AI Agent Developer
Who we are:
Who you are:
We are always looking for amazing talent who can contribute to our growth and deliver results! 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 need to 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.
To be successful in this role you will be a self-starter with a strong ability to identify opportunities for AI agent applications. In addition, the successful candidate will have deep technical skills in AI agent development and a strong focus on delivering measurable business impact and efficiency gains.
How you'll make an impact:
CoE Strategy & Foundation:
- 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 (but the responsibility of knowledge management at Geotab is not in scope)
- Establish processes for identifying, prioritizing, and managing a portfolio of internal AI agent use cases.
Use Case Identification & Prioritization:
- Partner closely with business units across the enterprise to understand their processes, pain points, and opportunities for AI agent application.
- Identify and qualify (with the assistance of key stakeholders) high-potential use cases where AI agents can deliver significant 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.
Development & Implementation Leadership:
- Lead the design, development (including hands-on coding/prototyping initially), testing, and deployment of pilot and production AI agent solutions.
- Collaborate extensively with the existing GenAI team to understand and potentially leverage their agentic platform, tools, and expertise for internal use cases, ensuring synergy and avoiding redundant efforts.
- Collaborate closely with platform, legal, compliance, security, and data governance teams to ensure agents adhere to all data governance, security, and regulatory guardrails.
Collaboration & Evangelism:
- 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.
Performance Measurement & Iteration:
- Define key performance indicators (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.
Technology & Cloud Tooling Strategy:
- Stay abreast of the latest advancements in AI, Large Language Models (LLMs), agentic frameworks, prompt engineering, and enabling technologies.
- In collaboration with the Cloud Business Office and Technical Operations, evaluate and recommend appropriate cloud tools, platforms, and services to support AI agent development and deployment across the enterprise.
- Evaluate new tools and techniques for potential application within the enterprise context.
What you'll bring to this role:
- Bachelor's degree in Computer Science, Data Science, Engineering, Artificial Intelligence, or a related quantitative field. Master's degree preferred.
- 5+ years of experience in AI/ML, Data Science, or software engineering roles with a focus on building and deploying intelligent systems or automation.
- Demonstrated experience with Generative AI concepts, LLMs (e.g., GPT series, Claude, Llama), and related technologies (e.g., vector databases, embedding models, prompt engineering).
- Hands-on experience developing AI-driven applications, automations, or prototypes; specific experience building or working with AI agents or agentic frameworks (e.g., LangChain, CrewAI, AutoGen, Microsoft Copilot Studio/Frameworks) is highly desirable.
- Strong ability to identify business problems/opportunities and translate them into tangible technical solutions.
- Proven ability to lead initiatives from concept to production, manage projects, and influence stakeholders in a corporate environment.
- Experience working collaboratively across technical and non-technical teams, including infrastructure and operations teams.
- Experience operating in or establishing a CoE structure is a plus.
- Proficiency in Python and relevant AI/ML libraries (e.g., scikit-learn, pandas, libraries for interacting with LLMs).
- Experience interacting with LLM APIs and understanding their capabilities, limitations, and cost implications.
- Solid understanding of software development best practices (e.g., version control with Git, testing, CI/CD concepts).
- Familiarity with data integration patterns, APIs (RESTful), and core cloud infrastructure concepts and services (AWS, Azure, or GCP).
- Excellent communication (written and verbal), presentation, and interpersonal skills – ability to explain complex concepts to diverse audiences.
- Strong analytical and problem-solving abilities.
- Strategic thinking combined with a pragmatic, results-oriented, "get-it-done" 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.
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
*The above are offered to full-time permanent employees only
How we work:
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