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MUMBAI: Streaming a cricket match to millions at once leaves little room for error. Tony Thomas has done exactly that, and now he is turning his attention to a new test: making artificial intelligence (AI) work for a media company. He has joined Zee Entertainment Enterprises Limited as head of AI transformation, a role he took up in October 2026 in the Mumbai region. It is also a homecoming of sorts, since he spent nearly three years at ZEE5 before moving to Jio.
His credentials come from a hard school. Thomas spent four years and three months at Jio, from August 2022 to October 2026, as associate vice-president and head of infrastructure, DevOps and quality. He ran DevOps, site reliability engineering (SRE) and quality across Jio’s media business, covering 16 products that include JioTV, JioTV+, JioNews, LiveTV and related streaming and software-as-a-service offerings. The systems ran on multi-region Google Cloud Platform (GCP) infrastructure in Mumbai and Delhi, supported by Azure DevOps for continuous integration and delivery, and on-premises data centre capacity.
The big events were the proof. Thomas owned the cloud infrastructure for FIFA 2022 and IPL 2023 on JioCinema, with loads of multi-million concurrent users. The work included multi-CDN edge delivery, performance tuning and capacity planning for extreme peaks. His own mandate, he says, has been simple: build large-scale systems that do not break when millions of users log on. Over 17 years in OTT, streaming and content delivery networks (CDN), he says, that rule has held.
The technology stack he lists reads like a modern cloud engineer’s kit: GCP and GKE, Kubernetes, Helm, Argo CD, Terraform and Terragrunt, Kafka, DragonflyDB, New Relic and multi-CDN delivery, with Azure DevOps for pipelines, work items and test plans.
Now comes the part most relevant to Zee. Thomas says his energy is dedicated to reshaping engineering around AI. Over the past year, he says, he transformed his organisation to make AI a first-class engineering practice instead of a side experiment. That meant restructuring team design, hiring and daily workflows. He embedded AI agents across the software development lifecycle and made spec-driven development the default. He also built internal skills and tooling that, in his words, compound team output.
His staffing idea deserves attention. Thomas reframed a multi-year DevOps staffing plan in AI-native terms and designed a squad structure that compounds output, instead of the usual belief that more headcount means more throughput. Many companies are still asking how many people they need. Thomas is asking how much each team can do. That is a better question, and it is one Zee can use.
In quality, he built AI-driven workflows with real practical value. They include daily status automation, test case and test script generation directly from API specifications, gap analysis against existing coverage, and incremental updates that keep test suites in line with shipping code without manual rewriting. Quality testing is often the slow part of a software release. Speeding it up helps products reach users sooner.
His roots in quality run deep, and they go back to 2006. He started as a senior test analyst at Atidan Technologies Pvt Ltd, where he spent five years and eight months, until January 2012. He was a QA engineer in tech at Everyday Health for a year, and a senior QA engineer at Ness Technologies (India) Pvt. Ltd. from January 2013 to September 2015. At BookMyShow he spent three years and four months, first as team leader for quality analysis and then as assistant manager for quality. At Turtlemint he was principal QA automation engineer from December 2018 to January 2020.
At ZEE5, Thomas spent two years and eight months from January 2020, first as engineering manager for quality and then, from June 2021 to August 2022, as architect for DevOps and quality. His tasks included leading the DevOps team for Zee5’s infrastructure, setting quality standards, and creating a CI/CD roadmap for all microservices, with Terraform scripts for AWS infrastructure. He also built a highly scalable, high-availability setup, introduced API documentation standards, and automated releases across stages with the Atlassian tools JIRA, BitBucket and Confluence. He says his leadership philosophy is pragmatism over engineering theatre, and designing teams that work AI-natively from day one rather than retrofitting it later.
The match is easy to see. Zee needs someone who knows its technology, understands streaming at scale and has already run an AI-first engineering team. Thomas knows ZEE5 from inside, ran streaming at a huge scale at Jio and has put AI into daily work. He says he is deeply focused on the operational redesign needed to make AI transformation real, including how technical leaders scope and review work when AI acts as a principal collaborator. He thanks the people he worked with at Jio and says he looks forward to diving into AI-driven strategies and building the next wave of tech innovation at Zee. For a company that wants its technology to work harder, that is a promising start.
