Senior Manager, Artificial Intelligence Engineering

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.

We are looking for a Senior Manager – AI Platform to lead the development and evolution of our next-generation platform powering autonomous, AI-driven agents. This role is ideal for a leader who combines data science expertise and technical depth ,
agentic platform thinking , and strategic execution to scale a distributed system that enables reasoning, planning, memory, and tool use at runtime.

As the Senior Manager, you will be responsible for driving product and data science strategy, overseeing a multidisciplinary team of engineers and data scientists, collaborating with AI/ML research and product teams, and ensuring that the AI Platform is performant, extensible, and production-ready.

• Lead the engineering and data science roadmap for the AI Platform, ensuring architectural scalability, reliability, and seamless integration with LLMs, data science pipelines.

• Partner with product, data science, research, and engineering teams to define requirements for capabilities such as predictive modeling, memory, planning, multi-agent collaboration, and tool orchestration.

• Drive the design and implementation of core platform services including API gateways, vector store integrations, RAG pipelines, and data science experimentation frameworks.

• Oversee integrations with third-party tools, internal data science services, and infrastructure platforms to enable real-world agent execution and model deployment at scale.

• Guide the team in applying best practices in cloud-native development, distributed computing, observability, and security.

• Manage, mentor, and grow a high-performing team of backend engineers, data scientists, and AI platform specialists.

• Ensure alignment between platform capabilities and evolving needs from AI product lines and downstream applications.

• Drive technical excellence through code and design reviews, system reliability practices, and collaboration across engineering functions.

• Contribute to the long-term vision and strategy of how agentic workflows, powered by data science and machine learning, will operate at scale across the organization.

• 12+ years of experience in software/platform engineering or data science, with 3+ years in engineering management or technical leadership roles overseeing AI-driven initiatives.

• Proven experience building and scaling distributed systems or cloud platforms in production environments.

• Strong technical background in backend development, APIs, infrastructure, or platform architecture.

• Hands-on experience with AI/ML platforms, LLM integrations, and demonstrated background in data science methodologies including model development, evaluation, and deployment.

• Proven experience working with vector databases, semantic search, feature stores, and end-to-end data science pipelines in production environments.

• Strong project management skills, with a track record of delivering large cross-functional initiatives.

• Excellent communication and collaboration skills, with the ability to work closely with executive stakeholders, researchers, and engineers.

• Passion for building platforms that enable intelligent, autonomous behavior at scale.

• A strong track record of leading platform engineering and data science teams that build scalable, reliable systems supporting internal and external developers or AI/ML workloads.

• Deep understanding of software architecture , distributed systems, and cloud-native infrastructure — with the ability to make strategic technical decisions.

• Experience working at the intersection of AI, data science, and engineering , ideally supporting LLM-based products, AI agents, or data science platforms that deliver measurable business value.

• A pragmatic approach to balancing technical depth with delivery speed , especially in fast-paced, R&D-heavy environments.

• Demonstrated ability to hire, mentor, and retain high-performing engineers while fostering a culture of ownership, experimentation, and accountability.

• Strong…