Sr. Specialist, AI Solutions Developer

L3HHCM20•Hamilton, ON

1d•CA$90,000 - CA$140,000•Onsite

About The Position

The AI Solutions Developer is responsible for designing, developing, integrating, and deploying AI-enabled solutions that improve business processes, productivity, decision-making, and operational effectiveness across WESCAM. This role combines AI application development, solution architecture, enterprise integration, and technical leadership to deliver scalable, secure, and maintainable AI capabilities aligned with operational priorities, data maturity, and enterprise technology standards. This role works closely with IT leadership, business stakeholders, engineering teams, data professionals, and external partners to transform business requirements into practical AI solutions. This role supports the evaluation of AI technologies, develops prototypes and production-ready applications, and ensures solutions are effectively integrated into enterprise systems and business workflows.

Requirements

Experience developing AI solutions using Azure AI Services, Azure OpenAI, Microsoft Copilot Studio, and related AI platforms.
Strong understanding of Large Language Models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), agentic AI workflows, and AI application patterns.
Experience designing and implementing AI-powered copilots, intelligent assistants, knowledge management, and process automation solutions.
Experience integrating AI solutions with enterprise systems, applications, databases, and business workflows.
Strong programming skills in Python, C#, JavaScript, or similar modern development languages.
Experience using Docker for containerization of AI applications and services.
Experience with Kubernetes for orchestration, scaling, deployment, and management of containerized workloads.
Ability to translate business requirements into scalable, maintainable, and secure technology solutions.
Experience designing end-to-end AI solution architectures and technical specifications.
Ability to evaluate technologies, frameworks, and platforms for technical fit, scalability, cost, and long-term sustainability.
Excellent communication and stakeholder management skills across business and technical audiences.
Ability to explain and interpret technical processes, architecture concepts, and operational impacts.
Ability to guide implementation activities, coordinate project work, and support change adoption.

Nice To Haves

Bachelor’s Degree in Information Technology, Computer Science, Engineering, Data Analytics, Business Technology, or related discipline with a minimum of 6 years of relevant experience; or Graduate Degree with a minimum of 4 years of related experience; or In lieu of a degree, a minimum of 10 years of directly related experience.
Experience building and deploying AI-powered applications in enterprise environments.
Experience integrating AI solutions into business applications and operational workflows.
Experience supporting or coordinating cross-functional technology implementations.
Knowledge of responsible AI governance and technology risk management practices.
Experience supporting enterprise architecture, systems integration, or operational transformation programs.
Experience with enterprise AI and automation platforms including Microsoft Copilot, Azure AI/OpenAI, Microsoft Fabric, enterprise integration technologies, and responsible AI governance tools.
Experience with containerization and orchestration technologies such as Docker and Kubernetes to deploy, manage, scale, and monitor AI-enabled applications, automation services, APIs, and enterprise integration workloads across cloud and hybrid environments.

Responsibilities

Design, develop, test, and deploy AI-powered applications, copilots, automation solutions, and intelligent workflows using enterprise-approved platforms and frameworks.
Translate business requirements into scalable AI solution architectures and technical specifications.
Integrate AI services with enterprise applications, databases, APIs, and business systems.
Ensure AI solutions align with enterprise architecture, security, and operational requirements.
Configure and deploy AI services including Azure OpenAI and Copilot technologies.
Utilize Docker and Kubernetes to containerize, orchestrate, scale, and manage AI workloads.
Document architecture, implementation patterns, and support procedures.
Implement responsible AI principles, security controls, and compliance requirements within AI solutions.
Ensure data privacy, access controls, auditability, and governance standards are incorporated into solution design.
Collaborate with business teams to identify opportunities for AI-enabled process improvements.
Participate in technical reviews, architecture discussions, and solution evaluations.
Support proof-of-concepts, pilots, and production implementations.