Senior AI Solutions Engineer for Enterprise Customer Deployments

Udemy; United States; Remote; USD 180,000 - 240,000; Full time

Job summary

Coursera + Udemy is seeking a Senior Software Engineer to join a fast-paced AI solutions team delivering production-grade, customer-facing deployments for enterprise and campus customers. You will work at the intersection of AI, data engineering, cloud architecture, and security, prototyping with customers and scaling proven patterns into secure, multi-tenant deployments.

Travel to customer sites is expected regularly (domestic and occasional international), with close collaboration to product,

Qualifications

• 5+ years of experience in a software engineering role, with strong hands-on backend engineering and cloud infrastructure experience.
• 1+ years of experience building production-grade agentic AI solutions.
• Proficiency in backend languages such as Python, Java, Typescript and technologies such as Docker, Kubernetes and Kafka.
• Deep understanding of cloud platforms (AWS preferred), able to design and operate both multi-tenant and hybrid customer-cloud deployment models.
• 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.
• Demonstrated comfort operating directly with customers - scoping ambiguous problems, running discovery, and demoing work-in-progress solutions live, in person and remotely.
• 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.

Responsibilities

• Scope customer environments directly with executive sponsors and IT/data owners - mapping systems, data models, and workflows to identify the real business problem, not just the stated one.
• 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.
• Design and implement multi-tenant, hybrid, or customer-controlled deployment architectures, as per customer's 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.
• Bring security, data-residency and compliance judgment into discovery conversations before a commercial commitment is made, not after.
• Own CI/CD, observability, and production support for systems living inside customer environments.
• Recognize repeatable patterns across customer engagements and feed field evidence back to Product to inform what should be standardized, deployed more broadly, or retired.
• Collaborate closely with Product Managers, AI Specialists, and Program Managers to scope problem statements with a laser focus on customer and business impact.
• Travel to customer sites as needed (expect regular travel) to support scoping, prototyping, and go-live phases of an engagement, including in-person workshops and executive readouts]

Skills

Backend engineering

Agentic AI

Python

Java

Typescript

Docker

Kubernetes

Kafka

AWS

Data engineering

IAM & encryption

Tools

Postgres

DuckDB

Job description

Coursera + Udemy is seeking a Senior Software Engineer to join a fast-paced AI solutions team delivering production-grade, customer-facing deployments for enterprise and campus customers. You will work at the intersection of AI, data engineering, cloud architecture, and security, prototyping with customers and scaling proven patterns into secure, multi-tenant deployments.

Travel to customer sites is expected regularly (domestic and occasional international), with close collaboration to product,