ensure lifecycle management consists of documentation such as test cases, source code repositories, etc., that are actively used and maintained
Continuously explore and implement AI-based solutions for predictive maintenance, intelligent monitoring, and automated remediation of cloud infrastructure issues
Requirements:
Bachelor’s degree in computer science (or related field) or equivalent experience
8+ years of hands-on software development experience
Advanced understanding of developing highly available infrastructures in a cloud services environment, with either Amazon Web Services, Microsoft Azure, or Google Cloud Platform
Deep understanding of cloud concepts (regions, zones, VMs, containers, VPC, tenants, authentication/security, logging, RDS, shared model, etc.)
Experience developing Microservices architecture using RESTful Services and Ansible Scripts
Expertise with IP networking principles, DNS, certificate management, routing, and load balancing
Experience with Linux Operating System
Knowledge of modern web frameworks and tools (such as REST, Django, Flask, Angular, React, Backbone, Spring, etc.)
Demonstrable proficiency in at least one modern general-purpose programming language (Java, C++, Node.js, TypeScript, Go, Python)
Experience working with automated deployments and source code/configuration management tools (GitHub, AWS CloudFormation, Jenkins, Chef, Ansible, Puppet, Vagrant, Terraform, and similar)
Must be able to work cross-functionally with other internal and external partner organizations
Deep passion for quality and customer focus
Proven experience building services on at least one public cloud platform (AWS, Azure, or GCP)
Proficiency with SQL, relational data modeling, and basic database schema design
Excellent communicator – ability to discuss technical solutions with peers, Scrum Masters, Product Owners, etc.
Expertise in building cloud native products and services, leveraging agentic AI for autonomous optimisation and intelligent orchestration
Expertise in designing & building distributed systems
Expertise in software engineering best practices, including AI-assisted code analysis and automated quality checks
Expertise with Docker container related technologies like Kubernetes, Mesos etc
Expertise in all phases of product development lifecycle - Design, develop, test, release & maintenance
Experience with supporting mission critical, 24x7 systems
Nice to have:
Amazon AWS / Microsoft Azure / Google Cloud Platform-related certifications are a plus
Hands-on experience with Agentic AI frameworks for autonomous task execution, workflow optimisation, and intelligent orchestration in cloud environments
What we offer:
We prioritize a people-first culture
We embrace a flexible work model
We focus on well-being
We are an anti-racist company
dedicated to Diversity, Equity, and Inclusion
foster an equitable environment that celebrates people