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SRE-AWS || contract job || 7-12 Years Experience
SRE-AWS || contract job || 7-12 Years ExperiencePeople Prime Worldwide • Hyderabad, Telangana, India
SRE-AWS || contract job || 7-12 Years Experience

SRE-AWS || contract job || 7-12 Years Experience

People Prime Worldwide • Hyderabad, Telangana, India
17 hours ago
Job description

About Client :

Our Client is a global IT services company headquartered in Southborough, Massachusetts, USA. Founded in 1996, with a revenue of $1.8B, with 35,000+ associates worldwide, specializes in digital engineering, and IT services company helping clients modernize their technology infrastructure, adopt cloud and AI solutions, and accelerate innovation. It partners with major firms in banking, healthcare, telecom, and media.

Our Client is known for combining deep industry expertise with agile development practices, enabling scalable and cost-effective digital transformation. The company operates in over 50 locations across more than 25 countries, has delivery centers in Asia, Europe, and North America and is backed by Baring Private Equity Asia.

Job Title : SRE-AWS Engineer

Experience Level : 7-12 years

Job Location : Hyderabad

Budget : 1,50,000 Per Month

Job Type : Contract

Work Mode : Hybrid

Notice Period : Immediate Joiners

Require applicants to attach a resume

Client : CMMI Level 5

Job Description :

Design, architect, and implement scalable, highly available, and secure infrastructure solutions, primarily on Amazon Web Services (AWS).

Develop and maintain Infrastructure as Code (IaC) using Terraform or AWS CDK for enterprise-scale maintainability and repeatability.

Implement robust access control via IAM roles and policy orchestration, ensuring least-privilege and auditability across multi-environment deployments.

Contribute to secure, scalable identity and access patterns, including OAuth2-based authorization flows and dynamic IAM role mapping across environments.

Support deployment of infrastructure lambda functions.

Troubleshoot issues and collaborate with cloud vendors on managed service reliability and roadmap alignment.

Utilize Kubernetes deployment tools such as Helm / Kustomize in combination with GitOps tools such as ArgoCD for container orchestration and management.

Design and implement CI / CD pipelines using platforms like GitHub, GitLab, Bitbucket, Cloud Build, Harness, etc., with a focus on rolling deployments, canaries, and blue / green deployments.

Ensure auditability and observability of pipeline states.

Implement security best practices, audit, and compliance requirements within the infrastructure.

Engage with clients to understand their technical and business requirements, and provide tailored solutions.

If needed, lead agile ceremonies and project planning, including developing agile boards and backlogs with support from our Service Delivery Leads.

Troubleshoot and resolve complex infrastructure issues.

Qualifications :

6+ years of experience in Infrastructure Engineering or similar role.

Extensive experience with Amazon Web Services (AWS).

Proven ability to architect for scale, availability, and high-performance workloads.

Deep knowledge of Infrastructure as Code (IaC) with Terraform.

Strong experience with Kubernetes and related tools (Helm, Kustomize, ArgoCD).

Solid understanding of git, branching models, CI / CD pipelines and deployment strategies.

Experience with security, audit, and compliance best practices.

Excellent problem-solving and analytical skills.

Strong communication and interpersonal skills, with the ability to engage with both technical and non-technical stakeholders.

Experience in technical mentoring, team-forming and fostering self-organization and ownership.

Experience with client relationship management and project planning.

Certifications :

Relevant certifications (e.g., Kubernetes Certified Administrator, AWS Certified Machine Learning Engineer - Associate, AWS Certified Data Engineer - Associate, AWS Certified Developer - Associate, etc.).

Software development experience (e.g., Terraform, Python).

Experience / Exposure with machine learning infrastructure.

Education :

B.Tech / B.E in computer sciences, a related field, or equivalent experience.

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