Senior Software Engineer, Applied AI & Customer Solutions

Toronto · Canada · USD 137,000-172,000 · 1+ years experience · Hybrid · Posted Oct 7, 2026

At a glance

Coursera and Udemy are now one company, bringing together two mission-driven brands to create the world’s most powerful platform for turning learning into progress. Together, we help more than 300 million learners and 12,000+ enterprise customers build the skills they need for a world being reshaped by AI. Read more about the combined company by visiting our blog.

As a Senior Software Engineer, you will join a fast-paced innovation team that builds and deploys AI-powered solutions directly with Coursera's enterprise and campus customers.
You will sit at the intersection of AI/Data Engineering, cloud and security architecture, and customer-facing solutioning.
You'll operate across the full engagement lifecycle: scoping a customer's environment and pain points, prototyping working demos, and hardening the strongest patterns into production-grade deployments.

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
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
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
Collaborate closely with Product Managers, AI Specialists, and Program Managers to scope problem statements
Travel to customer sites as needed to support scoping, prototyping, and go-live phases of an engagement

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

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

Role is customer-facing and requires regular travel to customer sites (domestic and occasionally international) for discovery, prototyping, and go-live phases

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