Senior Software Engineer (Applied AI & Customer Solutions)

Join Coursera as a Senior Software Engineer in Applied AI & Customer Solutions. In this role, you will work directly with enterprise and campus customers to build and deploy AI-powered solutions. You will be involved in the entire engagement lifecycle, from scoping customer environments to prototyping solutions and hardening them into production deployments. This is a customer-facing role that requires regular travel to customer sites. You will collaborate closely with Product Managers, AI Specialists, Data Analysts, and other Engineers on the team.

- Scope customer environments directly with executive sponsors and IT/data owners, mapping systems, data models, and workflows to identify the real business problem. - Rapidly prototype and demo working solutions in front of customers, iterating in real time to prove value fast. - Serve as the bridge between customer & core engineering team to harden validated prototypes into production deployments.

- Deep understanding of cloud platforms (AWS preferred), able to design and operate both multi-tenant and hybrid customer-cloud deployment models - 1+ years of experience building production-grade agentic AI solutions - 5+ years of experience in a software engineering role, with strong hands-on backend engineering and cloud infrastructure experience - Willingness and ability to travel regularly to customer sites, domestically and occasionally internationally, as engagement needs require - Prior experience leading projects and debugging complex issues with minimal supervision - Demonstrated comfort operating directly with customers — scoping ambiguous problems, running discovery, and demoing work-in-progress solutions live, in person and remotely - Strong experience with data engineering fundamentals — ingesting, cleaning, and normalizing messy, inconsistent customer data across disparate source systems - Working knowledge of identity and access management, encryption/key management, and secure network patterns (VPC peering, PrivateLink, mTLS) for customer-embedded or regulated environments - Proficiency in backend languages such as Python, Java, Typescript and technologies such as Docker, Kubernetes and Kafka with comfort working across the stack - Experience with modern agentic AI tooling such as LangChain, LangGraph, FastMCP, RAG, or MCP - Experience with Postgres, DuckDB, pgvector, or similar analytical/transactional data layers - Familiarity with data privacy and residency regimes relevant to enterprise/education/government customers (e.g., GDPR, FERPA, DPDPA, HIPAA) - Prior experience in a solutions engineering, professional services, or technical consulting role where you owned a customer relationship end-to-end, including on-site engagement - Demonstrated ability to work in a fast-paced, ambiguous environment and make sound technical trade-offs with limited guidance - Excellent communication skills, with the ability to translate technical constraints into terms an executive sponsor or non-technical stakeholder can act on