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
ResponsibilitiesDesign 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 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.
About Us
Skills Required
- 4-6 years of hands-on experience delivering production AWS pipelines, infrastructure as code, and ML-platform enablement
- Experience with AWS Batch, ECS, Lambda, Step Functions, SQS, SNS, S3, and EventBridge
- Containerization with Docker deployed through Amazon ECR, ECS, or AWS Batch
- GPU and CPU workload provisioning and elastic scaling
- Experience with Amazon Bedrock, Amazon SageMaker, and Amazon QuickSight for model hosting, training, and analytics
- Model deployment, endpoints, and serving for production models
- Integration of GenAI, LLM, and ML inference into data and document-processing pipelines
- Experience with IAM, VPC, security groups, KMS, load balancers, and S3 permissions
- Infrastructure as code using CloudFormation, AWS CDK, or Terraform
- Python, Shell scripting, AWS CLI, and Boto3
- CI/CD experience with Azure DevOps, GitHub Actions, or AWS CodePipeline
- Version control with Git or Azure DevOps, automated testing, and release automation
- Experience with RDS, PostgreSQL, and other data stores
- Query and performance tuning in high-volume environments
- Logging, monitoring, alerting, and operational dashboards using CloudWatch and related AWS services
- Bachelor's or master's degree in Computer Science, Engineering, Mathematics, Statistics, or equivalent experience
- OCR and NLP-driven document processing for unstructured data
- US healthcare payer or Payment Integrity domain exposure
- AWS certification such as Solutions Architect, DevOps Engineer, or ML Specialty
- Agile certification
- US healthcare insurance, payer, or Payment Integrity context
- Strong ownership, end-to-end accountability, and production-first mindset
- Clear consultative communication and cross-functional collaboration
What We Do
Choosing a digital partner is about more than capabilities — it’s about collaboration and character. Unrealistic overhauls and off-the-shelf products ignore what matters most — your unique needs, culture, goals, and your legacy data and technology environments. At EXL, our collaboration is built on ongoing listening and learning to adapt our methodologies. We’re your business evolution partner—tailoring solutions that make the most of data to make better business decisions and drive more intelligence into your increasingly digital operations. Whether your goals are scaling the use of AI and digital, redesign operating models, or driving better and faster decisions, we’re here to partner with you to help you gain—and maintain—competitive advantage with efficient, sustainable models at scale. Our expertise in transformation, data science, and change management helps make your business more efficient and effective, improve customer relationships and enhance revenue growth. Instead of focusing on multi-year, resource- and time-intensive platform designs or migrations, we look deeper at your entire value chain to integrate strategies with impact. We use our specialization in analytics, digital interventions, and operations management—alongside deep industry expertise — to deliver solutions that help you outperform the competition. At EXL, it’s all about outcomes—your outcomes—and delivering success on your terms. Share your goals with us and together, we’ll optimize how you leverage data to drive your business forward. For more information, visit www.exlservice.com.
