Data & AI Platform Solution Architect

Shakudo

Toronto

On-site

CAD 120,000 - 180,000

Full time

14 days+

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Job summary

Shakudo is seeking a Solution Architect to join our Stack team as the technical anchor for customers, translating data and AI infrastructure challenges into production-ready solutions on the Shakudo platform. You will bridge Kubernetes, Helm, and cloud infrastructure with strategic customer conversations to drive adoption and account growth.

You will own the technical relationship for assigned accounts, guiding architecture, integration, and delivery while collaborating with Product and

Qualifications

4–8 years of experience in solution engineering, solution architecture, or a senior engineering role with significant client-facing responsibility.
Strong Kubernetes and Helm Chart development and deployment experience.
Experience with cloud platforms (AWS, GCP, or Azure), CI/CD pipelines, and infrastructure as code.

Responsibilities

Design and deliver end-to-end technical solutions on the Shakudo platform that address real-world data and AI challenges for enterprise customers.
Integrate open-source and proprietary components seamlessly with the Shakudo platform using Kubernetes, Helm Charts, and infrastructure-as-code.
Build elegant, production-ready solutions — not just proof-of-concepts — that customers rely on in production.
Contribute to architectural decisions and establish design patterns for platform development with high autonomy.
Serve as the trusted technical advisor for assigned accounts — understand their infrastructure, roadmap, and pain points deeply.
Diagnose and resolve complex technical issues customers face in their data and AI stack, from Kubernetes orchestration to pipeline performance.
Identify opportunities to expand Shakudo’s footprint within existing accounts by connecting customer needs to platform capabilities.
Navigate customer organizations effectively — from individual contributors to engineering leaders and C-suite decision-makers.
Champion customer needs internally, influencing product direction and Stack team priorities.
Partner with Product and Engineering teams to translate customer requirements into scalable, robust systems.
Collaborate with Customer Engineering to ensure smooth hand-offs and consistent solution quality.
Contribute to internal knowledge bases, solution patterns, and best practices that accelerate delivery across the team.