AWS Engineer

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

Responsibilities

• 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.

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 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.

EXL (NASDAQ: EXLS) is a leading data analytics and digital operations and solutions company. We partner with clients using a data and AI-led approach to reinvent business models, drive better business outcomes and unlock growth with speed. EXL harnesses the power of data, analytics, AI, and deep industry knowledge to transform operations for the world’s leading corporations in industries including insurance, healthcare, banking and financial services, media and retail, among others. EXL was founded in 1999 with the core values of innovation, collaboration, excellence, integrity and respect. We are headquartered in New York and have more than 54,000 employees spanning six continents. For more information, visit www.exlservice.com.

EXL never requires or asks for fees/payments or credit card or bank details during any phase of the recruitment or hiring process and has not authorized any agencies or partners to collect any fee or payment from prospective candidates. EXL will only extend a job offer after a candidate has gone through a formal interview process with members of EXL’s Human Resources team, as well as our hiring managers.

EXL is the indispensable partner for leading businesses in data-led industries such as insurance, banking and financial services, healthcare, retail and logistics. We bring a unique combination of data, advanced analytics, digital technology and industry expertise to help our clients turn data into insights, streamline operations, improve customer experience, and transform their business. Our partnerships with clients are built on a foundation of collaboration – and we’ve been chosen as a partner by nine of the top ten leading US insurance companies, nine of the top 20 global banks, and six of the top ten US health care payers. We function as one team to make your goals our goals, whether that’s unlocking the value of generative AI or embedding analytics into workflows that reduce risk or power your growth. Clients choose EXL as their transformation partner for many reasons. Our geographic diversity make talent all over the world instantly accessible. Digital accelerators enable unmatched speed-to-value, letting you realize results fast. It’s our people that truly set us apart, though, including the 1,500 data scientists we have dedicated to our generative AI practice. And our more than twenty years of experience in delivering business services, garnering stellar client references, and maintaining a solid balance sheet are reassuring to our C-suite clients. Find out for yourself why clients, employees, and analysts think we’re some of the best in the business. Contact us to see how we can help you achieve your goals.