Manager, Engineering - Context Engine Our Company:

Teradata Autonomous Knowledge Platform activates enterprise intelligence by unifying data, knowledge and business context to achieve tangible outcomes. With Teradata, organizations can provide agents with full context for impact when it matters. Our solution lets businesses connect and scale on premises, in the cloud, or through a hybrid approach. Teradata delivers real business value with AI.

As the Manager of Engineering for Teradata's Knowledge Platform, you will lead engineering teams responsible for building and delivering core agentic AI-powered platform capabilities. You will drive execution of the technical roadmap, ensure engineering excellence, and partner closely with Product Management, Architecture, and cross-functional stakeholders to deliver scalable, secure, and reliable AI-driven solutions.

You will play a key role in transforming innovative AI concepts into production-ready platform capabilities while building and mentoring high-performing engineering teams that support Teradata's next generation of autonomous and knowledge-driven products.

Lead, mentor, and develop multiple engineering teams spanning platform engineering, AI/ML, and distributed systems.

attract, retain, and grow top technical talent in agentic AI, developer platforms, and cloud infrastructure.

Drive organizational clarity, resource planning, and cross-functional alignment across engineering, product, and platform teams.

Coach engineering managers, technical leads, and senior engineers to maximize team effectiveness.

Lead execution of the architecture strategy for Teradata's autonomous, knowledge, and agentic AI platform capabilities.

Oversee delivery of production-grade agentic AI functionality across the Knowledge & Data Platform.

Guide teams build core frameworks and services that embed agentic AI into Teradata's product portfolio.





Drive technical evaluation and adoption of technologies related to knowledge graphs, LLM orchestration, AI agents, and AI-native developer experiences.

Proven knowledge and experience with the entire AI (Machine Learning, Deep Learning, Reinforcement Learning, LLM, etc.)

Champion engineering excellence in reliability, observability, automation, and platform scalability.

Work closely with Security Engineering to ensure AI-driven capabilities meet enterprise-grade compliance and governance requirements.

Partner with Product Management to translate customer needs into differentiated AI and analytics platform capabilities.

Collaborate with Architecture, R&D;, SRE, and Cloud Operations teams to improve reliability, performance, and developer productivity.

Communicate technical strategy, execution progress, and risks to senior leadership stakeholders.

Required Experience

- 8+ years in software engineering with at least 5+ years leading engineering teams and managers.
- Proven track record delivering complex distributed systems, cloud-native platforms, or large-scale data platforms.
- Demonstrated experience integrating AI/ML, generative AI, or agentic AI technologies into enterprise-grade products.
- Expertise in hybrid and multi-cloud architectures across AWS, Azure, and/or GCP.
- Experience modernizing applications into microservices and Kubernetes-based deployment environments.
- Solid understanding of APIs, streaming systems, observability, DevOps practices, and production-grade AI inference pipelines.
- Bachelor's or Master's degree in Computer Science, Engineering, or related field.

Ability to lead managers and senior technical contributors while fostering a high-performance culture.

Deep understanding of platform reliability, scalability, performance, and AI platform governance.

Passion for building AI-native enterprise platforms and driving innovation at scale.

📌 Manager, Software Engineering (ML) (Secunderabad)
🏢 Teradata
📍 Secunderabad