Job Type: Contract
Work Mode: Hybrid (3 Days from office)
Mandatory - SC Eligible
We are seeking a highly skilled AWS Cloud Engineer with deep hands‑on experience across AWS cloud services and BAU Ops role. This role requires hands-on Cloud Engineering expertise, Networking, AWS cloud migration experience, good communication skills, and product maintenance experience for post go-live operational support.
Your core responsibilities include:
• Implement end‑to‑end AWS solutions across compute, networking, storage, and analytics, leveraging services such as Fargate, Bedrock, Redshift, ALBs, VPC networking, Neptune DB, and regional AWS deployments. • Migration of existing AWS infra from Cloud Formation templates to Terraform.
• Migration of CHEF cookbooks to Ansible
• Migration of Jenkins jobs to GitHub actions.
• Post go-live production BAU Ops role.
• Ensure robust operational standards across logging, security, monitoring, IAM governance, and distributed cloud reliability.
What skills are required?
Minimum skills:
• Degree in Computer Science, Information Systems, Engineering, or equivalent experience.
• Good architectural understanding of core AWS services, cloud networking, and distributed system design.
• Proven hands-on experience in AWS, CHEF, API development, Ansible, GitHub actions and runners, and Terraform.
Essential skills:
• Strong experience with AWS data and AI ecosystem: Bedrock, Fargate, EFS, Redshift, Neptune, ALBs, VPC networking, CloudWatch, IAM, and regional deployment strategies including software’s such as CHEF, Ansible, Terraform, GitHub.
• Good understanding of cloud security, scalability patterns, and cost-aware solution design.
• Confident communicator with excellent command of English, capable of influencing and leading client conversations.
• Working experience of ServiceNow, Jira, DataDog (or any other platform monitoring tool)
Good to have:
• Experience with vector databases, graph databases (Neptune), or graph exploration tools.
• Proven hands-on experience in Python, API development, and automation.
• Hands-on background with LLM integrations, GenAI solution architecture, and AI pipeline orchestration.
• Familiarity with orchestration tools, serverless design patterns, or container-native workflows.
• Exposure to modern AI frameworks, LangGraph/LangChain concepts, and prompt engineering