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AltaML

Manager, Software Engineering

Toronto, ON, Canada

Job type: Full-time
Apply by: Nov 1, 2026
Experience: 5+ years of software engineering experience, including at least 2 years in a technical lead or management role
Posting language: English
Posted: Sep 15, 2026

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Original job description

Engineering @ AltaML - How We Work:

We are an AI-first company. Claude Code and AltaML's shared configuration and skills library are the default way engineers design, build, test, and review software, not an optional accelerant a few people use.
We expect dramatically higher productivity from working this way. A step change, not a marginal gain. That's the baseline we hire and promote against, not an aspirational ceiling.
We believe AI has compressed what used to take weeks into days, and what used to take days into hours. Estimates, sprint commitments, and delivery timelines should reflect that reality, not pre-AI habits.
Show us, don't tell us. As part of applying, share an example of your AI-assisted coding: a PR, a repo, a recorded session, or whatever best demonstrates how you actually work with AI day to day.
We overpay for the right people. We'd rather pay a premium for an engineer who embodies this and multiplies the team than save money on someone who doesn't.

About the Role:
AltaML is looking for a Manager, Software Engineering to lead a delivery pod where technical excellence and team health go hand in hand. You'll own the architectural integrity of your pod's solutions, clear the path for your engineers to do their best work, and keep delivery on time and on scope, all while operating at AltaML's AI-first standard for how fast and how well work gets done. This is a role for someone who can set the technical bar, grow a strong team, and keep clients and stakeholders confident in what your pod delivers.

Technical Execution & Oversight

Guide your pod on architectural decisions and set technical direction, ensuring solutions are robust, scalable, and aligned with company standards
Champion AI-assisted development as the default way of working, holding your pod to a standard where weeks compress to days and days compress to hours
Remove engineering blockers and facilitate cross-functional technical discussions to keep delivery on track
Partner with the delivery team to ensure on-time, on-scope delivery across all active projects
Lead or actively participate in cross-pod technical guilds (e.g., Frontend, AI/ML, DevOps)

People Leadership & Development

Run regular 1:1s with direct reports focused on career growth, performance, and wellbeing
Provide timely, constructive feedback and support individual development plans
Foster an inclusive, psychologically safe environment where engineers can do their best work

Responsible AI & Quality Assurance

Ensure models and systems are explainable, fair, and auditable throughout the solution lifecycle
Uphold and 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 & 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 Q&A

Resource Planning & Hiring

Conduct hiring interviews and contribute to candidate assessment for engineering roles, evaluating for genuine 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 (e.g., Claude Code or equivalent), with the ability to set - not just permit - that expectation for your team
A demonstrated track record of driving architectural decisions and maintaining engineering quality in a fast-paced delivery environment
Experience managing and growing engineers across different levels
Comfort engaging directly with clients and stakeholders, translating technical complexity into clear, confident communication
Familiarity with AI/ML solutions and modern MLOps or software delivery practices
A track record of championing responsible, ethical AI and inclusive team culture

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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More about this job

Responsibilities

Lead a software engineering delivery pod by setting technical direction, maintaining architectural integrity and solution quality, removing blockers, and ensuring projects are delivered on time and within scope. Develop and support engineers, champion AI-assisted and responsible development practices, coordinate with clients and stakeholders, and contribute to hiring and resource planning.

Requirements

Requires at least five years of software engineering experience, including two or more years in a technical lead or management role, with hands-on fluency in AI coding tools. Candidates should have experience with architecture, engineering quality, people development, client communication, AI/ML or MLOps practices, responsible AI, and inclusive team culture.

Skills

Software Engineering
Technical Leadership
People Management
AI-Assisted Development
Claude Code
Software Architecture
Project Delivery
Responsible AI
Quality Assurance
AI/ML
MLOps
Client Communication
Stakeholder Management
Hiring
Resource Planning
Cross-Functional Collaboration

Visa sponsorship

Not detected in the job text

Keywords

Software Engineering
Claude Code
AI-Assisted Coding
AI-First Development
Software Architecture
Technical Direction
Scalable Solutions
Engineering Quality
Project Delivery
Responsible AI
Explainable AI
Fairness
Auditability
AI/ML
MLOps
Software Delivery Practices
People Leadership
Career Development
Psychological Safety
Client Communication
Stakeholder Management
Solution Architecture
Pre-Sales
Hiring
Resource Allocation
Cross-Functional Collaboration
Technical Guilds
Frontend
DevOps

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