Cloud Engineering Specialist - AI & Site Reliability Engineering

BT Group; Bengaluru; On-site; INR 2,500,000 - 4,200,000; Full time

Job summary

BT Group in Bengaluru seeks a Cloud Engineering Specialist to establish SRE standards, drive reliability, observability, and operational excellence. You will design and validate Generative AI models within AWS, creating scalable baselines that accelerate Product Development Lifecycle optimization across the organization.

You will lead AI/ML initiatives, develop scalable data pipelines, and collaborate with cross-functional teams to deliver AI-driven transformation and improved operational

Qualifications

• Proven hands-on experience in designing, developing, and deploying ML/DL solutions in enterprise environments.
• Strong understanding of Generative AI, LLMs, Retrieval-Augmented Generation (RAG), and AI-powered automation frameworks.
• Experience building and managing scalable data pipelines capable of processing large volumes of structured and unstructured data.
• Proficient in Python and/or Java for production-grade AI and data-driven applications.
• Experience deploying AI/ML solutions on AWS including SageMaker, Bedrock, Lambda, S3, EC2, EKS, ECS.

Responsibilities

• Explore, understand, and implement recent ML algorithms for supervised/unsupervised learning and deep learning.
• Develop and deploy ML models (regression, classification, clustering, etc.).
• Use AI and big data to identify opportunities and optimize operations.
• Design and optimize scalable AI pipelines on AWS.
• Stay updated on AI advancements and apply them to business goals.
• Troubleshoot and optimize AI models for performance and accuracy.
• Build trusted advisory relationships with stakeholders and sponsors.
• Provide strategic guidance on AI-driven transformation and technology innovation.

Skills

ML/DL development

Generative AI

AWS SageMaker

Python/Java

DevOps

Cloud architecture

Tools

SageMaker

Bedrock

Lambda

S3

EC2

EKS

ECS

Job description

Cloud Engineering Specialist Job Req ID: 61685 Posting Date: 20 Aug 2026 Location: Bengaluru Salary: Competitive

About the role

You will establish and drive the standards, frameworks, and best practices that underpin the Site Reliability Engineering (SRE) function. Working collaboratively across multiple technology teams and closely with the Service Assurance organization, you will ensure the consistent adoption of reliability, observability, and operational excellence disciplines while fostering a culture of continuous improvement and cross-functional collaboration. You will actively contribute to the design, development, and validation of Generative AI models within the AWS cloud environment, creating scalable baseline frameworks that support and accelerate Product Development Lifecycle (PDLC) optimization initiatives across the organization. The role is responsible for ensuring the use of AI and big data to aggregate observational data (from monitoring systems output, job logs, syslog, etc.) and engagement data (from ticketing, incident, and event recording system data) to produce a virtuous circle of continuous insights yielding continuous improvements and fixes. This role will lead the implementation of state-of-the-art AI and Generative AI techniques to unlock value from enterprise data, developing innovative approaches that improve operational efficiency and decision‑making. Leveraging a combination of technical expertise, analytical judgment, and experimentation, the role will evaluate, select, and implement the most effective technologies, methodologies, and solutions to support business objectives and accelerate continuous improvement initiatives.

What you’ll be doing

• Explore, understand, and implement the most recent machine learning algorithms and approaches for supervised and unsupervised machine learning and deep learning.
• Develop and implement machine learning algorithms and models. (Regression, classification, clustering, etc).
• Use AI and big data to identify opportunities and work with partner teams to optimise operations.
• Design and optimise scalable AI pipelines for processing and analysing large-scale datasets on the AWS platform.
• Conduct research to stay up to date with the latest advancements in AI.
• Troubleshoot and optimise AI models and pipelines for performance and accuracy.
• Identify and develop trusted adviser relationships with relevant stakeholders, management sponsors and senior executives.
• Build and maintain trusted advisor relationships with key stakeholders, management sponsors, and senior executives, providing strategic guidance on AI‑driven transformation, operational optimisation, and technology innovation

Essential Skills / Experience

• Proven hands‑on experience in designing, developing, and deploying Machine Learning and Deep Learning solutions within enterprise environments.
• Strong understanding of Generative AI technologies, Large Language Models (LLMs), Retrieval‑Augmented Generation (RAG), and AI‑powered automation frameworks.
• Experience building and managing scalable platforms and data pipelines capable of processing and analysing large volumes of structured and unstructured data.
• Strong programming expertise in Python and/or Java, with experience developing production‑grade AI and data‑driven applications.
• Demonstrated experience deploying and managing AI/ML solutions on AWS, including services such as SageMaker, Bedrock, Lambda, S3, EC2, EKS, and ECS.
• Experience developing innovative solutions from concept through implementation, including architecture design, experimentation, deployment, and continuous optimisation.
• Strong understanding of DevOps principles, containerization technologies, and cloud‑native architectures.
• Ability to collaborate effectively with cross‑functional teams and influence stakeholders at all levels while driving AI‑led transformation initiatives.

Desirable Skills / Experience

• Experience working with Agentic AI frameworks and multi‑agent architectures.
• Knowledge of Amazon SageMaker for machine learning model development, training, and deployment.
• Experience implementing and managing CI/CD pipelines to support automated testing, deployment, and release processes.
• Familiarity with Apache Airflow or similar workflow orchestration tools for managing data and AI pipelines.
• Understanding of Quality Assurance (QA) methodologies, testing frameworks, and best practices for AI/ML solutions.
• Exposure to MLOps practices, including model monitoring, versioning, and lifecycle management.
• Experience with workflow automation, model operationalisation, and production‑scale AI deployments.
• Knowledge of AI governance, model validation, and responsible AI practices.
• Familiarity with Agile delivery methodologies and modern software engineering best practices.

BT is the UK’s leading communications group and the holding company behind some of the country’s most recognised brands – including BT, EE, Openreach and Plusnet. Our purpose is as simple as it is ambitious: we connect for good. Our customers include consumers, small, medium and large businesses, public sector organisations and other communications providers. Having come through the most capital‑intensive phase of our fibre investment, our focus now is on what comes next – simplifying how we operate, using technology and AI to work smarter, and organising ourselves to serve customers better and grow sustainably. We have a singular culture that unites all our people: we are customer‑first challengers, who are committed, clear and connected. These behaviours unite us as one team to deliver for our colleagues, our customers, our stakeholders and the country. Joining BT means working at the heart of a business that matters to the UK, with the opportunity to shape decisions, influence outcomes and help set the future course of one of the country’s most important companies.

Experience Level Mid Level