Senior Software Engineer – Applied AI & Customer Solutions

About the role

Join a fast‑paced innovation team that builds and deploys AI‑powered solutions for Coursera's enterprise and campus customers. You will work at the intersection of AI, data engineering, cloud security, and customer‑facing solutioning, delivering prototypes and production‑grade deployments.

Key responsibilities

• Scope customer environments with executive sponsors and IT owners to map systems, data models, and workflows.
• Rapidly prototype and demo working solutions in real time, iterating to prove value.
• Bridge customers and core engineering teams to harden validated prototypes into secure, production deployments.
• Design multi‑tenant, hybrid, or customer‑controlled architectures respecting data residency and privacy requirements.
• Own identity and access management, encryption, and secure cross‑network connectivity (mTLS, VPC peering, PrivateLink, API gateways).
• Manage CI/CD, observability, and production support for systems deployed inside customer environments.
• Identify repeatable patterns across engagements and feed insights back to product teams.
• Travel regularly to customer sites for discovery, prototyping, and go‑live phases.

Required profile

• 5+ years of software engineering experience with strong backend and cloud infrastructure skills.
• 1+ years building production‑grade agentic AI solutions.
• Proven ability to work directly with customers, scope ambiguous problems, and deliver live demos.
• Willingness to travel regularly, domestically and occasionally internationally.
• Experience leading projects and debugging complex issues with minimal supervision.

Required skills

• Python, Java, TypeScript
• Docker, Kubernetes, Kafka
• AWS (cloud platform)
• Data engineering fundamentals – ingesting, cleaning, normalizing customer data
• Identity and access management, encryption/key management, secure network patterns (VPC peering, PrivateLink, mTLS)
• Modern agentic AI tooling such as LangChain, LangGraph, FastMCP, RAG, MCP
• Analytical/transactional data layers like Postgres, DuckDB, pgvector