Applied AI Solutions Technical Lead
Urban Ridge Supplies
About Us
At CAA Club Group, we are passionate about keeping our Members safe - whether they are on the road, at home, or travelling abroad. As a trusted Member-based organization, we provide products and services that are essential to Members’ safety and peace of mind. With over 2.6 million Members across Ontario and Manitoba, we advocate on issues such road safety and infrastructure, the environment, seniors’ mobility, and consumer protection. Associates share in each other’s successes, drive change and support each other while cultivating a great working environment to deliver on what is best for our Members. CAA SCO Systems & Services Inc. is a member of the CAA Club Group of Companies. Who We Are Are you ready to join an award-winning, purpose-driven culture? Welcome to the CAA Club Group of Companies (CCG), where purpose leads to passion!- At CCG, we are committed to delivering an exceptional Associate experience. We offer:
- Work-life harmony with access to an award-winning holistic wellness program,
- Continuous learning through our robust corporate curriculum and education reimbursement program,
- Incredible rewards, travel incentives, and product and service discounts,
- Pay-for-performance and best-in-class recognition programs, and
- Competitive benefits that include a defined contribution plan, personal spending account, and so much more.
- Guide IT application teams in identifying and designing applied AI, machine learning, and generative AI capabilities that address practical business needs.
- Translate business requirements into reusable AI solution patterns, reference designs, and implementation guidance for delivery teams.
- Create focused proofs of concept and prototypes to demonstrate emerging AI capabilities and validate feasibility.
- Ensure proposed AI capabilities are practical, maintainable, reliable, scalable, and aligned to enterprise architecture standards.
- Provide hands-on coaching and technical consultation so teams can adopt AI responsibly and consistently.
- Design and implement RAG pipelines, including ingestion, embeddings, retrieval strategies, and grounding.
- Integrate enterprise knowledge sources while respecting data classification, privacy requirements, access controls, and security boundaries.
- Partner with IT application, architecture, data, cybersecurity, infrastructure, and platform teams to move approved AI capabilities into production environments.
- Support application teams through SDLC, CI/CD, API integration, testing, monitoring, versioning, documentation, and operational readiness for AI-enabled solutions.
- Ensure solutions meet enterprise standards for performance, resilience, security, privacy, supportability, and cost management.
- Establish operational guardrails, implementation standards, and support practices for consistent enterprise adoption.
- Bachelor’s degree in Information Security, Computer Science, or a related discipline.
- 5+ years of experience in machine learning, AI, data science, software engineering, or applied AI solution delivery, with demonstrated experience moving solutions from concept to production.
- Experience in insurance, financial services, or other regulated environments.
- Familiarity with cloud AI platforms, vector databases, AI agent frameworks, and model integration approaches such as MCP or similar orchestration patterns.
- Experience measuring business outcomes from AI solutions, such as productivity improvement, reduced manual effort, improved knowledge reuse, or enhanced decision support.
- Hands-on experience with:
- Generative AI and large language models
- Prompt engineering techniques
- RAG architectures and vector databases
- Model and system evaluation frameworks, including accuracy, relevance, safety, latency, cost, and user feedback measures
- Secure integration patterns for enterprise systems, APIs, data sources, and AI orchestration frameworks
- Strong programming skills in Python and modern AI/ML frameworks.
- Experience deploying AI solutions into production environments using disciplined SDLC, DevOps, MLOps, or platform engineering practices.
Job Id: LZTq5qBfu1H6wiBrAjgFOo9Ukh3Oxd/O5Sxu/OhErrvcT1TPrdr29BCeRi4ntN5x7kI8kvvT1XJ/f8b5IQZGGS3B9erhp3j9jg==
Vacancy posted 1 day ago
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