Our Company

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.

What You’ll Do

As an AI Engineer, you will be a key contributor to our internal engineering AI initiatives, designing and building agent-based AI solutions that significantly enhance developer productivity across the organization. You will work on AI agents and platforms across Software Development Lifecycle and design them to be scalable, reusable, and marketplace-ready for broader adoption.

You will operate in a technically deep, fast-paced environment, collaborating closely with platform, product, and engineering teams to shape the future of our developer-facing AI capabilities.

In this role, you will:

• Design, build, and evolve AI-powered agents that automate, accelerate, and improve software development workflows such as coding, testing, debugging, documentation, and operational tasks.
• Develop production-grade systems and services with a strong focus on scalability, reliability, performance, and secure multi-tenant design suitable for internal platforms and external AI marketplaces.
• Collaborate with internal engineering teams and product partners to identify high-impact developer productivity use cases and translate them into well-designed agentic solutions.
• Build and integrate APIs, SDKs, and services that enable seamless adoption of AI agents across developer tools, CI/CD pipelines, and engineering platforms.
• Apply advanced AI/ML techniques, including large language models (LLMs), agentic architectures, prompt engineering, tool/function calling, retrieval-augmented generation (RAG), and workflow orchestration.
• Design agents with reuse and commercialization in mind, ensuring they meet quality, security, observability, and compliance standards required for inclusion in an AI Marketplace.
• Leverage AI-powered engineering tools to improve development velocity, code quality, and overall engineering effectiveness.
• Optimize system performance and cost, identifying bottlenecks across models, inference pipelines, data access, and infrastructure.
• Write high-quality, testable code, including unit, integration, and agent behavior tests, and actively participate in code and design reviews.
• Support and mentor engineers, sharing best practices in AI engineering, agent design, and production deployment.
• Troubleshoot and resolve production issues, ensuring reliability and continuous improvement of AI-powered systems.
• Stay current with emerging trends in AI agents, developer productivity tooling, LLM ecosystems, and cloud-native architectures, and apply them pragmatically to real-world engineering problems.

Who You’ll Work With

You will be part of an internal engineering team building AI-powered agents and platforms that improve developer productivity. You’ll collaborate closely with software engineers, AI/ML specialists, platform and DevEx teams, as well as product and marketplace partners, to deliver scalable, reusable AI solutions that can be adopted internally and offered through the AI Marketplace.

What Makes You a Qualified Candidate

(Nonnegotiable qualifications)

• Bachelor’s degree in Computer Science or equivalent from a recognized institution.
• 2+ years of experience in backend services, distributed systems, or data platform development.
• Strong proficiency in Java, Go, or Python for service development.
• Good understanding of design principles, distributed system patterns and service framework.
• Hands-on experience designing and developing RESTful APIs.
• Experience with SQL and/or NoSQL databases and data modelling.
• Strong debugging, problem solving, and troubleshooting skills.
• Experience with modern containerization and orchestration tools such as Kubernetes.
• Knowledge of public cloud platforms.
• Experience with AI productivity tools (e.g., GitHub Copilot).
• Ability to work independently, and deliver high quality outcomes.
• Strong communication and collaboration skills.

What You’ll Bring

(Preferred qualifications)

• Familiarity with messaging systems such as Kafka.
• Experience experimenting with or implementing AI/ML technologies, Agentic AI, or LLMs.
• Familiarity with engineering best practices.
• A proactive mindset and comfort working in fast paced, dynamic environments.
• Curiosity, adaptability, and a passion for building impactful AI-driven products.

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