Description

You will build and enhance AI/ML infrastructure and application patterns to ensure high availability for mission-critical applications.

This role is hybrid.

Responsibilities

• Design and deliver critical components using AWS SageMaker, Bedrock, Lambda, and container technologies.
• Optimize systems and eliminate manual tasks through infrastructure automation and self-service capabilities.
• Peer-review infrastructure-as-code and partner with application teams to develop reusable cloud patterns.
• Develop MLOps, CI/CD, and production operations tools to improve developer productivity.
• Conduct post-incident reviews and root cause analysis with SRE teams to build preventative monitoring.

Required Skills

• 5+ years of experience with Amazon Web Services (AWS) and AI/ML services.
• Proficiency in Python, Node.js, Bash, or PowerShell.
• Hands-on experience with infrastructure-as-code tools including Terraform and CloudFormation.
• Experience with container technologies and orchestration such as Docker, AWS ECS, or EKS.
• Strong knowledge of AWS security and IAM, including Security Groups, KMS, VPC NACLs, and SCPs.
• Familiarity with ETL and big data tool-chains like Hadoop, EMR, Glue, or Spark.
• Experience with CI/CD and pipeline automation tools such as Jenkins, CodePipeline, or Azure DevOps.
• Understanding of relational database systems and foundational AWS services like VPC, EC2, S3, and RDS.
• Experience using Git for source control management.

Preferred Skills

• Experience with log and event aggregation systems like Splunk, ELK, Prometheus, or Grafana.
• Expertise in LLM, Agentic frameworks, and model monitoring/governance.

Key Skills

Education

Any Gradute