Senior Software Engineer, Applied AI & Customer Solutions

About Coursera Udemy

Coursera and Udemy are now one company bringing together two mission-driven brands to create the worlds most powerful platform for turning learning into progress. Together we help more than 300 million learners and 12000 enterprise customers build the skills they need for a world being reshaped by AI. Read more about the combined company by visiting ourblog.

Why join us now

AI is transforming how people learn work and grow and the need for new skills has never been greater. Coursera brings trusted content and credentials from leading university and industry partners while Udemy brings a dynamic skills marketplace and global network of real-world experts. By combining these strengths we can connect more people and organizations to the skills they need when they need them.

Shape what comes next

By joining our team youll have the opportunity to reshape how the world learns and applies skillsand help millions of people participate in the new economy. Bring your ideas expertise and perspective to meaningful work that can make a difference at global scale.

Job Overview

As a Senior Software Engineer you will join a fast-paced innovation team that builds and deploys AI-powered solutions directly with Courseras enterprise and campus customers. You will sit at the intersection of AI/Data Engineering cloud and security architecture and customer-facing solutioning working hands-on with customers to map their workflows and data prototype solutions quickly and harden the ones that prove valuable into production deployments.

Youll operate across the full engagement lifecycle: scoping a customers environment and pain points like a consultant prototyping working demos in real time with the customer and then hardening the strongest patterns into production-grade secure and compliant deployments. This role is customer-facing and will require regular travel to customer sites (domestic and occasionally international) for discovery prototyping and go-live phases of engagements. You will work closely with Product Managers AI Specialists Data Analysts and other Engineers on the team and directly with customer executive sponsors and IT/data owners to decide what gets standardized deployed or retired.

Key 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 customers 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

Basic 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 with comfort working across the stack
• 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

Preferred Qualifications

• 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
• 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
• Familiarity with data privacy and residency regimes relevant to enterprise/education/government customers (e.g. GDPR FERPA DPDPA HIPAA)
• 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

Why Join Us

• Work on high-visibility engineering problems with direct measurable impact on enterprise and campus customers
• Work directly with strategic customers across geographies owning engagements end-to-end rather than a narrow slice of a roadmap
• Directly influence what graduates from customer-facing custom solutions into Courseras core product
• Be part of a lean cross-functional team (Engineering AI Specialists Product Program Management) with high autonomy and high trust and become a go-to technical leader
• Be part of a mission-driven company transforming global access to education and upskilling in the AI era

For more information about how Coursera collects and uses your personal information please see our Coursera Udemy Global Applicant Privacy Notice.

To protect against recruitment fraud Coursera Udemy recruiters only communicate via official email addresses and never through personal accounts. We do not accept resumes via email or social media; please submit all applications directly through our careers page.

If you encounter suspicious recruitment activity please report it via ourFraudulent Activity Submission Form.

Coursera is an Equal Opportunity Employer committed to building a welcoming and inclusive workplace. We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request at