Platform Engineering Manager at Sia Partners - Canada

Mumbai, maharashtra, India -

Full Time

Start Date

Immediate

Expiry Date

21 Jul, 26

Salary

0.0

Posted On

22 Apr, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Platform Engineering, DevOps, SRE, Cloud Architecture, AWS, Azure, GCP, Terraform, Docker, Kubernetes, CI/CD, Python, Linux, MLOps, Leadership, Stakeholder Management

Industry

Business Consulting and Services

Description

Company Description Sia is a next-generation, global management consulting group. Founded in 1999, we were born digital. Today our strategy and management capabilities are augmented by data science, enhanced by creativity, and driven by responsibility. We’re optimists for change and we help clients initiate, navigate, and benefit from transformation. We believe optimism is a force multiplier, helping clients mitigate downside and maximize opportunity. With expertise across a broad range of sectors and services, our consultants serve clients worldwide. Our expertise delivers results. Our optimism transforms outcomes. Job Description Sia Partners is looking for a Platform Engineering Manager to support the design and delivery of next-generation AI and Generative AI platforms within Sia’s AI Factory. This role is pivotal in bridging high-level product vision with robust, cloud-native engineering execution. As a Platform Engineering Manager, you will be responsible for building and evolving internal development and MLOps platforms that improve automation, scalability, reliability, and developer productivity. You will operate as a player-coach, combining hands-on technical leadership with people management and strategic ownership. This is a product-focused role, working closely with product managers, data scientists, ML engineers, application engineers, and security teams to deliver platform capabilities that directly support AI, data, and software workloads Key Responsibilities Leadership of Platform / DevOps / SRE engineering teams, ensuring delivery excellence and strong engineering culture Ownership of internal platform products, working closely with product, application, and data engineering teams to deliver scalable, reliable, and secure platform capabilities. Support to Data Scientists, ML Engineers, Data Engineers, and Software Engineers by providing reliable, scalable, and easy-to-use platform services Definition and execution of the platform engineering strategy and roadmap, aligned with business and delivery objectives Development and operation of internal developer platforms enabling automation, self-service, and scalability Support to Data Scientists, Data Engineers, and Software Engineers by providing reliable, secure, and scalable platforms Cloud services: architecture and operations across AWS, Azure, and GCP, including compute, storage, networking, access management, cost monitoring, and cost optimization Infrastructure as Code: design, standardization, and governance using Terraform Containers: containerization and orchestration of applications using Docker and Kubernetes, including Kubernetes platform ownership CI/CD: definition and standardization of continuous integration and deployment pipelines Observability & reliability: monitoring, logging, alerting, and application of SRE principles to ensure availability, performance, and resilience Contribution to technological, architectural, and governance decisions to address the challenges of scaling AI and data platforms Collaboration with product, application, data, and security teams to gather requirements and deliver platform capabilities Planning and management of platform initiatives, including timelines, resourcing, and budget oversight Mentoring engineers and fostering knowledge sharing and continuous improvement. Qualifications Experience: 8+ years of experience in the data/software space, with at least 3+ years in a formal people management or technical leadership role leading Data Science or ML teams. Strong hands-on experience with cloud platforms (AWS, Azure, and/or GCP) Strong expertise in Infrastructure as Code, preferably Terraform Solid experience with Docker and Kubernetes Experience designing and operating CI/CD pipelines Proficiency in Python scripting and strong Linux fundamentals Good understanding of SRE principles, reliability, scalability, and security best practices AI-Native Engineering Leadership: Experience managing teams that utilize Cursor, GitHub Copilot, or Claude Code as a core part of their daily workflow. Strong communication, leadership, and stakeholder management skills Fluency in English, written and spoken. Additional Information What Success Looks Like Platform Ownership: Treats platform capabilities as long-lived products, not one-off infra projects. Enablement Mindset: Measures success by how effectively product teams ship using the platform. Strong Technical Judgment: Understands platform trade-offs across scalability, reliability, security, and cost. Production Readiness: Ensures platforms are production-grade (deployment, monitoring, rollback, lifecycle). Reliability & Operations: Owns uptime, incident response, post-mortems, and continuous improvement. Developer Experience: Reduces friction in CI/CD, environments, tooling, and self-service workflows. Cost & Efficiency Awareness: Balances performance with cloud and compute cost optimization Roadmap & Prioritization: Aligns platform roadmap with product needs and AI Factory growth. Team Leadership: Builds and grows strong platform, DevOps, and infra engineers. Calm Ownership: Leads with clarity and accountability during incidents and scale challenges. What We Offer Opportunity to lead cutting-edge AI projects in a global consulting environment. A dynamic and collaborative team environment with diverse projects. Sia is an equal opportunity employer. All aspects of employment, including hiring, promotion, remuneration, or discipline, are based solely on performance, competence, conduct, or business needs.

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Responsibilities

Lead platform, DevOps, and SRE engineering teams to deliver scalable, reliable, and secure AI and Generative AI platforms. Collaborate with cross-functional teams to define platform strategy, manage roadmaps, and foster an engineering culture of continuous improvement.