AI Agent Developer

Overview Join to apply for the AI Agent Developer role at Geotab. 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 advances security, connects commercial vehicles to the internet, and provides web-based analytics to help customers manage fleets. Our open platform and Geotab Marketplace offer hundreds of third-party solution options that automate operations by integrating vehicle data with other data assets. We process billions of data points daily and use data analytics and machine learning to improve productivity, optimize fleets, and enhance driver safety while complying with regulations. Our team is growing and we’re looking for people who follow their passion, think differently, and want to make an impact. Geotabers work in a fast-paced, ever-changing environment and are willing to take on new tasks and activities that may not 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. 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. Who You Are Geotab is seeking an AI Agent Developer who will drive the internal AI Agent Centre of Excellence (CoE) by identifying, developing, and deploying AI agents to solve internal business challenges and deliver measurable ROI. If you love technology and are keen to join an industry leader, we would love to hear from you What You’ll Do As an AI Agent Developer your key area of responsibility will be identifying, developing, and deploying AI agents to solve internal business challenges and deliver measurable ROI. You will work closely with the existing Generative AI product team and other business units across the enterprise to accelerate the adoption of AI agents internally through high-impact projects. You will be a self-starter with a strong ability to identify opportunities for AI agent applications and have deep technical skills in AI agent development with a focus on delivering measurable business impact. How You’ll Make An Impact In concert with executive AI stakeholders across the organization, develop and implement the vision, strategy, and operating model for the internal AI Agent CoE, mirroring successful aspects of the Data CoE. Define governance frameworks, best practices, and standards for internal AI agent development, deployment, and maintenance. Develop best practices for inclusion of knowledge into our agents (note: knowledge management at Geotab is not in scope). Establish processes for identifying, prioritizing, and managing a portfolio of internal AI agent use cases. Partner with business units to understand processes, pain points, and opportunities for AI agent application. Identify and qualify high-potential use cases where AI agents can deliver ROI, efficiency gains, or operational improvements. Prioritize initiatives based on feasibility, business impact, and strategic alignment, focusing initially on a specific area for rapid, iterative deployment to production. Lead the design, development (including hands-on coding/prototyping initially), testing, and deployment of pilot and production AI agent solutions. Collaborate with the GenAI team to understand and leverage their agentic platform, tools, and expertise for internal use cases, ensuring synergy. Collaborate with platform, legal, compliance, security, and data governance to ensure agents adhere to data governance, security, and regulatory guardrails. Serve as the primary point of contact and subject matter expert for internal AI agent capabilities. Build and foster an internal AI Agent developer community through knowledge sharing, workshops, and direct guidance. Develop and share best practices, reusable components, and documentation to empower other teams to build their own agents. Evangelize the potential of AI agents internally through demonstrations, workshops, and knowledge sharing; act as a change agent. Define KPIs and metrics to measure the success and ROI of implemented AI agents (e.g., time saved, cost reduction, process improvement). Monitor agent performance, gather user feedback, and drive continuous improvement cycles. Report on CoE progress, outcomes, and value generated to senior leadership. Stay abreast of the latest advancements in AI, LLMs, agentic frameworks, prompt engineering, and enabling technologies. Collaborate with the Cloud Business Office and Technical Operations to evaluate and recommend cloud tools, platforms, and services for AI agent development and deployment. Evaluate new tools and techniques for potential enterprise application. What You’ll Bring To This Role Bachelor’s degree in Computer Science, Data Science, Engineering, Artificial Intelligence, or related quantitative field. Master’s preferred. 5+ years of experience in AI/ML, Data Science, or software engineering with a focus on building and deploying intelligent systems or automation. Demonstrated experience with Generative AI concepts, LLMs, and related technologies (e.g., vector databases, embedding models, prompt engineering). Hands-on experience developing AI-driven applications, automations, or prototypes; experience with AI agents or agentic frameworks (e.g., LangChain, CrewAI, AutoGen, Copilot Studio/Frameworks) is highly desirable. Ability to identify business problems and translate them into technical solutions. Experience leading initiatives from concept to production, managing projects, and influencing stakeholders. Experience working with cross-functional teams, including infrastructure and operations. Experience operating in or establishing a CoE structure is a plus. Proficiency in Python and AI/ML libraries (e.g., scikit-learn, pandas). Experience interacting with LLM APIs and understanding their capabilities and costs. Strong understanding of software development best practices (Git, testing, CI/CD). Familiarity with data integration patterns, APIs (REST), and core cloud concepts/services (AWS, Azure, or GCP). Excellent communication, presentation, and interpersonal skills. Strong analytical and problem-solving abilities. Strategic thinking with a pragmatic, results-oriented approach. Ability to operate independently, manage ambiguity, and drive initiatives forward. Passion for AI and its potential to transform business operations internally. Strong business acumen. If you got this far, we hope you’re excited about this role. Even if you don’t meet every requirement, we still encourage you to apply. Please note: Geotab does not accept agency resumes and is not responsible for any fees related to unsolicited resumes. Do not forward resumes to Geotab employees. Why Job Seekers Choose Geotab Flex working arrangements Home office reimbursement program Baby bonus & parental leave top up program Online learning and networking opportunities Electric vehicle purchase incentive program Competitive medical and dental benefits Retirement savings program Note: The above benefits are offered to full-time permanent employees only. How We Work Geotab uses a flexible hybrid working model with support for both in-person and virtual work. You are welcome to come into our offices, and when working from home you should have reliable internet (minimum 50 Mbps download / 10 Mbps upload). We support virtual work with cloud-based applications and asynchronous collaboration. We prioritize health and safety and encourage work-life balance with online events and social activities. Geotab is committed to diversity and inclusion and accommodating people with disabilities during recruitment and employment. If you require accommodations, contact careers@geotab.com. By submitting an application, you acknowledge Geotab’s data practices per our Privacy Policy. #J-18808-Ljbffr