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/EKSMLOps &
- CI/CDGitHub, Azure DevOpsREST APIs and Microservices

📌 Database/Compute -Sr. Engineer (Telangana)
🏢 PepsiCo
📍 Telangana