Riva is seeking a hands-on Engineering Team Lead to guide the development of our AI-powered meeting intelligence product. This product transforms conversations between relationship managers and their clients into structured, CRM-ready insights, helping ensure that valuable client context is accurately captured and available when it is needed. You will join one of Riva’s most AI-forward teams, where AI is integrated directly into the software development lifecycle. The team uses agentic workflows to support development and code review and continues to explore new ways for AI agents to take ownership of engineering work. In this role, you will lead a small engineering team that is expected to approximately double in size. This is a hands-on leadership position, with approximately 60–70% of your time focused on coding, architecture, and system design. The remainder of your time will be dedicated to supporting the team, strengthening engineering processes, and representing technical decisions in leadership discussions. As the Engineering Team Lead, your responsibilities will be centered around delivering the following outcomes: Provide hands-on technical leadership. Design, build, and maintain full-stack product capabilities while contributing directly to coding, architecture, and system design. Use and expand agentic AI workflows throughout the development lifecycle, including specification, implementation, review, testing, and delivery. Work closely with the Product Owner to manage the backlog, refine requirements, estimate work, plan sprints, and support product rollouts and optimization. Strengthen engineering delivery. Own and continuously improve development workflows, CI/CD practices, release traceability, technical standards, and team processes. Manage technical risk.



Track technical debt, identify dependencies approaching end of support, and clearly communicate risks, tradeoffs, blockers, and timelines before they affect delivery. Build quality into the product. Partner with the team’s tester to strengthen unit, integration, end-to-end, and automated test coverage, particularly for AI-enabled features. Lead Agile team practices. Facilitate sprint planning, backlog refinement, demos, retrospectives, and other Agile ceremonies while maintaining visibility into delivery progress. Communicate technical decisions. Represent the team in bi-weekly leadership meetings and explain architecture, timelines, risks, and technical decisions to both technical and non-technical audiences. Hold regular one-on-one meetings, provide timely feedback, mentor engineers, support performance reviews, and create opportunities for continued growth. Examine your skill gaps and identify opportunities for training, industry certifications, and project work to elevate your skills and support continued career growth. During your first 30 days, you will focus primarily on learning the product, roadmap, development environment, internal processes, and business domain, including CRM, banking, messaging systems, and specification-driven development. By 60 days, you will begin contributing low-risk production work and establish a plan to address any identified skill gaps.



Proven experience leading a software engineering team. Experience owning system design, architecture, backlog management, delivery reporting, and engineering workflow improvements. Experience presenting technical decisions, risks, tradeoffs, and timelines to leadership. Demonstrated success coaching and mentoring engineers, providing feedback, and supporting performance conversations. Experience working in an Agile software development setting. Experience helping a software team grow and introducing the processes needed to support that growth. Experience developing customer-facing products with integrated AI capabilities, including hands-on involvement in the software development lifecycle. Strong understanding of the product lifecycle for AI-enabled features, including development, testing, deployment, monitoring, and continuous improvement. Ability to assess and clearly communicate the risks, limitations, and tradeoffs associated with AI-powered solutions. Software Engineering

Skills:
Strong full-stack software engineering experience. Solid foundation in C#, .
NET 10, TypeScript, and REST API design. Experience working with Microsoft Graph API. Experience owning CI/CD pipelines and deployment workflows. Cloud deployment experience; AWS experience is preferred but not required. Strong understanding of unit, integration, and end-to-end testing. Experience working with relational or NoSQL databases. Ability to communicate technical concepts clearly to technical and non-technical audiences. Bonus Points For: Familiarity with additional technologies in Riva’s engineering stack. Formal performance review experience. Experience owning the full software development lifecycle. Frontend: Vu

📌 Software Engineering Manager/Leader (Edmonton)
🏢 Riva International
📍 Edmonton