At a glance
- Experience
- 4+ years experience
- Location
- India
About Coursera
- Coursera and Udemy are now one company, bringing together two mission-driven brands to create the world’s most powerful platform for turning learning into progress. Together, we help more than 300 million learners and 12,000+ enterprise customers build the skills they need for a world being reshaped by AI. Read more about the combined company by visiting our blog.
About the role
- We at Coursera are seeking a highly skilled and motivated AI Specialist, with strong hands on expertise in AI and data.
- This is a hands-on applied AI role for someone who enjoys figuring out how the system should think, not just how the application should be built.
Responsibilities
- Build and Design AI systems by selecting the right combination of data, including retrieval pipelines, agentic workflows with tool use, and structured extraction from unstructured sources
- Architect and implement Retrieval Augmented Generation (RAG) pipelines with vector databases (Pinecone, Weaviate) for grounded, context-aware AI applications.
- Build and maintain agentic AI workflows using frameworks such as Langgraph, Mastra, LlamaIndex, CrewAI, or AutoGen including multi-step tool use, planning, and autonomous execution loops.
- Design and run evaluation for every AI system you ship, covering accuracy, hallucination and grounding checks, regression suites, and human review loops
- Work with large-scale structured and unstructured datasets on cloud-native databases & storage (S3, Postgres, GCS, BigQuery, Databricks) with strong SQL and data modelling skills.
- Build rapid AI prototypes and experiment with different models, retrieval strategies, prompts, and approaches to find what works best.
- Partner with product managers, data engineers and backend/frontend engineers to translate business problems into well-scoped AI solutions with measurable KPIs.
- Document architectures, design decisions, runbooks, prompts, evaluation results and troubleshooting guides to enable knowledge continuity and team velocity.
Requirements
- 4+ years of experience in Data Science, Applied AI, or Machine Learning, with experience building data driven or AI powered solutions.
- Experience taking an AI use case from data exploration and experimentation through a validated working prototype.
- Hands-on experience with machine learning and/or modern Generative AI techniques such as LLMs, embeddings, RAG, semantic search, NLP, recommendation, or agentic systems.
- At least 2 production deployments involving LLM-based systems (fine-tuning, RAG, agentic workflows, or prompt-engineered solutions).
- Experience with AI experimentation and evaluation, including comparing approaches, defining quality metrics, analyzing errors, and iterating based on results.
- Experience using Python and SQL to work with data, build analysis workflows, develop AI algorithms, experiment with models, and build AI/ML solutions.
Preferred qualifications
- 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.
Skills
- Pinecone
- Weaviate
- Langgraph
- Mastra
- LlamaIndex
- CrewAI
- AutoGen
- S3
- Postgres
- GCS
- BigQuery
- Databricks
Show all 15 skills
- Python
- SQL
- LangChain
