Manulife
Financial Services
SeniorData&AISolutionArchitect
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Data & AI Solution Architect at Manulife. Skills: Data architecture, AI architecture, GenAI solutions, Azure solutions. Design end-to-end data and AI solutions. Produce HLDs/LLDs”
Industry & Context.
Resolve trade-offs; Resolve technical blockers
What They're Looking For.
Must Have
5+ years data/analytics architecture, 3+ years designing AI/ML solutions, Proven experience architecting on Azure, Understanding of data governance, Architecture leadership skills, Excellent communication skills, Stakeholder management skills, Experience with modern engineering practices, Experience with MLOps/LLMOps concepts
Nice to Have
Master's degree preferred, GenAI experience strongly preferred, Experience in financial services, Experience in insurance, Azure certifications, Hands-on experience implementing RAG architectures, Hands-on experience implementing Vector databases, Hands-on experience implementing Prompt orchestration frameworks, Experience with Lakehouse architectures, Experience with data products, Experience with Domain-driven environments, Experience with data mesh environments, Familiarity with Model risk management, Familiarity with Responsible AI frameworks, Azure Solutions Architect certification, Azure Data Engineer certification, Azure AI Engineer certification
What You'll Do.
Design end-to-end data and AI solutions
Lead design decisions
Review solution designs
Approve solution designs
Guide engineering teams
Guide data science teams
Resolve technical blockers
Ensure production readiness
Implement ingestion patterns
Implement lakehouse patterns
Implement ML pipeline patterns
Implement GenAI patterns
Architect solutions leveraging Azure
Define CI/CD patterns
Define IaC-based deployment patterns
Design data contracts
Design event-driven architectures
Ensure interoperability
Embed security controls
Embed privacy controls
Embed AI governance controls
Define monitoring strategies
Define observability strategies
Define cost optimization strategies
How You'll Work.
Team & Collaboration
Across teams; With stakeholders
Communication Scope
Translate complex concepts
Full Job Description
The Senior Data & AI Solution Architect is accountable for designing and governing end-to-end data and AI solutions that translate business requirements into secure, scalable, and production-ready architectures. This role operates as the hands-on architecture authority across the solution lifecycle, driving design decisions, defining solution blueprints, resolving trade-offs, and guiding engineering and data science teams through implementation. The architect ensures solutions are aligned with enterprise standards, regulatory expectations, and operational readiness, while enabling the delivery of modern data platforms, analytics, and AI/GenAI use cases. **Position Responsibilities:** **Solution Architecture Ownership** * Design end-to-end data and AI solutions (data pipelines, analytics, ML/GenAI use cases). * Produce HLDs/LLDs, define NFRs (scalability, performance, security, cost). **Architecture Decisioning** * Lead design decisions and trade-offs (e.g., batch vs streaming, cost vs performance). * Review and approve solution designs aligned with enterprise standards. **Delivery & Implementation Support** * Guide engineering and data science teams during build and deployment. * Resolve technical blockers and ensure production readiness. **Applied Data & AI Patterns** * Implement patterns for ingestion, lakehouse, ML pipelines, and GenAI (RAG, vector search). * Enforce MLOps/LLMOps (versioning, evaluation, monitoring). **Azure Solution Design** * Architect solutions leveraging Azure (ADLS, Databricks, Synapse/Fabric, Azure ML/OpenAI). * Define CI/CD and IaC-based deployment patterns. **Integration & Data Governance** * Design API, data contracts, and event-driven architectures. * Ensure data quality, lineage, and interoperability. **Security & Responsible AI** * Embed security, privacy, and AI governance controls (model risk, guardrails). **Operational Readiness** * Define monitoring, observability, and cost optimization strategies. **Required Qualifications:** * 5
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