AWS Engineer

Qualifications

• Overall 4-6 years of demonstrable hands-on delivery of production AWS pipelines, infrastructure as code, and ML-platform enablement experience
• AWS Batch, ECS, Lambda, Step Functions, SQS, SNS, S3, EventBridge
• Containerization with Docker, deployed via Amazon ECR / ECS / AWS Batch
• GPU & CPU workload provisioning and elastic scaling
• Amazon Bedrock, Amazon SageMaker, Amazon QuickSight for model hosting, training, and analytics
• Model deployment, endpoints, and serving as the go-forward baseline for running production models
• Integration of GenAI/LLM and ML inference into data and document-processing pipelines
• IAM, VPC, Security Groups, KMS, Load Balancers, S3 permissions
• IaC with CloudFormation, AWS CDK, or Terraform
• Cost-efficient, highly available, secure architecture by design
• Python, Shell scripting, AWS CLI / Boto3 (SDK)
• CI/CD with Azure DevOps, GitHub Actions, or AWS CodePipeline
• Version control (Git / Azure DevOps), automated testing, release automation
• RDS / PostgreSQL and other data stores powering processing pipelines
• Query and performance tuning in high-volume environments
• Logging, monitoring, alerting, and operational dashboards using CloudWatch and related AWS services
• Nice to Have:
• OCR & NLP-driven document processing for unstructured data
• US Healthcare payer / Payment Integrity domain exposure
• AWS certifications (Solutions Architect, DevOps Engineer, or ML Specialty); agile certifications
• US Healthcare Insurance / Payer & Payment Integrity context (preferred)
• Strong ownership, end-to-end accountability, and production-first mindset
• Clear, consultative communication; collaborates across DevOps, data, and infrastructure teams
• Educational Requirements:
• Master's or bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or equivalent experience.
• AWS certifications a strong plus; US Healthcare certifications welcome.
• *The posted range is the hiring range for this role — a subset of the broader range available to employees over time — and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidate's skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position. The top of the range is reserved for candidates who notably exceed the requirements; the lower end applies to those with less experience or fewer preferred qualifications. For positions based in higher-cost zones (e.g., California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process.