Manager, Software Engineering

Engineering at AltaML

About the Role

Technical Execution and Oversight

• Guide architectural decisions and technical direction for robust, scalable solutions aligned with company standards.
• Champion AI-assisted development and hold the pod to the company's accelerated delivery standard.
• Remove engineering blockers and facilitate cross-functional technical discussions.
• Partner with delivery teams to ensure projects are delivered on time and within scope.
• Lead or participate in technical guilds including Frontend, AI/ML, and DevOps.

People Leadership and Development

• Run regular one-to-ones focused on career growth, performance, and wellbeing.
• Provide timely, constructive feedback and support individual development plans.
• Foster an inclusive and psychologically safe environment where engineers can do their best work.

Responsible AI and Quality

• Ensure models and systems are explainable, fair, and auditable throughout the solution lifecycle.
• Champion AltaML's Responsible AI guidelines and development best practices across the pod.
• Manage end-to-end solution quality in partnership with the pod lead from design through deployment.

Stakeholder and Client Coordination

• Communicate pod progress, risks, and outcomes clearly to internal stakeholders and external clients.
• Maintain a strong communication loop with the delivery team to keep project requirements aligned.
• Support pre-sales and business development with solution architecture input, demos, and technical questions.

Resource Planning and Hiring

• Conduct hiring interviews and contribute to engineering candidate assessments, including evaluation of AI-assisted development fluency.
• Assist with quarterly resource allocation planning across the pod.

What You Bring

• 5+ years of software engineering experience, including at least 2 years in a technical lead or management role.
• Fluent, hands-on use of AI coding tools such as Claude Code or an equivalent.
• Demonstrated architectural decision-making and engineering quality ownership in a fast-paced delivery environment.
• Experience managing and growing engineers across different levels.
• Client and stakeholder communication experience, including translating technical complexity clearly.
• Familiarity with AI/ML solutions and modern MLOps or software delivery practices.
• A track record of championing responsible, ethical AI and inclusive team culture.