Senior Engineering Manager, AI Product Engineering

Description

ABOUT THE POSITION

Meet the Smart Safety Company

At Safe Fleet our name says it all. We make fleet vehicles – and everyone in and around them – safer. Our fleet safety platform brings together best-in-class products, ground-breaking technology, and a 100-year history of fleet know-how and innovation to solve the world’s biggest fleet safety problems.

Our core value is safety. Without safety first, efficiency and productivity are not possible. This is true for our products, our culture, and our relationship with our community. Our vision is to reduce preventable deaths and injuries in and around fleet vehicles with a goal of ZERO accidents.

We are re-defining what safety means for fleets of every type – from school buses to waste collection trucks, firefighting to utility vehicles, police cruisers to delivery vans.

Whether you work in our Charlotte plant to build life-saving stop arms for school buses, or design advanced camera vision products in our Vancouver office, forge valves and high-quality nozzles to fight fires, or dream up new ways to protect fleet operators in our Corporate HQ in Kansas City, you’ll contribute to our goal to keep everyone safe.

We are a fast-growing manufacturing, service, and technology company with over 1700 employees in over 15 locations across Canada and the US. We’re looking for motivated self-starters with innovative thinking to join our team and help us achieve our growth and performance goals. Sound like you?

JOB SUMMARY

We are seeking a highly technical, hands-on Engineering Manager to lead the development of AI-powered features and capabilities across our product portfolio.

The ideal candidate combines strong software engineering fundamentals, practical expertise in modern AI technologies, and proven engineering leadership. This role also requires experience with AI-Native Engineering and Agentic SDLC, leveraging AI coding agents, Spec-Driven Development, and automation to improve engineering productivity and software delivery.

This is a hands-on leadership role focused on building and delivering production-ready AI solutions that create measurable customer value.

You will

AI Product Engineering

• Lead the architecture, development, and delivery of scalable, production-ready AI features and shared AI platforms.
• Apply Generative AI, Machine Learning, Deep Learning, and Computer Vision to solve product challenges.
• Develop solutions using LLMs, RAG, AI agents, workflow orchestration, and traditional ML techniques.
• Establish reusable AI architecture patterns and ensure performance, scalability, security, reliability, and cost efficiency.
• Contribute directly to technical architecture, prototyping, coding, and complex problem-solving.

AI-Native Engineering & Agentic SDLC

• Lead the adoption of AI-Native Engineering and Agentic SDLC practices.
• Implement AI-assisted development workflows using AI coding agents, Spec-Driven Development (SDD), and development automation.
• Leverage AI agents and reusable skills across design, implementation, testing, code review, and delivery.
• Establish engineering standards and metrics to improve productivity without compromising quality, security, or maintainability.

Team Leadership & Collaboration

• Lead and mentor a team of 4–8 engineers, fostering technical excellence and continuous improvement.
• Partner with Product Management to translate business requirements into technical solutions and execution plans.
• Collaborate with other engineering teams to integrate AI capabilities into existing products.
• Work with Security, Compliance, and other stakeholders to ensure responsible AI deployment.

Salary: $150,000 - $170,000/yr CAD + 12.5% bonus

The final offer will be determined based on a combination of factors including skills, experience, and alignment with the role’s responsibilities.

• Candidates at the lower end of the range will meet the core qualifications and demonstrate strong potential to grow within the role.
• Mid-range offers reflect a solid match with the role’s technical and collaborative requirements.
• Offers at the top of the range are reserved for candidates who bring exceptional qualifications, specialized expertise, or unique value that significantly exceeds the baseline expectations

At Safefleet, we are an equal opportunity employer that is committed to creating a diverse and inclusive workplace where everyone is valued and respected. We embrace diversity and do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or any other legally protected status. We promote fair and equitable hiring practices and foster a culture of inclusivity and respect. Our core values of integrity, innovation, teamwork, customer focus, and safety guide our efforts to provide a workplace where all employees can thrive and reach their full potential.

Requirements

• 8+ years of software engineering experience, including strong system design and architecture expertise.
• 3+ years of engineering leadership experience, with proven ability to lead and mentor technical teams.
• 2+ years of hands-on experience developing and deploying production AI applications or product features.
• Strong experience with modern AI platforms and services, such as OpenAI, Azure OpenAI, Google Gemini, Claude, or equivalent technologies.
• Solid understanding of LLMs, transformer-based models, prompt engineering, RAG, AI agents, and workflow orchestration.
• Practical knowledge of Data Science and Machine Learning, including predictive modeling and model evaluation.
• Hands-on experience using AI coding agents, such as Claude Code, GitHub Copilot, or equivalent tools.
• Practical experience with AI-Native Engineering, Spec-Driven Development, and AI-assisted software development workflows, with an understanding of Agentic SDLC practices.
• Experience developing scalable cloud-based solutions using AWS, Azure, or GCP.
• Strong technical leadership, communication, and cross-functional collaboration skills.

Preferred Qualifications

• Experience developing AI-powered features for commercial software products.
• Experience with Computer Vision, image/video analytics, Deep Learning, or predictive ML.
• Experience with local/self-hosted models, Hugging Face, and Model Context Protocol (MCP).
• Experience with AI agent orchestration frameworks and production ML pipelines.
• Experience implementing advanced Agentic SDLC workflows, including custom agents, reusable skills, automated verification, and CI/CD integration.
• Experience building reusable AI platforms or shared AI services.
• Familiarity with Agile methodologies and experience working in regulated or security-conscious environments.