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.

Ignite the Future of AI at Teradata!

Location: Hybrid – Hyderabad, India

Teradata is building the next generation of AI-native enterprise platform, where autonomous agents don't just assist — they reason, plan, act, and learn. We are looking for a Senior Agentic AI Engineer to lead the design and development of production-grade agentic systems: multi-agent pipelines, memory and context management, agent evaluation infrastructure, and the governance framework that makes autonomous AI safe at enterprise scale.

This role is ideal for an engineer who operates at the frontier of LLM capabilities, understands how to harden agents for real-world enterprise workloads, and cares deeply about building systems that are not only capable but trustworthy and measurable.

Develop planning and reasoning frameworks (React, chain-of-thought, tree-of-thought) and integrate them with enterprise workflows.

Implement tool-calling pipelines and dynamic function invocation with schema validation and error recovery.

Design end-to-end agent evaluation frameworks: task taxonomies, success criteria, ground-truth datasets, and multi-dimensional scoring across task completion, tool accuracy, reasoning quality, safety, and cost.

Implement LLM-as-judge scoring systems with calibrated rubrics, inter-rater reliability checks, and human-in-the-loop validation.

Build trajectory-level evaluation tooling to analyze full agent execution traces — tool call sequences, intermediate reasoning steps, and decision points — not just final outputs.

Instrument evaluation pipelines with cost, latency, and quality dashboards; Context Management & LLM Memory

Build multi-tier LLM memory architectures:

Optimize prompt assembly pipelines that dynamically compose context from multiple memory tiers under token budget constraints.

Build document generation and file-handling skills covering DOCX, PPTX, XLSX, and PDF, with programmatic layout control, template rendering, and format-aware extraction for heterogeneous input types.

Create frontend artifact generation skills for producing interactive HTML/React components, data visualizations,



and UI prototypes as structured agent outputs.

Integrate skills with the Model Context Protocol (MCP) and establish skill authoring standards — versioning, deprecation policies, and evaluation harnesses — that ensure reliable agent-to-skill routing at scale.

Vibe Coding & AI-Accelerated Development

Leverage AI coding assistants (Claude Code, GitHub Copilot, Cursor, or equivalent) as primary development tools — collaborative pair programmers for architecture, implementation, and debugging, not just autocomplete.

Translate high-level intent into production-quality code through natural-language-driven development loops, maintaining engineering rigor while dramatically compressing cycle time.

Build and curate prompt libraries and system prompts that reliably steer AI assistants toward enterprise-grade output: typed, tested, documented, and security-conscious.

Maintain sharp critical judgment over AI-generated code — catching logic errors, security gaps, and architectural drift — and set team norms for code review, testing, and documentation at AI-assisted scale.

Build document generation and file-handling skills covering DOCX, PPTX, XLSX, and PDF, with programmatic layout control, template rendering, and format-aware extraction for heterogeneous input types.

Create frontend artifact generation skills for producing interactive HTML/React components, data visualizations, and UI prototypes as structured agent outputs.

Integrate skills with the Model Context Protocol (MCP) and establish skill authoring standards — versioning, deprecation policies, and evaluation harnesses — that ensure reliable agent-to-skill routing at scale.

Vibe Coding & AI-Accelerated Development

Leverage AI coding assistants (Claude Code, GitHub Copilot, Cursor, or equivalent) as primary development tools — collaborative pair programmers for architecture, implementation, and debugging, not just autocomplete.

Translate high-level intent into production-quality code through natural-language-driven development loops, maintaining engineering rigor while dramatically compressing cycle time.





Build and curate prompt libraries and system prompts that reliably steer AI assistants toward enterprise-grade output: typed, tested, documented, and security-conscious.

Maintain sharp critical judgment over AI-generated code — catching logic errors, security gaps, and architectural drift — and set team norms for code review, testing, and documentation at AI-assisted scale.

You'll collaborate with AI architects, ML engineers, platform engineers, and domain experts across Teradata's global AI team, including deep technical partnerships with Silicon Valley research and product leadership.

Product and UX to translate enterprise use cases into agent behaviors that are both powerful and intuitive.

Security and compliance teams to ensure every agent deployment meets enterprise governance standards.

BS/MS/PhD in Computer Science, AI/ML, or a related field.

- 5+ years of software engineering experience, with 2+ years focused on LLM or agentic systems.
- Hands-on experience building and deploying production agentic systems (not just prototypes).
- Proficiency in Python with strong fundamentals in typing, testing, and observability.
- Experience publishing or implementing research on agent evaluation, reasoning, or memory-augmented LLMs.

Experience with model serving infrastructure (vLLM, TGI, Triton) and quantization techniques.

Exposure to enterprise observability stacks (OpenTelemetry, Datadog, Prometheus/Grafana).

Experience designing systems for regulated industries (financial services, healthcare) with compliance constraints.

Familiarity with multi-modal agents (vision, structured data, voice).

Contributions to open-source agentic or LLM evaluation ecosystem projects.

Experience with cloud AI platforms (AWS SageMaker, Azure ML, GCP Vertex AI).

Portfolio of projects built primarily through AI-assisted development, demonstrating velocity, code quality, and critical review practices.

We embrace a versatile work model because we trust our people to make decisions about how, when, and where they work. We are an anti-racist company because our dedication to Diversity, Equity, and Inclusion is more than a statement. We do not discriminate based upon race, color, ancestry, religion, creed, sex (including pregnancy, childbirth, breastfeeding, or related conditions), national origin, sexual orientation, age, citizenship, marital status, disability, medical condition, genetic information, gender identity or expression, military and veteran status, or any other legally protected status.

📌 Senior AI Programmer (Hybrid) (India)
🏢 Teradata
📍 India