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Platform Engineering Manager

Sia Partners

Sia Partners

Software Engineering
Mumbai, Maharashtra, India
Posted on Feb 5, 2026

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.