C
AI Specialist II
Contract type
Ongoing
Work mode
Remote
Experience
Mid-level · 4+ years
Job description
Applied AI role at Coursera focused on designing, prototyping, and evaluating AI systems—including RAG pipelines, agentic workflows, and custom models—to turn ambiguous business problems and complex datasets into working AI solutions for education.
At a glance
- Work mode
- Remote
What you'll do
- 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 shipped, 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
What we're looking for
- 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
Nice to have
- 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
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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. Coursera brings trusted content and credentials from leading university and industry partners, while Udemy brings a dynamic skills marketplace and global network of real-world experts.
Mission
We help more than 300 million learners and 12,000+ enterprise customers build the skills they need for a world being reshaped by AI.
Key facts
- Coursera and Udemy are now one company
- More than 300 million learners
- 12,000+ enterprise customers