Senior AI Engineer

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.

Responsibilities

Design and implement production-grade multi-agent architectures, including task decomposition, inter-agent communication, delegation, and coordination patterns; Build agentic harnesses: agent loop controllers, tool registries, execution sandboxes, and retry/fallback logic; 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 and LLM-as-judge scoring systems; Build trajectory-level evaluation tooling and red-teaming and adversarial harnesses; Design context window management systems and multi-tier LLM memory architectures; Implement memory indexing, lifecycle management, and privacy-respecting memory scoping across enterprise tenants; Design and implement reusable agent skills and document generation and file-handling skills (DOCX, PPTX, XLSX, PDF); Create frontend artifact generation skills for interactive HTML/React components and data visualizations; Integrate skills with the Model Context Protocol (MCP) and establish skill authoring standards; Use AI coding assistants as primary development tools and maintain critical judgment over AI-generated code; Collaborate with AI architects, ML engineers, platform engineers, product and UX, security and compliance, infrastructure, and customer success teams

Requirements

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; Familiarity with agent frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or equivalent

Nice to have

Experience publishing or implementing research on agent evaluation, reasoning, or memory-augmented LLMs; Familiarity with MLOps tooling (MLflow, Weights & Biases, DVC, or equivalent); 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); 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

Benefits

Flexible work model; Well-being focus; People-first culture; Inclusive environment