Team Lead, GenAI Engineering

Geotab•Waterloo, ON

49d•Hybrid

About The Position

Geotab ® is a global leader in IoT and connected transportation and certified “Great Place to Work™.” We are a company of diverse and talented individuals who work together to help businesses grow and succeed, and increase the safety and sustainability of our communities. Geotab is advancing security, connecting commercial vehicles to the internet and providing web-based analytics to help customers better manage their fleets. Geotab’s open platform and Geotab Marketplace ®, offering hundreds of third-party solution options, allows both small and large businesses to automate operations by integrating vehicle data with their other data assets. Processing billions of data points a day, Geotab leverages data analytics and machine learning to improve productivity, optimize fleets through the reduction of fuel consumption, enhance driver safety and achieve strong compliance to regulatory changes. Our team is growing and we’re looking for people who follow their passion, think differently and want to make an impact. Ours is a fast paced, ever changing environment. Geotabbers accept that challenge and are willing to take on new tasks and activities - ones that may not always be described in the initial job description. Join us for a fulfilling career with opportunities to innovate, great benefits, and our fun and inclusive work culture. Reach your full potential with Geotab. To see what it’s like to be a Geotabber, check out our blog and follow us @InsideGeotab on Instagram. Join our talent network to learn more about job opportunities and company news. We are always looking for amazing talent who can contribute to our growth and deliver results! Geotab is seeking a Team Lead, GenAI Engineering who will champion and guide a team of Software Developers and Data Scientists, accounting for the end-to-end implementation and deployment of advanced Generative AI solutions. The projects will vary in scope, complexity, and affected business area. If you love technology, and are keen to join an industry leader — we would love to hear from you! As a Team Lead, GenAI Engineering, your key area of responsibility will be leading the design, development, and deployment of cutting-edge Generative AI software applications, establishing high technical standards through code reviews and scalable architectures, and ensuring all data products meet critical business needs. You will need to work closely with the Manager of AI Engineering, Geotab’s software engineering and data science squads, and cross-functional stakeholders to translate complex technical insights into actionable reports. To be successful in this role you will be a technical leader with an entrepreneurial mindset who is comfortable in a dynamic environment and possesses a passion for coaching and mentoring team members toward their full potential. In addition, the successful candidate will have strong analytical and problem-solving skills, with the ability to manage multiple development projects simultaneously, break down complex requirements into executable tasks, and make data-driven decisions to ensure timely, high-standard results.

Requirements

Bachelors degree in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field.
3-5 years of relevant industry experience in a Data Science, Machine Learning, or AI Engineering role, with hands-on experience in the entire GenAI project lifecycle.
1-3 years of supervisory or team leadership experience, with a proven ability to mentor junior engineers and conduct rigorous code reviews.
Expert proficiency in Python, SQL, and GenAI frameworks such as LangChain and LangGraph.
Deep technical knowledge of Large Language Models (LLMs), transformer architectures, RAG systems, and vector databases (e.g., FAISS).
Experience designing scalable AI architectures on cloud platforms, preferably GCP or Azure, with an understanding of MLOps and microservices.
Strong soft skills, including high organization, meticulous attention to detail, and the ability to build relationships across all levels of the organization.

Responsibilities

Cultivate a High-Performing Team: Actively mentor and coach team members on best practices in both AI product development and software engineering. Beyond technical guidance, serve as a career coach, conducting regular 1-on-1s to align individual aspirations with organizational goals and providing the radical candor necessary for continuous professional growth.
Own the Hiring Process: Drive the end-to-end recruitment of top-tier talent, rigorously assessing technical depth (Data Science and LLM Engineering) and cultural alignment. Design and oversee a seamless onboarding experience that integrates new hires into the GenAI stack and team culture with speed and clarity.
Foster a Culture of Innovation: Encourage and enable the team to experiment with new technologies and methodologies, making pragmatic trade-offs to meet project goals while fostering a culture of continuous learning.
Performance Management & Accountability: Establish clear performance metrics and KPIs for the engineering squad. Take ownership of the performance review cycle, identifying high-potential talent for advancement and proactively managing underperformance through structured support and feedback loops.
Spearhead Advanced GenAI Development: Lead the design, development, and deployment of cutting-edge Generative AI software applications. Research and implement novel solutions using techniques such as prompt engineering, Agentic workflows, and Retrieval Augmented Generation (RAG) to solve complex business challenges.
Technical Direction & Code Quality: Establish and maintain a high technical bar for the team. Perform regular code reviews, ensure adherence to software engineering best practices, and lead the design of objective evaluation systems to rigorously assess model quality, performance, and user experience.
Architect Scalable Solutions: Oversee the design and maintenance of high-quality, scalable, and secure AI architectures on cloud platforms. Ensure the architectural integrity of applications built on top of Generative AI models, balancing critical considerations like AI safety, latency, and cost.
Task Management & Delivery: Serve as the primary technical subject matter expert. Break down complex, high-level requirements into executable technical tasks and sprints. Own the planning, execution, and delivery of multiple development projects, ensuring they are completed on time and to a high standard.
Lead Communication and Documentation: Act as the primary technical point of contact. Manage communication with cross-functional stakeholders, translating complex technical insights into clear, actionable reports. Ensure comprehensive documentation of research, methodologies, and system designs is maintained.