Our Company
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
At Teradata, we're not just managing data; we're unleashing its full potential. Our Teradata AI Studio platform and pioneering Enterprise Vector Store are empowering the world's largest enterprises to derive unprecedented value from their most complex data. We're rapidly pushing the boundaries of what's possible with Artificial Intelligence, especially in the exciting realm of autonomous and agentic systems
We’re building intelligent systems that go far beyond automation — they observe, reason, adapt, and drive complex decision-making across large-scale enterprise environments. As a member of our AI engineering team, you’ll play a critical role in designing and deploying advanced AI agents that integrate deeply with business operations, turning data into insight, action, and measurable outcomes.
In this role, you’ll architect foundational components for production-grade AI systems — from agent frameworks and LLM pipelines to observability and evaluation layers that ensure reliability, accountability, and performance. You’ll be responsible not just for building models, but for making them measurable, debuggable, and trustworthy in real-world, high-stakes deployments.
You’ll work alongside a high-caliber team of AI researchers, engineers, and data scientists tackling some of the hardest problems in AI and enterprise software — from scalable multi-agent coordination and fine-tuned LLM applications, to real-time monitoring, drift detection, and closed-loop retraining systems.
If you're passionate about building intelligent systems that are not only powerful but observable, resilient, and production-ready, this role offers the opportunity to shape the future of enterprise AI from the ground up.
Who You'll Work With
Imagine collaborating daily with some of the brightest minds in the company – individuals who champion diversity, equity, and inclusion as fundamental to our success. You'll be part of a cohesive force, laser-focused on delivering high-quality, critical, and highly visible AI/ML functionality within the Autonomous Knowledge Platform. Your insights will directly shape the future of our intelligent data solutions.
You'll report directly to the inspiring Sr. Manager, Software Engineering, who will champion your growth and empower your contributions.
What Makes You a Qualified Candidate
- We’re seeking a hands-on, deeply technical Staff Architect to lead innovation in the Agentic AI space.
- You bring proven experience in the design, development, and deployment of intelligent agents that can reason, plan, and act autonomously—and critically, you’ve done so securely and responsibly at scale.
- This role sits at the intersection of deep systems engineering, modern AI architectures, and the real-world operational challenges of deploying agents in enterprise environments.
- At Teradata, you will be at the forefront of implementing agent management, governance, and compliance, solving some of the most complex problems in building safe and scalable Agentic AI systems.
- You’ll work cross-functionally with product leaders, architects, and platform teams to define our next-generation agent platform.
- Architect, design, and implement secure, scalable frameworks for autonomous AI agents.
- Define and lead the technical roadmap for agent management—from discovery and provisioning to task orchestration and retirement.
- Ensure AI agents are secure by design, with visibility, accountability, and guardrails baked in.
- Collaborate with AI researchers, platform engineers, and product managers to bring cutting-edge agentic capabilities to production environments.
- Build foundational infrastructure and tools to support multi-agent collaboration, memory/context management, and extensibility.
- Drive adoption of AI agents across the enterprise by enabling easy integration and safe execution.
- Serve as a thought leader on best practices for agent safety, observability, performance, and ethical deployment.
What You Bring
- A Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field – your academic foundation is key.
- A genuine excitement for AI and large language models (LLMs) is a significant advantage – you'll be working at the cutting edge!
- 8+ years of experience in software architecture, backend systems, or AI infrastructure.
- Deep knowledge of autonomous agent frameworks (e.g., LangChain, AutoGen, CrewAI) and AI orchestration models.
- Experience with agent memory, planning loops, self-reflection, and execution chains.
- Proven ability to build systems that solve for access control, identity management, and policy enforcement in the context of AI agents.
- Proficiency with cloud-native platforms, distributed systems, and infrastructure design for scalability and security.
- Experience building SDKs or APIs that expose agentic capabilities to developers or downstream applications.
- Excellent collaboration and communication skills across technical and non-technical teams.
- Proven ability to lead projects across large, distributed teams.
- Strong knowledge of LLMs, RL, or cognitive architectures is highly desirable.
- Experience with vector DBs, graph-based memory systems, or agentic frameworks.
- Passion for building safe, human-aligned autonomous systems.
- Experience in software development (Python, Go, or Java is preferred).
- Familiarity with backend service development, APIs, and distributed systems.
- Interest or experience in LLMs, autonomous agents, or AI tooling.
- Familiar with CI/CD practices, testing, and observability.
- You're knowledgeable about open-source tools and technologies and know how to leverage and extend them to build innovative solutions.
- Passion for AI/ML, especially in building smart, agent-driven interfaces that feel human.
- Ownership mindset — you build, deploy, iterate, and scale with a long-term view.
- Bonus: Experience with knowledge graphs, graph-based identity modeling, or AI-native security analytics.
- Bonus: Familiarity with zero-trust architectures, AI governance frameworks, or secure multi-tenancy.
- Bonus: Contributions to open-source agent frameworks or LLM orchestration tooling.
- Bonus: Background in identity security, compliance-driven environments, or enterprise SaaS platforms.
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