Senior Solution Architect at Intact evolving Data and AI platforms. Collaborating across teams to deliver secure and scalable solutions that impact business.
Responsibilities
Evolve the Enterprise Data Platform and AI platform architectures, including integrations with corporate systems and market tools
Contribute to and execute the Data & AI Strategy while defining and refining the Architecture patterns
Deliver architecture blueprints and implementation strategies that meet enterprise security and data protection standards; ensure alignment to corporate vision and objectives while proposing innovative approaches
Collaborate with members of various technical teams, business teams and delivery teams to develop solutions that address key customer needs while adhering to EA principles and guidelines
Execute and evolve architecture processes; create and maintain architecture models, roadmaps, and strategies (platform, application, data, integration, security)
Lead risk and cost analyses, including build vs buy strategies and recommendations
Lead and facilitate research and assessments of new approaches and technologies (e.g., serverless, event-driven, GenAI, MLOps, IaC) for potential use
Design AI/ML solution architectures and model-serving/hosting patterns; evolve ML platform capabilities (feature stores, experimentation tracking, pipelines/orchestration)
Promote event-driven and serverless patterns where beneficial; enable DevSecOps, MLOps, and Infrastructure as Code with strong observability (monitoring, logging, alerting)
Lead cross-team dependency management for complex migrations and platform transitions, drive standards and best practices
Requirements
10+ years in a Solution Architecture role
Experience architecting Data and AI platforms in the cloud (e.g., AWS Lambda, S3, EC2, ECS, RDS, DynamoDB, API Gateway, ALB, CloudWatch, Amazon SageMaker)
Experience with AI/ML solution and platform architecture: model lifecycle, hosting/serving patterns, experimentation, and pipelines into Databricks and/or SageMaker
Familiarity with generative AI platforms (e.g., AWS Bedrock, Mosaic AI, OpenAI) and frameworks (e.g., LangChain, LangGraph)
Familiarity with ML technologies and ecosystems (e.g., Spark, PyTorch)
Experience with container-based technologies and orchestration (Docker, Kubernetes/OKE)
Data modeling and analytics tooling: Snowflake, Data Vault, Informatica IICS, Power BI, PowerDesigner
Architecture frameworks/certifications: TOGAF or similar; CGI RCDA experience
Knowledge of the insurance business is an asset (e.g., policy, billing, claims, sales, self-serve, telematics, customer experience, document processing, analytics)
Benefits
Flexible work arrangements and a hybrid work model
Possibility to purchase up to 5 extra days off per year
Multiple benefits offered to support physical and mental wellbeing, including telemedicine, Wellness account and much more
Share plan & other savings: up to 12% of salary or even more (ask how you could earn guaranteed income for life)
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