Database/Compute -Sr. Engineer

PepsiCo Inc.

Hyderabad

On-site

INR 1,500,000 - 2,900,000

Full time

14 days+

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Job summary

PepsiCo is seeking an automation and AI-focused DevOps engineer to design and scale Ansible-based automation across cloud and on-prem environments. You will implement robust playbooks, modular roles, and CI/CD integrations to improve reliability and speed of deployments.

You will collaborate with infrastructure, applications, and security teams, applying AI-assisted workflows and RAG-based data pipelines to optimize operations, monitoring, and incident response.

Qualifications

  • Bachelor's degree in CS, Engineering, Data Science, or related field.
  • Strong Python, SQL, and ML fundamentals with experience in AI/LLM tooling.
  • Expertise with Ansible, automation design patterns, and CI/CD integrations.

Responsibilities

  • Accelerate infrastructure provisioning and automation using Ansible and AI-driven workflows.
  • Collaborate across infra, cloud, and service management teams to scale automation.
  • Deliver enterprise-grade automation, observability, and secure deployment practices.

Skills

Ansible
Python
CI/CD
AI/ML basics
Cloud (AWS/Azure)

Education

Bachelor's degree in CS/Engineering/Data Science

Tools

Azure DevOps
GitHub Actions
OpenSearch/Pinecone

Job description

Overview
  • Develop and maintain robust Ansible-based automation frameworks for provisioning, configuration, patching, and operational tasks
  • Design and build reusable, modular Ansible roles and playbooks to ensure consistency, scalability, and maintainability
  • Implement idempotent automation with proper error handling, conditional execution, and logging to ensure reliable production workflows
  • Manage source control, branching strategies, and CI/CD integrations using Azure Repos and GitHub
  • Optimize existing Ansible code for performance and efficiency by reducing unnecessary API calls, leveraging native modules, and minimizing reliance on raw Linux/command-based execution
  • Design and implement enterprise-scale DevOps and automation architecture across cloud and infrastructure environments
  • Integrate automation workflows with ServiceNow for ticket-driven execution, updates, and operational alignment
  • Understand connection handling, authentication, and credential management for database-integrated applications
  • Assist in implementing and validating database monitoring, alerting, and logging integrations
  • Contribute to automation of routine database operational tasks where applicable (e.g., validation, status checks, reporting)
  • Collaborate with cross-functional teams (infra, cloud, application, and service management teams) to drive automation adoption
  • Implement alert-based automation for both compute and database environments, enabling automated response to events such as failures, threshold breaches, and health issues
  • Familiarity with leveraging AI assistants, copilots, or automation insights to optimize DevOps workflows, troubleshooting, and operational dashboards
  • Design and develop end-to-end Generative AI solutions using LLMs.
  • Build and optimize RAG pipelines utilizing vector databases and enterprise knowledge sources.
  • Fine-tune, evaluate, and deploy foundation models for domain-specific use cases.
  • Develop scalable data pipelines for ingestion, transformation, embedding generation, and retrieval.
  • Implement prompt engineering, agentic workflows, and AI orchestration frameworks.
Responsibilities
  • Accelerate infrastructure provisioning and operational workflows through automation.
  • Reduce manual effort through AI-powered operational intelligence. Improve incident response using event-driven automation.
  • Enable enterprise knowledge discovery through RAG-based AI assistants. Deliver scalable, secure, and production-ready Generative AI solutions that drive measurable business value.
Qualifications
  • Bachelor's in Data Science, Artificial Intelligence, Engineering, or related field
  • Python, SQL Machine Learning & Deep Learning Generative AI & LLMs RAG Architecture LangChain, Lang Graph, LlamaIndexVector Databases (OpenSearch, Pinecone, Chroma DB, FAISS)AWS Bedrock, Sage Maker, Lambda, ECS/EKS MLOps & CI/CDGitHub, Azure DevOpsREST APIs and Microservices
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