Senior Manager, AI Engineering

Senior Manager of AI Engineering

Bangalore/Hyderabad (hybrid)

Solid product experience and an educational background from Tier‑1 or Tier‑2 universities are preferred.

Exp Level - 14+ years

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 the Senior Manager of AI Engineering for Teradata's AI Cloud Infrastructure products, you will lead the planning, development, and delivery of a scalable platform that enables customers to discover, use, and deploy AI cloud products. Your work will influence the full cloud and product lifecycle.

In this role, you will guide engineering teams, including Senior Staff Engineers. You will shape the product vision, drive technical excellence, and create an environment that fosters innovation, quality, and continuous improvement.

You will play a key role in defining architecture, building high quality distributed systems, and ensuring smooth delivery across the full engineering lifecycle. You will partner closely across functions to deliver customer centric outcomes with predictable execution and high standards of reliability, performance, and security.

Who You'll Work With -

You will collaborate with engineering, product management, design, security, cloud operations, and other cross functional partners to deliver end to end AI cloud product capabilities. You will report to a senior engineering leader and work closely with stakeholders across the company to prioritize work, align on strategy, and drive successful product adoption.

What Makes You a Qualified Candidate -

• Bachelor's degree in Computer Science or equivalent from a recognized institution.
• Typically 14+ years of engineering experience with at least 2 years leading multiple teams and senior level engineering talent.
• Strong background in building and operating cloud native or on-prem infrastructure, large scale distributed systems, services, or applications supporting multi cloud deployments.
• Deep hands-on expertise with public cloud providers such as AWS, Azure, or GCP, cloud APIs and SDKs, and infrastructure components such as VPC/VNet, API gateways, storage and compute.
• Mastery of virtualization/container orchestration technologies like Kubernetes, Istio and Docker.
• Advanced proficiency in automation tools like Terraform and Helm.
• Experience with configuration management tools like Chef or Puppet.
• Strong proficiency in languages like Python, Go, and Bash for services development and scripting.
• Familiarity with CI/CD pipelines and tools such as Jenkins, GitHub Actions and ArgoCD.
• Familiarity with security, compliance, IAM and observability.
• Solid understanding of system design, architecture principles, UI frameworks, and API driven ecosystems.
• Proficiency with backend service technologies, RESTful API development, and modern engineering best practices.
• Experience with data systems (SQL/NoSQL) and UI technologies.
• Familiarity with AI/ML ecosystems, including large language models, agentic AI, and AI productivity tools.
• Strong problem solving abilities and familiarity with SDLC and production operations.
• Ability to partner across teams, influence diverse stakeholders, and operate effectively in dynamic or ambiguous situations.
• Excellent communication and collaboration skills.
• Commitment to fostering a healthy, inclusive team culture focused on quality, accountability, and continuous learning.

What You'll Bring -

(Preferred qualifications)

• Familiarity with cloud infrastructure KPIs and cost optimization.
• Experience with messaging systems such as Kafka.
• Experience experimenting with or implementing AI/ML technologies, Agentic AI, or LLMs.
• A track record of influencing infrastructure architecture decisions and driving engineering best practices.
• The ability to mentor engineers and guide them through design, planning, and execution.
• A proactive mindset and comfort working in fast paced, dynamic environments.
• Curiosity, adaptability, and a passion for building impactful AI-driven products.