Manager, Software Engineering

Teradata; Hyderabad; On-site; INR 4,500,000 - 7,500,000; Full time

Job summary

Teradata is seeking a Manager of Engineering for its Knowledge Platform to lead AI-powered platform capabilities and a team of engineers. The role focuses on delivering scalable, secure enterprise features across hybrid cloud environments.

You will drive architecture, mentor managers, and partner with product, security, and cloud teams to ensure reliable, production-grade AI solutions. Strong leadership and communication are essential.

Qualifications

• 8+ years in software engineering, with at least 5+ years leading engineering teams and managers.
• Experience integrating AI/ML, generative AI, or agentic AI 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.
• Strong 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.

Responsibilities

• Lead engineering teams responsible for building and delivering core agentic AI-powered platform capabilities.
• Drive execution of the technical roadmap, ensure engineering excellence, and partner with Product Management and Architecture.
• Mentor engineering managers, technical leads, and senior engineers to maximize team effectiveness.
• Oversee delivery of scalable, secure, and reliable AI-driven solutions across Teradata's Knowledge Platform.
• Collaborate with Security, Product, Architecture, R&D, SRE, and Cloud Operations for reliability and governance.
• Communicate technical strategy, progress, and risks to senior leadership.

Skills

AI/ML integration

Hybrid & multi-cloud

Microservices architecture

APIs/Observability/DevOps

Leadership of engineering teams

Education

Bachelor's or Master's degree in Computer Science/Engineering

Tools

Kubernetes

AWS/Azure/GCP

DevOps tooling

Job description

At Teradata, we believe that people thrive when empowered with better information. 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.

What You'll Do

• 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.

Key Responsibilities

Organizational & People Leadership

• Lead, mentor, and develop multiple engineering teams spanning platform engineering, AI/ML, and distributed systems.
• Build and scale high-performing teams; attract, retain, and grow top technical talent in agentic AI, developer platforms, and cloud infrastructure.
• Establish a culture of innovation, accountability, and continuous improvement.
• 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.

Technical & Strategic Leadership

• 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.
• Partner with knowledge modeling teams to industrialize proof-of-concepts into highly reliable, scalable, and secure enterprise features.
• 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.)
• Good statistical knowledge
• Champion engineering excellence in reliability, observability, automation, and platform scalability.

Cross-Functional Leadership

• 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.

What Makes You a Qualified Candidate

Required Experience

• 8+ years in software engineering with at least 5+ years leading engineering teams and managers.
• 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.
• Strong 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.

What You Will Bring

• Ability to lead managers and senior technical contributors while fostering a high-performance culture.
• Strong systems-thinking mindset coupled with a pragmatic, execution-focused approach to solving technical challenges.
• Deep understanding of platform reliability, scalability, performance, and AI platform governance.
• Excellent communication skills with the ability to influence senior leadership and cross-functional stakeholders.
• Passion for building AI-native enterprise platforms and driving innovation at scale.