jobapplier

Senior Software Engineer (Applied AI & Customer Solutions)

Coursera

Skills

Required

  • software engineering
  • backend engineering
  • cloud infrastructure
  • scoping ambiguous problems
  • VPC
  • Python
  • Java
  • Typescript
  • Docker
  • Kubernetes
  • Kafka
  • Postgres

Preferred

  • data models
  • iterating in real time
  • prove value fast
  • cloud platforms
  • AWS
  • hybrid customer-cloud deployment models

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.

Serve as the bridge between customer & core engineering team to harden validated prototypes into production deployments.

Responsibilities

  • 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.
  • Deep understanding of cloud platforms (AWS preferred), able to design and operate both multi-tenant and hybrid customer-cloud deployment models

Requirements

  • 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