Project Role : Custom Software Engineer
Project Role Description : Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs.
Must have skills : Amazon Web Services (AWS)
Good to have skills : NA
Minimum 7.5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
As a Senior AWS Full-Stack, DevOps and MLOps Engineer, a typical day involves developing Python-based cloud applications and APIs, designing AWS platforms, deploying containerized workloads on Amazon EKS, automating infrastructure and delivery pipelines, and building reliable MLOps capabilities. The role requires collaboration with application, data science, platform, security, architecture, and operations teams to deliver scalable, secure, and highly available solutions. The engineer combines strong AWS and Python development expertise with Kubernetes, DevOps, Infrastructure as Code, CI/CD, and end-to-end machine-learning lifecycle practices. Technical leadership, platform ownership, stakeholder alignment, mentoring, and continuous improvement are key aspects of the role.
Roles & Responsibilities:
Expected to be an SME, collaborate with multiple teams, and manage the team to perform effectively.
Responsible for technical and team-level decisions across AWS application development, DevOps, Kubernetes, Amazon EKS, and MLOps delivery.
Engage with application, data science, platform, security, architecture, and operations teams and contribute to key technical decisions.
Provide solutions to complex development, infrastructure, deployment, machine-learning lifecycle, performance, availability, and production problems across teams.
Design and develop Python-based backend services, REST APIs, serverless applications, automation utilities, data/ML services, and microservices on AWS.
Design, build, deploy, and operate containerized application and ML workloads using Docker, Kubernetes, Amazon EKS, Helm, and automated delivery pipelines.
Design and maintain secure, scalable, highly available, resilient, and cost-aware AWS cloud architectures.
Create and manage Infrastructure as Code using AWS CDK, Terraform, or AWS CloudFormation.
Design and maintain CI/CD pipelines using AWS CodePipeline, AWS CodeBuild, Jenkins, GitHub Actions, or equivalent tools.
Build MLOps pipelines for model training, validation, packaging, registry, deployment, monitoring, retraining, rollback, and governance.
Implement AWS and MLOps services using Amazon SageMaker, SageMaker Pipelines, Model Registry, endpoints, S3, ECR, Lambda, API Gateway, Step Functions, EventBridge, SQS, SNS, RDS, DynamoDB, and CloudWatch as applicable.
Apply cloud and Kubernetes security controls including IAM, RBAC, network policies, encryption, secrets management, image security, vulnerability remediation, and least-privilege access.
Implement monitoring, logging, tracing, alerting, model-performance monitoring, drift detection, incident response, backup, and disaster-recovery practices.
Lead troubleshooting, root-cause analysis, performance and cost optimization, release coordination, and production support.
Mentor junior team members and establish reusable automation, coding standards, infrastructure modules, deployment patterns, documentation, and engineering best practices.
Facilitate communication between technical and business stakeholders to align AWS and MLOps solutions with business objectives.
Professional & Technical Skills / Technical Expertise:
Must To Have Skills: Strong hands-on expertise in Python development, Amazon Web Services (AWS), Amazon EKS, Kubernetes, DevOps, and MLOps.
Strong Python software-development experience for backend APIs, microservices, serverless applications, AWS automation, data/ML services, infrastructure tooling, and operational utilities.
Strong hands-on knowledge of AWS…