Job Title: AWS DevOps / FinOps Engineer with AI & Automation
Location: Bethesda, MD (Hybrid 2 Days Onsite per Week)
Duration: 12+ Months Contract
Job Summary
We are seeking an experienced AWS DevOps / FinOps Engineer with strong expertise in cloud infrastructure, cost optimization, AI technologies, and Python automation. The ideal candidate will be responsible for managing AWS environments, implementing FinOps best practices, automating cloud operations, and leveraging Generative AI solutions such as AWS Bedrock to improve operational efficiency and business outcomes.
Key Responsibilities
- Design, implement, and maintain scalable AWS cloud infrastructure.
- Develop and manage CI/CD pipelines to support application deployment and infrastructure automation.
- Drive FinOps initiatives including cloud cost monitoring, optimization, budgeting, forecasting, and governance.
- Build automation solutions using Python for cloud operations, monitoring, and reporting.
- Implement Infrastructure as Code (IaC) using Terraform or CloudFormation.
- Collaborate with engineering teams to optimize cloud resource utilization and performance.
- Develop and integrate Generative AI solutions using AWS Bedrock and related AI services.
- Create dashboards and reports to provide visibility into cloud spending and operational metrics.
- Ensure cloud environments comply with security, governance, and operational best practices.
- Troubleshoot production issues and provide operational support for cloud platforms.
Required Skills
- 7+ years of experience in AWS Cloud and DevOps Engineering.
- Strong hands-on experience with AWS services including EC2, S3, Lambda, ECS/EKS, RDS, CloudWatch, IAM, and VPC.
- Experience with AWS Bedrock and Generative AI technologies.
- Strong knowledge of FinOps principles, cloud cost management, and optimization strategies.
- Proficiency in Python scripting and automation.
- Experience with Terraform, CloudFormation, or other Infrastructure as Code tools.
- Strong experience with CI/CD tools such as Jenkins, GitHub Actions, GitLab CI, or AWS CodePipeline.
- Experience with Docker and Kubernetes.
- Knowledge of monitoring and logging tools.
- Strong understanding of cloud security and governance best practices.
Preferred Qualifications
- AWS Solutions Architect, DevOps Engineer, or Cloud Practitioner Certification.
- Experience with AI/ML services such as Amazon SageMaker, OpenAI, or other LLM platforms.
- Knowledge of cost management tools such as AWS Cost Explorer, CUR, CloudHealth, or Apptio Cloudability.
- Experience working in enterprise-scale cloud environments.
- Familiarity with data analytics and reporting tools.
Education
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
Nice to Have
- Experience with Agentic AI, Prompt Engineering, and RAG-based applications.
- Knowledge of MLOps and AI infrastructure management.
- Experience supporting large-scale cloud transformation initiatives.
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