Senior Software Engineer, Applied AI and Customer Solutions

You'll join a fast-paced innovation team that builds and deploys AI-powered solutions directly with Coursera's enterprise and campus customers. You'll operate across the full engagement lifecycle: scoping customer environments and pain points like a consultant, prototyping working demos in real time, and hardening validated solutions into production-grade, secure deployments. This role sits at the intersection of AI and data engineering, cloud and security architecture, and customer-facing solutioning. You'll work hands-on with customers to map workflows and data, while collaborating closely with Product Managers, AI Specialists, and Engineers to decide what gets standardized and deployed broadly. Regular travel to customer sites (domestic and occasionally international) is required for discovery, prototyping, and go-live phases.

Software Engineering - Core competency for designing, developing, and maintaining production-grade systems deployed in customer environments.

AI Fluency - Essential for building and deploying agentic AI solutions and understanding AI capabilities for customer problem-solving.

Customer/Stakeholder Focus - Essential for understanding customer needs, scoping ambiguous problems, and maintaining focus on business impact throughout engagements.

• Scope customer environments directly with executive sponsors and IT/data owners to map systems, data models, and workflows. 
• Rapidly prototype and demo working solutions in front of customers, iterating in real time to validate business value.
• Serve as the bridge between customer and core engineering teams to harden validated prototypes into production deployments.
• Design and implement multi-tenant, hybrid, or customer-controlled deployment architectures that meet data residency, privacy, and IT-maturity requirements.
• Build and own identity and access management, encryption, and secure cross-network connectivity (mTLS, VPC peering, PrivateLink, API gateways) for customer-embedded deployments. 
• Integrate security, data-residency, and compliance considerations into discovery conversations before commercial commitments are made.
• Own CI/CD, observability, and production support for systems deployed inside customer environments.
• Identify repeatable patterns across customer engagements and feed field evidence back to Product to inform standardization, broader deployment, or retirement decisions. 
• Collaborate with Product Managers, AI Specialists, and Program Managers to scope problem statements with focus on customer and business impact. 
• Travel to customer sites as needed to support scoping, prototyping, and go-live phases, including in-person workshops and executive readouts.

• 5+ years of experience in a software engineering role with hands-on backend engineering and cloud infrastructure work.
• 1+ years of experience building production-grade agentic AI solutions.
• Experience with backend languages such as Python, Java, or Typescript and technologies such as Docker, Kubernetes, and Kafka, with demonstrated ability to work across the full stack.
• Background in cloud platforms (AWS preferred) and ability to design and operate multi-tenant and hybrid customer-cloud deployment models.
• Experience with data engineering fundamentals including ingesting, cleaning, and normalizing messy, inconsistent customer data across disparate source systems.
• Working knowledge of identity and access management, encryption and key management, and secure network patterns (VPC peering, PrivateLink, mTLS) for customer-embedded or regulated environments.
• Demonstrated history of operating directly with customers to scope ambiguous problems, conduct discovery, and demo work-in-progress solutions both in person and remotely.
• Willingness and ability to travel regularly to customer sites, domestically and occasionally internationally, based on engagement needs.
• Prior experience leading projects and troubleshooting complex issues with minimal supervision.

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