Sia

Technology

StaffDevOpsEngineer

₹35–55L ~AI est. Mumbai, Maharashtra, India FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for mid candidates.

The Brief

“Staff DevOps Engineer at Sia”

Industry & Context.

Technology
Full Job 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. We are hiring a Staff DevOps Engineer for the AI Factory product team, responsible for architecting, scaling, and standardizing the cloud and platform foundations that power AI-driven products and internal platforms. This is a senior individual contributor role with org-level technical influence. The Staff DevOps Engineer operates beyond a single product or squad, shaping platform strategy, reliability standards, CI/CD foundations, and cloud cost governance across the AI Factory. The role is hands-on where it matters most, while also acting as a technical authority and escalation point for complex infrastructure, deployment, and reliability challenges. Key Responsibilities * Architect and evolve cloud-native platform foundations supporting AI Factory products and internal platforms * Define and enforce DevOps standards across environments: CI/CD, deployment patterns, observability, security, and cost controls * Design scalable infrastructure patterns for multi-service, multi-environment systems * Act as the final escalation point for complex infrastructure and reliability issue * Own architecture and best practices across AWS / GCP / Azure (multi-cloud exposure) * Design highly available, secure, and cost-efficient infrastructure * Drive reliability engineering practices: SLOs, SLIs, incident response, post-mortems, and resilience planning. * Identify systemic risks early (

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