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Open nowPosted 112 days ago

AI Cloud Engineer

KData Inc.30 open roles

Where
Toronto, Ontario, Canada
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Your applicationOpen nowAI Cloud EngineerKData Inc. · Toronto, Ontario, Canada
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  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: posted 112 days ago

The posting

Role Overview We are looking for an AI Cloud Engineer to support our AI infrastructure and platform engineering needs. This role is distinct from traditional cloud engineering: the AI platform team builds custom, Python-based AI products and services — for example, AI gateway and AI guardrail-type capabilities — that are consumed by many lines of business across our clients. The ideal candidate blends strong AI/ML development skills with working cloud knowledge, and is comfortable customizing open-source tooling or integrating third-party AI platforms into production-grade services. Key Responsibilities • Design and build custom, Python-based AI platform services consumed by multiple internal lines of business (e.g., AI gateway- and AI guardrail-type services) • Customize open-source AI tooling and integrate with third-party AI providers to deliver production-grade platforms • Integrate AI platform services with enterprise systems such as SharePoint and SQL/PostgreSQL databases • Apply platform-engineering principles — defining clear requirements that consuming application teams must satisfy to safely use the platform • Bring working cloud knowledge to ensure AI services integrate cleanly with the broader cloud environment • Operate within clients • 's enterprise governance, security, and change-management frameworks as a platform service provider AI & Platform Development Skills • Python — strong, hands-on development experience (top priority) • Demonstrated experience building or customizing AI/ML-driven products or platforms • Experience integrating open-source AI frameworks and/or third-party AI platforms (e.g., Cohere or similar) into production services Platform-engineering mindset: experience defining clear consumption requirements so other applications/teams can safely integrate with the platform Requirements Enterprise Cloud Engineering Fundamentals (Required) Client's AI platform work still runs inside a large, regulated banking environment. Beyond core AI/Python skills, candidates are expected to bring the same enterprise cloud discipline required across our banking engagements — this is not optional exposure, it's a baseline: • Working knowledge of cloud service integration in an enterprise setting (e.g., SharePoint, SQL, PostgreSQL, Azure) • Enterprise-scale delivery mindset: building for many consuming teams/lines of business, not a single application • Security posture and compliance awareness for regulated industries: vulnerability management, RBAC / least-privilege access, audit readiness • Observability fundamentals: logging, monitoring, and alerting for production platform services • Identity and access management basics (Azure AD/Entra ID or equivalent) for securing platform endpoints • Comfortable operating within formal change-management/ITSM and documentation standards expected by large banking clients • Full SDLC fluency, including requirement gathering and cross-team architecture discussions • Strong written communication — detailed documentation and ticket-level updates expected by enterprise stakeholders • Formal cloud platform experience beyond working knowledge (Azure, GCP, or AWS), e.g., Infrastructure-as-Code / Terraform exposure Preferred / Nice to Have • Prior banking or financial-services experience • Lead-level experience: TL/Architect-level capability plus current hands-on delivery, with proven ability to manage 2–3 engineers

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