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Senior AWS DevOps & Platform Engineer

Location: Bangalore, Gurgaon, Mohali, Pune
Experience: 8–12 Years

This role offers the opportunity to work on cutting-edge AWS technologies, modern DevSecOps practices, AI-powered engineering, and enterprise-scale cloud infrastructure while contributing to next-generation AI-driven modernization initiatives.

Role Overview

We are seeking a highly skilled Senior AWS DevOps & Platform Engineer to own the cloud infrastructure, deployment automation, release engineering, platform reliability, and production operations for Pixel Perfect.

In addition to owning the DevOps platform, this engineer will contribute to client’s AI-first engineering initiatives by building intelligent agents, supporting AWS Transform-based modernization programs, and developing automation capabilities that accelerate software delivery, cloud operations, and analytics migration.

You will partner closely with Engineering, Product Management, Customer Success, and Enterprise Customers to ensure secure, scalable, and highly available deployments while driving engineering excellence through automation and AI.

Key Responsibilities

AWS Cloud Platform

• Design, implement, and manage scalable, secure, and highly available AWS infrastructure.
• Manage AWS services including EC2, IAM, VPC, S3, EBS, ALB/NLB, Route53, ACM, WAF, CloudWatch, Auto Scaling, Security Groups, CloudFront and others.
• Optimize cloud architecture for performance, resilience, scalability, security, and cost efficiency.
• Drive AWS operational excellence, governance, and platform standardization.

DevOps & Release Engineering

• Design, build, and maintain enterprise-grade CI/CD pipelines using Jenkins.
• Automate infrastructure provisioning using Terraform and Ansible.
• Containerize applications using Docker and manage deployments through Helm.
• Standardize build, release, deployment, rollback, and environment management processes.
• Implement Infrastructure as Code (IaC) and GitOps best practices.

Platform Reliability & Operations

• Own production deployments across Development, QA, UAT, Staging, and Production environments.
• Monitor platform availability, reliability, and performance.
• Lead incident response, root cause analysis (RCA), and continuous operational improvements.
• Implement proactive monitoring, alerting, logging, and observability solutions.
• Participate in rotational production support for global enterprise customers.

DevSecOps

• Drive secure software delivery throughout the SDLC.
• Perform CVE remediation, dependency upgrades, SAST/DAST remediation, and security hardening.
• Manage SSL/TLS certificates, encryption, secrets management, and identity/access controls.
• Ensure compliance with enterprise security standards and AWS best practices.

Automation & AI Engineering

• Develop automation using Python, Bash, Shell, and PowerShell.
• Build reusable deployment frameworks and self-service engineering tools.
• Eliminate repetitive operational tasks through intelligent automation.
• Build AI agents and autonomous workflows to improve engineering productivity and customer operations.
• Support AWS Transform initiatives for modernization and migration programs.
• Evaluate and implement AI-powered engineering capabilities using Claude, Amazon Bedrock, Amazon Bedrock AgentCore, Amazon Q Developer, and emerging AWS AI services.

Enterprise Customer Support

• Support enterprise customer deployments across Linux and Windows environments.
• Troubleshoot application, infrastructure, networking, and deployment issues.
• Collaborate with Product Engineering to resolve complex production incidents.
• Prepare installation guides, deployment documentation, release notes, operational runbooks, and knowledge base articles.

Required Technical Skills

AWS Cloud

• Amazon EC2, IAM, VPC,S3,EBS,ALB/NLB,Route53,ACM,WAF,CloudWatch,Auto Scaling, CloudFormation (preferred),Cost Optimization, AWS Security Best Practices

DevOps & Automation

• Jenkins, Terraform, Ansible, Docker, Helm, Git, Bitbucket or GitHub

Operating Systems

• Linux (RHEL/Ubuntu), Windows Server,
• Programming & Scripting
• Python, Bash, Shell Scripting, PowerShell

Application Technologies

• Java, Spring Boot, REST APIs, Maven, PostgreSQL, SQL

Packaging & Release Management

• Linux RPM Packaging, Windows Installer (.MSI/.EXE), Versioning, Release Engineering

Monitoring & Observability

• Amazon CloudWatch, ELK, Splunk, Log Analysis, Performance Monitoring, Application Diagnostics

Security

• SSL/TLS, Certificate Management,JKS, CVE Remediation, SAST, DAST, Vulnerability Management

Desired Skills & Emerging Technologies

• Experience with AWS Transform for application modernization, migration assessment, and code transformation.
• Hands-on experience building AI agents, autonomous workflows, or agentic applications using Amazon Bedrock, Bedrock AgentCore, LangGraph, LangChain, CrewAI, AutoGen, or similar agent orchestration frameworks.
• Experience integrating Large Language Models (LLMs) into enterprise applications using Amazon Bedrock or equivalent AI platforms.
• Knowledge of Model Context Protocol (MCP), Retrieval-Augmented Generation (RAG), AI tool integration, and agent communication patterns.
• Experience developing AI-powered automation for DevOps, deployment validation, incident management, engineering productivity, or cloud operations.
• Experience supporting Agentic Migration solutions for application, analytics, or data modernization initiatives.
• Familiarity with AI-assisted software engineering tools such as Amazon Q Developer, GitHub Copilot, Cursor, or similar developer productivity platforms.
• Experience with AWS Lambda, EventBridge, Step Functions, API Gateway, DynamoDB, and OpenSearch.
• Exposure to Kubernetes or Amazon EKS.
• Strong understanding of event-driven and serverless architectures on AWS.
• Passion for evaluating and adopting emerging AWS AI capabilities to improve engineering productivity and customer experience.

Preferred Qualifications

• AWS Certified DevOps Engineer – Professional
• AWS Certified Solutions Architect – Associate or Professional
• Experience supporting enterprise SaaS products.
• Experience working in Agile/Scrum product engineering teams.
• Exposure to Amazon QuickSight or modern BI/Analytics platforms.
• Familiarity with Site Reliability Engineering (SRE) principles and cloud-native operations.

What We Are Looking For

• Strong ownership mindset with the ability to independently drive platform engineering initiatives.
• Passion for automation, cloud engineering, and AI-driven software development.
• Excellent analytical, troubleshooting, and problem-solving skills.
• Ability to work directly with enterprise customers and cross-functional engineering teams.
• Strong communication and stakeholder management skills.
• Ability to thrive in a fast-paced product engineering environment.
• Continuous learner with enthusiasm for cloud innovation, AI, and emerging AWS technologies.
• Ready to support in shift

Why This role?

• Build and scale a modern AWS-native SaaS platform powering enterprise customers worldwide.
• Work on cutting-edge AWS cloud, AI, DevSecOps, and Agentic AI technologies.
• Contribute to next-generation modernization solutions powered by AWS Transform and AI agents.
• Own critical cloud infrastructure, automation, and platform engineering initiatives.
• Influence product architecture, engineering practices, automation strategy, and operational excellence from day one.
• Join a high-performing product engineering team shaping the future of analytics modernization and intelligent software delivery.

Pay: ₹1,800,000.00 - ₹3,000,000.00 per year

Work Location: Hybrid remote in Bengaluru, Karnataka