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 other teams to industrialize proof-of-concepts into highly reliable, scalable, and secure enterprise features.
Drive technical evaluation and adoption of technologies related to autonomous data platform, workload management, 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.)
Proven experience in engineering excellence
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
12+ 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.
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.
