VP · Platform Engineering & Infrastructure
Pranav
Kalambi
24 years shaping enterprise IT operations, platform reliability & digital transformation across global financial institutions.
24 years shaping enterprise IT operations, platform reliability & digital transformation across global financial institutions.
With 24 years of deep-rooted expertise in Information Technology and Operations, I am a seasoned technology leader who has consistently transformed complex, large-scale infrastructure challenges into strategic business advantages. Born in Mumbai, I have built and commanded high-performing, cross-functional teams spanning IT Managed Services, Service Desk, Networking, Servers, Datacentre Operations, and End-User Computing — steering annual budgets in excess of USD 10 Million with precision and purpose.
My leadership philosophy is simple: technology must serve people. I have served as a trusted strategic partner to senior business stakeholders — architecting long-term technology transformation roadmaps that retire legacy debt and accelerate modernization. From orchestrating large-scale cloud migrations to embedding Site Reliability Engineering (SRE) practices into enterprise DNA, I bring both the vision to inspire and the operational rigour to execute.
I am driven by a relentless pursuit of operational excellence — continuously assessing, rethinking, and elevating application platforms, system performance, and delivery processes to raise the bar on customer experience and organizational resilience.
Lead India's Platform Engineering and Infrastructure Reliability function, owning end-to-end IT Operations, Site Reliability Engineering (SRE), and large-scale automation programs across Mumbai and Bangalore. Accountable for on-premises and hosted Datacentre operations, Network, Servers, and Storage, alongside Production Management and End User Computing for thousands of users. Drive Global Platform Engineering initiatives encompassing Azure cloud deployments, DevOps pipelines, Infrastructure as Code (IaC), Messaging platforms, Kafka, SSL, and Webservices. Spearheading the adoption of intelligent automation and beginning to explore how Generative AI and Agentic AI can augment platform operations — from AI-assisted incident triage to autonomous remediation workflows — to build a more proactive, self-healing infrastructure estate.
Entrusted with full IT Site leadership across two of Barclays' most strategic India locations. Established and matured the Chennai site, then relocated to Mumbai to build the operation from the ground up — scaling it to a seat capacity of 3,800 and a live user base of approximately 4,500 spanning Front, Middle, and Back Office Operations. Delivered mission-critical technology support for Front Office trading, Sales, and Corporate Banking teams, where uptime and precision were non-negotiable. Drove continuous infrastructure upgrades, vendor governance, and service quality improvements, ensuring the Mumbai site operated at the exacting standards expected of a global financial institution.
Played a pivotal role in one of Barclays' most ambitious India expansion programmes — orchestrating the seamless transition of over 3,500 roles from the UK, US, and Middle East into the newly established Chennai Technology Centre. Led complex, multi-geography project streams with tight timelines and high stakeholder visibility. As the site reached full operational capacity, shifted focus to sustaining excellence — managing infrastructure upkeep, driving process improvements, and ensuring the site consistently delivered against evolving business requirements and service level commitments.
Modern infrastructure teams are leveraging Gen AI to automate runbook generation, accelerate incident triage, and synthesize monitoring signals — reducing MTTR and freeing engineers for higher-order work.
Agentic AI systems autonomously execute multi-step IT workflows — from auto-remediation in SRE pipelines to intelligent provisioning of cloud resources — enabling truly self-healing infrastructure at scale.
Combining IaC principles with AI-driven code generation accelerates deployment velocity, reduces configuration drift, and enables policy-as-code enforcement across hybrid cloud environments.
AIOps platforms use ML to correlate alerts, predict failures before they surface, and intelligently route escalations — aligning well with the SRE model and platform engineering disciplines.