AWS Engineer
At a glance
Mid-level Cloud role at Fa Ewjt Saasfaprod1. United States · full-time · $60,100–$98,700 base.
devopsroles summary, based on the employer's posting.
What you'll do
- Build AWS pipelines for data and document processing, using services such as Batch, ECS, Lambda, Step Functions, SQS, SNS, S3, and EventBridge
- Package workloads in Docker and run them through ECR, ECS, or Batch, scaling GPU and CPU compute as needed
- Set up and run the Bedrock, SageMaker, and QuickSight platform for production models, including model serving and inference integration
- Automate AWS environments with Python, Shell, and infrastructure-as-code tools, and implement CI/CD using the listed platforms
- Monitor pipeline and data-ingestion performance, resolve urgent production incidents, and prevent repeat failures
What you bring
- Four to six years delivering production AWS pipelines, infrastructure as code, and ML-platform enablement
- Hands-on experience with AWS services for pipelines, containers, compute, networking, security, and observability
- Experience building automation with Python or Shell and implementing CI/CD and infrastructure as code
- A bachelor's or master's degree in a relevant technical or quantitative field, or equivalent experience
Who this fits
This role suits a hands-on engineer who can own production cloud and ML-platform delivery and coordinate with application, DevOps, data, and infrastructure teams. You’ll also engage client stakeholders to clarify needs and demonstrate capabilities. The work centers on AWS production systems supporting US healthcare payment operations.
From the employer
Are you a hands-on cloud engineer who thrives on building scalable, secure, cost-efficient AWS solutions?
As an AWS Cloud & MLOps Engineer at EXL, you'll design, develop, deploy, and maintain scalable cloud-based data and document-processing pipelines, and stand up the AWS ML platform (Bedrock, SageMaker, QuickSight) that runs our production models. You'll work closely with application, DevOps, data, and infrastructure teams to deliver highly available AWS solutions that power critical operations in the US healthcare payment space.
*Base Pay Range: $60,100 - $98,700
For more information on benefits and what we offer please visit us at https://www.exlservice.com/us-careers-and-benefits
Design and implement scalable AWS data and document-processing pipelines.
Develop and maintain pipelines using AWS Batch, ECS, Lambda, Step Functions, SQS, SNS, S3, and EventBridge.
Build containerized workloads with Docker, deployed through Amazon ECR / ECS / AWS Batch.
Work with GPU and CPU-based workloads, including provisioning and scaling compute resources.
Stand up and operate the AWS ML platform using Amazon Bedrock, Amazon SageMaker, and Amazon QuickSight, the go-forward baseline for running all our models.
Develop automation using Python, Shell scripting, and AWS CLI / SDK (Boto3).
Implement CI/CD pipelines using Azure DevOps, GitHub Actions, or AWS CodePipeline.
Manage infrastructure as code using CloudFormation, AWS CDK, or Terraform.
Configure and troubleshoot IAM roles, security groups, VPC, load balancers, KMS, and S3 permissions.
Implement logging, monitoring, alerting, and operational dashboards using CloudWatch and related AWS services.
Work with RDS / PostgreSQL and other data stores used by processing pipelines.
Resolve high-priority production incidents with precision, drive zero-downtime operations, and proactively prevent recurrence.
You're not just running infrastructure. You're building the cloud and ML platform that powers payer operations, ensures compliance, and scales with the business.
Deliver AWS solutions that work at scale, with reliability, speed, security, and cost-efficiency built in.
Own production performance and observability across pipelines, compute, and data-ingestion points.
Collaborate with application, DevOps, data, and infrastructure teams to ship reliable, production-grade cloud services.
Apply strong architecture principles, automation, and agile delivery to accelerate time-to-market.
Proactively remove roadblocks, anticipate risks, and communicate mitigation plans clearly to stakeholders.
Collaborative Interactions:
Internal: Partner with data engineers, DevOps, infrastructure, application teams, and tech leads. Share knowledge and grow cloud depth across the team.
External: Engage with client-side stakeholders to understand expectations, demo capabilities, and bridge business needs with technical delivery.
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 base salary range is the hiring base salary range for this role. 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.
Cloud work from LinkedIn, X, Reddit and Upwork, in one list.
Each morning you get everything that fits, strongest first.
Cloud$60k+
Find me workBy the team behind devopsroles.