PepsiCo Recruitment 2026 | Cloud Delivery Engineer (Azure/AWS) | Experienced Roles
Job Description
Eligibility Criteria
Top engineering graduates possessing a Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related technical discipline.
A minimum of 8+ years of robust experience in IT, with at least 4 years explicitly dedicated to deploying advanced multi-cloud technologies.
Proven engineering expertise across both Amazon Web Services (AWS) and Microsoft Azure frameworks, with a sharp focus on scaling intelligent platforms.
Elite professional certifications, such as AWS Certified Solutions Architect – Professional or Azure Solutions Architect Expert, are highly preferred.
Comprehensive knowledge of infrastructure as code (IaC) tools like Terraform, CloudFormation, or ARM templates alongside proficiency in Python, Bash, or PowerShell scripting.
Job Responsibilities & Core Skills Required
Multi-Cloud Resource Provisioning: Architect, design, and provision scalable cloud infrastructure components on AWS and Azure, ensuring total alignment with strict organizational architecture and governance standards.
Deploy Advanced Machine Learning Algorithms: Build, experiment with, and integrate highly sophisticated AI models and deep learning algorithms directly into live production environments to resolve complex business constraints.
Secure AI Infrastructure & Guardrails: Formulate and implement advanced cloud security principles, compliance guardrails, and risk mitigation strategies to safe-keep distributed multi-cloud assets.
Optimize Cloud Infrastructure & Costing: Actively participate in strategic capacity planning and data platform cost-optimization models to keep modern data science operations highly efficient.
Vector Database & Search Integration: Deploy and maintain high-volume vector databases, specifically Datastax HCD, to drive modern workflows like Intelligent Search, Intelligent Document Processing, and Media Intelligence systems.
Enterprise Software Development for DevOps: Leverage foundational AWS compute, networking, and serverless resources including Amazon Bedrock, SageMaker, App Runner, and AWS Lambda to build robust automated CI/CD pipelines.
Application Process Overview
Securing a high-profile spot within PepsiCo's AWS artificial intelligence specialist division demands a methodical preparation strategy. Start by streamlining your resume to prominently display your multi-cloud expertise, vector database familiarity, and deep automation capabilities.
The screening timeline involves multiple technical evaluation phases designed to assess your systems architecture mastery, script writing fluidity, and secure environment provisioning workflows. Candidates will also face an in-depth scenario-based architectural interview with cross-functional data science and software development leaders.
To forward your professional application directly to the corporate recruitment engine, please scroll down to the bottom of this page. Click the "Apply Now" button located in the official section below to launch your candidate registration form.
Conclusion
Stepping into the Cloud Delivery Engineer role at PepsiCo is an excellent move for senior professionals aiming to lead the future of enterprise software development and AI systems. Fine-tune your architectural concepts, highlight your multi-cloud milestones, and submit your application today.
Frequently Asked Questions (FAQs)
1. What specific cloud environments will the Cloud Delivery Engineer manage at PepsiCo? This role horizontally spans across a dual-platform setup, demanding equal execution fluency in both Amazon Web Services (AWS) and Microsoft Azure infrastructure ecosystems.
2. Is this position open to remote work or hybrid flexibility? According to the latest corporate updates from the PepsiCo talent acquisition team, this Cloud Delivery Engineer position is structured as a full-time, on-site role based in Hyderabad.
3. What AI-specific tools are required for this cloud architecture career path? Candidates must possess hands-on proficiency with Amazon Bedrock, SageMaker, Vector Databases (such as Datastax HCD), and have a solid foundation in building deployments for Intelligent Document Processing and Content Moderation.