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Mid-level metro role with strong employer brand and broad DevOps+AI requirements increases candidate competition.
Core DevOps skills are transferable, but GenAI and regulated pharmaceutical compliance add moderate industry bias.
Explicit 4–6 years plus many mandatory AWS, Terraform, CI/CD, Python, and security skills raises shortlisting strictness.
Automate and maintain AWS infrastructure and CI/CD pipelines using Terraform, CloudFormation, Jenkins, GitHub Actions, and GitLab CI to enable secure, repeatable, and efficient cloud deployments.
Develop and deploy AI-enabled applications integrating AWS Bedrock, foundation models, and implement Retrieval-Augmented Generation (RAG) solutions with monitoring and governance.
Collaborate with cloud, DevOps, AI/ML, and data teams to create reusable platform capabilities, ensure security compliance, and enhance observability and reliability at enterprise scale.
4–6 years of experience in AWS, cloud engineering, DevOps, or related software engineering roles.
Strong hands-on expertise with AWS core services including EC2, ECS, Lambda, IAM, CloudWatch, VPC, SQS, and SNS.
Proficiency with Infrastructure as Code tools (Terraform and/or CloudFormation) and CI/CD tools such as Jenkins, GitHub Actions, or GitLab CI.
Bachelor’s or master’s degree in Computer Science, IT, or related technical field, or equivalent experience.
Experienced in designing and operating secure, scalable AWS cloud architectures with strong emphasis on automation and compliance (e.g., IAM least privilege, guardrails).
Skilled in developing production-ready AI/GenAI applications on AWS integrating LLM APIs, embedding services, and RAG concepts with MLOps practices.
Proficient in Python scripting, containerization (Docker, ECS/EKS), and observability tooling (CloudWatch, Datadog, Grafana) to deliver resilient AI-driven cloud platforms.