AI specialist II at Coursera (India), building hands-on LLM and GenAI pipelines for the combined Coursera-Udemy platform.

This full-time India role was posted on 28 September 2026. The listing seeks a deeply technical, hands-on specialist with experience building AI pipelines using modern LLM and GenAI systems. Requirements include experience with generative AI platforms and ecosystems such as Vertex AI, Bedrock, Azure AI, OpenAI or Anthropic APIs, and experience designing RAG, vector search, tool-calling, MCP, agent orchestration or multi-step AI workflows and LLM gateways.

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 requirement list is a precise map of current applied-GenAI practice - RAG, tool-calling, MCP, orchestration, gateways - which means the team builds production AI features, not experiments, and will probe real experience with each pattern it names. Specialist rather than generalist software engineer: the role goes deep on AI systems within a product organisation at very large learner scale.

The team and the work

Per the listing, the work serves the combined Coursera-Udemy platform (300 million+ learners), so the pipelines you build operate at consumer scale where cost and latency discipline matter.

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:

Experience with Generative AI platforms and ecosystems such as Vertex AI, Bedrock, Azure AI, OpenAI/Anthropic APIs, Hugging Face , LangGraph, LangChain or equivalent technologies.
Experience designing RAG, vector search, tool-calling, MCP, agent orchestration, or multi-step AI workflows and LLM gateways .
Experience with AI evaluation techniques such as golden datasets, LLM-as-judge, regression evaluation, human evaluation, ranking metrics, or automated quality frameworks .
Experience working with modern data platforms such as Databricks, BigQuery, Snowflake, Spark, or equivalent technologies .
Familiarity with AI observability, model monitoring, responsible AI, PII handling, prompt injection mitigation, and AI guardrails.
For more information about how Coursera collects and uses your personal information, please see our Coursera + Udemy Global Applicant Privacy Notice .
To protect against recruitment fraud, Coursera + Udemy recruiters only communicate via official coursera.org/udemy.com email addresses and never through personal accounts. We do not accept...
If you encounter suspicious recruitment activity, please report it via our Fraudulent Activity Submission Form.

Who this role suits

Engineers with hands-on production experience across LLM platforms and RAG/agent patterns. Not for ML engineers whose experience is classical modeling, or engineers whose GenAI work is prototype-level - the listing expects production systems.

Practical notes

For applied GenAI roles, expect design questions on a RAG or agent system: retrieval quality, evaluation, latency, cost. Have one production AI pipeline you can walk through end to end.

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: AI Specialist II at Coursera. We found this listing on the Greenhouse public job board (job-boards.greenhouse.io), where it was posted on 28 Sep 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.

Related openings on GetFirstJob

If this role is not the right fit, these current openings are in a similar area:

We write and maintain this page from the employer's public listing and link straight to their application page. We do not act as a recruiter, and applying is always free. If the link above stops working, the role has likely been filled.

This is our short summary of the employer's listing. The full description, eligibility and deadline are on the employer's page.