Technical Architect & Engineering Lead
Job Description
Our client is seeking a Technical Architect & Engineering Lead to support the delivery of modern cloud, data, and AI solutions across a wide range of client engagements. This is a high-impact role that blends hands-on engineering with solution architecture and delivery oversight.You’ll be joining a boutique consultancy that works at the intersection of business strategy and advanced technology, helping organizations harness value from cloud-native platforms, machine learning, and generative AI.
This role offers the chance to shape and implement forward-thinking solutions that make an immediate business impact—ideal for someone who enjoys both building and leading.
This role requires hybrid work from the client's office in downtown Vancouver. Candidates must be elligible to work in Canada.
Responsibilities:
Architecture & Solution Design (25%)
Design scalable, cloud-based solutions across modern data and AI platforms (e.g. GCP, Snowflake, Databricks)
Align technical architecture with real-world business needs and implementation constraints
Translate functional requirements into actionable engineering strategies, infrastructure, and design patterns
Develop and deploy core solution components (pipelines, APIs, model endpoints, orchestration layers)
Prototype and productionize ML and GenAI solutions using modern tooling
Implement engineering best practices, including Dev Ops, CI/CD, testing, and Infrastructure as Code (IaC)
Lead technical execution across multi-stream delivery projects
Collaborate directly with client-side stakeholders to ensure technical feasibility and alignment
Act as a trusted technical advisor across engagements
Provide mentorship to engineering and data team members
Share knowledge through documentation, code reviews, and solution demos
Contribute to reusable internal tools, frameworks, and playbooks
5+ years of experience delivering cloud-native data or AI solutions, ideally in a consulting or multi-client environment
Deep expertise in:
Data Engineering: ETL/ELT, APIs, orchestration, structured/unstructured data
Applied AI/ML: model development, deployment, tuning, and monitoring
GenAI Frameworks: such as Lang Chain, Llama Index, Agent Space, etc.
Solution Architecture & Dev Ops
Hands-on experience with at least one major cloud platform (GCP or Azure)
Proficiency with Dev Ops practices, CI/CD workflows, Docker, and Infrastructure as Code (e.g., Terraform)
Strong system design and documentation skills
Comfortable engaging with both technical and non-technical stakeholders
Familiarity with Agile or iterative delivery models
Exposure to multi-cloud environments (Azure, AWS)
Familiarity with tools such as dbt, Looker, Airflow, or Dagster
Experience with MLOps or Vector Databases (e.g., Pinecone, Weaviate)
Google Cloud certifications (e.g., Professional Data Engineer, ML Engineer)
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