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Lead AWS DevOpsHan IT StaffingUnited States

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Lead AWS DevOps

Han IT Staffing
  • US
    United States
  • US
    United States

Über

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:
  • United States

Sprachkenntnisse

  • English
Hinweis für Nutzer

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