Senior data & ai solution architect

Position Overview

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.

Responsibilities

• Solution Architecture Ownership: Design end‑to‑end data and AI solutions (data pipelines, analytics, ML/GenAI use cases). Produce HLDs/LLDs and define NFRs (scalability, performance, security, cost).
• Architecture Decisioning: Lead design decisions and trade‑offs (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 ingestion, lakehouse, ML pipelines, and GenAI patterns (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.

Qualifications

• Required Qualifications
  • 5+ years of experience in data/analytics architecture, with 3+ years designing AI/ML solutions in production (GenAI experience strongly preferred).
  • Bachelor’s degree in computer science, Engineering, Information Systems, Data/AI, or a related field (Master’s preferred).
  • Proven experience architecting on Azure across data and AI services, ideally within financial services and/or insurance.
  • Strong understanding of data governance, data modeling, integration, metadata management, and privacy/security controls; able to extend these practices to AI/GenAI governance.
  • Strong architecture leadership skills: drive decisions, manage trade‑offs, and influence across teams while maintaining delivery focus.
  • Excellent communication and stakeholder management skills, with the ability to translate complex data/AI concepts for technical and non‑technical audiences.
  • Experience with modern engineering practices (IaC, CI/CD), and with MLOps/LLMOps concepts such as model/prompt versioning, evaluation, monitoring, and deployment patterns.
  • Relevant certifications in Azure (Architecture/Data/AI) are a plus.
• Preferred Qualifications
  • Hands‑on experience implementing RAG architectures, vector databases/semantic search, and prompt orchestration frameworks.
  • Experience with lakehouse architectures and data products, domain‑driven/data mesh environments.
  • Familiarity with model risk management, responsible AI frameworks in regulated industries, and Azure certifications (Solutions Architect, Data Engineer, AI Engineer).

Benefits & Culture

Our culture encourages learning, flexibility, inclusion, and growth. Employees receive a comprehensive benefits program that includes healthcare, dental, vision, mental health, disability, life insurance, and retirement plans. Paid leave and a supportive environment for well‑being are also provided.

Salary

Location: Toronto, Ontario
Range: $113,000.00 CAD – $163,000.00 CAD

Equal Opportunity Statement

Manuvie is an equal‑opportunity employer. We value diversity and are committed to ensuring a fair and inclusive hiring process for all candidates, regardless of race, ethnicity, gender, sexual orientation, disability, age, or other protected characteristics.