Enterprise agentic AI architect at Coursera (India), owning the core architecture for AI agents across the combined Coursera-Udemy company.

This full-time India role was posted on 14 October 2026. The listing states that Coursera's AI adoption has moved fast - engineering teams code AI-first, dozens of internal tools have shipped - and that this role owns the foundation: the Senior Agentic AI Architect Lead designs and builds the core architecture for the company's AI agents. Requirements include 12+ years of experience with clear progression from engineer to senior/staff engineer to architect leader, and hands-on experience with agentic AI frameworks and orchestration such as LangGraph or comparable tools.

About Coursera

Coursera is an online learning platform offering courses and credentials from universities and companies. Per its current listings, Coursera and Udemy are now one company, together serving more than 300 million learners and 12,000+ enterprise customers.

The combined company hires in India across engineering and AI roles, with current listings describing work on AI agent platforms for learning and enterprise experiences. Learn more on Coursera's website.

The role in plain terms

The listing's framing - adoption already happened, now the foundation needs an owner - describes an architecture consolidation role: making dozens of shipped experiments coherent, governed and reusable. The 12+ year bar with explicit progression to architect leader sets a genuine principal-plus level. Hands-on agentic framework experience (LangGraph or comparable) is required, which filters out pure strategists: this architect still builds.

The team and the work

Per the listing, the company context is the combined Coursera-Udemy organisation serving 300 million+ learners and 12,000+ enterprise customers, so agent architecture decisions carry unusual scale across both consumer learning and enterprise products.

What the employer asks for

These requirements are quoted from the employer's listing, kept in their exact words so eligibility details are not distorted:

12+ years of experience with clear progression from engineer to senior/staff engineer to architect leader, including ownership of platforms or infrastructure used by multiple teams—not...
Hands-on experience with agentic AI frameworks and orchestration (e.g., LangGraph or comparable) and familiarity with Model Context Protocol (MCP) or similar standards for connecting AI...
Experience designing agent harnesses, evaluation frameworks, guardrails, testing, observability, and failure recovery for production AI systems.
Practical experience with enterprise context architecture, RAG, semantic search, or structured data access.
Practical experience with LLM cost and performance engineering—prompt caching, model routing, token economics—with quantifiable results.
AI security fundamentals, including access control, data isolation, prompt injection defense, and secure tool execution.
CI/CD, cloud infrastructure, APIs, and production operations experience.
Experience defining enterprise AI architecture, reusable platform patterns, operating models, or governance standards across multiple teams.

Who this role suits

Architect-level engineers with 12+ years, hands-on agentic AI framework experience, and a record of setting technical direction across teams. Not for senior engineers without architect-level leadership or for architects without current hands-on AI depth.

Practical notes

For agentic architecture roles, expect deep questions on orchestration patterns, context management, evaluation and governance of agents, plus how you would consolidate existing fragmented AI efforts. Current fluency in frameworks like LangGraph is a stated requirement - prepare specifically.

Working at Coursera

Engineering at Coursera covers the learning platform, enterprise products, and newer AI agentic systems described in its listings.

How to apply

Apply directly on the employer's site: Enterprise Agentic AI Architect at Coursera. We found this listing on the Greenhouse public job board (job-boards.greenhouse.io), where it was posted on 14 Oct 2026 and was still open when we checked on 30 Oct 2026. Before applying, re-read the employer's own description in full, since eligibility details, deadlines and process steps can change at any time and the employer's page is always the final word. Tailor your resume to the specific requirements above rather than sending a generic one: mirror the skills and tools the listing names where you genuinely have them. A short, specific note on why this team and this problem interest you goes further than a long generic cover letter. Never pay a fee to apply or interview; genuine employers, including this one, do not charge candidates.

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