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 USEReady'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.
