Lead AWS DevOps

Job ID: 27416641Reference Number: 26-00130Title: Lead AWS DevOpsLocation: Iselin, NJ, 08830Posted Date: 2026-02-09Contact: Shyam MaramContact Email: View email address on click.appcast.io Phone: (848) 234-8733Company: HAN Staffing Lead AWS DevOps Engineer with Generative AI Location: New Jersey Type: Contract Role Summary We are seeking a highly skilled AWS DevOps Engineer with hands‐on Generative AI experience to support cloud automation, LLM integration, and AI‐driven platform modernization. The consultant will work onsite with engineering, data, and product teams to build scalable CI/CD pipelines, automate cloud infrastructure, and integrate GenAI capabilities into enterprise workflows. Key Responsibilities Design, build, and maintain AWS infrastructure using Terraform/CloudFormation. Develop and optimize CI/CD pipelines (CodePipeline, Jenkins, GitHub Actions, GitLab CI). Implement containerization and orchestration using Docker, ECS, EKS, and Kubernetes. Integrate Generative AI services such as AWS Bedrock, SageMaker, or custom LLMs. Build automation for model deployment, prompt workflows, and inference pipelines. Collaborate with data engineering and application teams to embed AI into cloud services. Monitor, troubleshoot, and optimize cloud performance, cost, and reliability. Ensure security best practices: IAM, VPC, Secrets Manager, KMS, GuardDuty, CloudTrail. Required Skills & Experience 7+ years of DevOps / Cloud Engineering experience. 5+ years hands‐on AWS experience (EC2, Lambda, S3, API Gateway, RDS, DynamoDB, EKS). Strong expertise in Terraform, CloudFormation, and Infrastructure‐as‐Code. Deep experience with CI/CD, GitOps, and automated deployment pipelines. Strong scripting skills: Python, Bash, Shell. Experience with Docker, Kubernetes, Helm, and container security. Hands‐on experience with Generative AI, including: AWS Bedrock, SageMaker, or Hugging Face Prompt engineering LLM fine‐tuning or orchestration Experience integrating AI into microservices or automation workflows. Nice to Have Experience with LangChain, LangGraph, vector databases (Pinecone, FAISS, OpenSearch). Knowledge of MLOps frameworks and model lifecycle automation. Experience with event‐driven architectures (SNS, SQS, Kinesis). Exposure to financial, insurance, or enterprise cloud environments. Soft Skills Strong communication and ability to work directly with onsite stakeholders. Problem‐solver with a proactive, ownership‐driven mindset. Ability to work in fast‐paced, collaborative, onsite engineering teams. If you want, I can also prepare: