

AWS Cloud Engineer - Remote
β - Featured Role | Apply direct with Data Freelance Hub
This role is for an AWS Cloud Engineer, remote, long-term contract (W2 or C2C) with a major financial firm. Requires 5+ years AWS experience, proficiency in GenAI, MLOps, Terraform, and an AWS certification. U.S. citizenship or green card required.
π - Country
United States
π± - Currency
$ USD
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π° - Day rate
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ποΈ - Date discovered
July 26, 2025
π - Project duration
More than 6 months
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ποΈ - Location type
Remote
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π - Contract type
W2 Contractor
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π - Security clearance
Unknown
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π - Location detailed
United States
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π§ - Skills detailed
#Automation #Impala #Ansible #RDS (Amazon Relational Database Service) #AWS SageMaker #Database Systems #Hadoop #AWS (Amazon Web Services) #Agile #GIT #SageMaker #Prometheus #Big Data #S3 (Amazon Simple Storage Service) #Deployment #EC2 #Unix #Bash #Docker #"ETL (Extract #Transform #Load)" #A/B Testing #Monitoring #Web Services #AI (Artificial Intelligence) #Elasticsearch #Computer Science #Scrum #ML (Machine Learning) #Security #Cloud #Python #Spark (Apache Spark) #Scala #Terraform #Azure DevOps #Lambda (AWS Lambda) #IAM (Identity and Access Management) #DevSecOps #Azure #Grafana #DevOps #Jenkins #Splunk #VPC (Virtual Private Cloud) #Linux #Puppet
Role description
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Title
Job summary:
AWS cloud Engineer - Remote
Location:
Remote
Length And Terms
Long term - W2 or C2C
Position created on 07/22/2025 02:03 pm
Job Description
β’ Webcam interview;
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β’ Long term project
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β’ Remote, contract to hire position with a major Financial firm.
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β’ Due to secrurity reasons only USC / GC
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β’ Job Description
As a Cloud Engineer within the AWS AI/ML platform team, you will have the opportunity to work one-on-one with application and infrastructure developers to build and enhance the AI/ML infrastructure and application patterns that power mission-critical applications, ensuring that theyre engineered for high availability, durability, and resiliency. You will be part of an agile team that combines various backgrounds, experiences, and perspectives to solve complex problems within AWS and beyond.
Responsibilities
β’ Focus on optimizing existing systems, building infrastructure, and eliminating work through automation.
β’ Influence application and security architecture and design across multi and hybrid cloud platforms.
β’ Peer-reviewing infrastructure-as-code (AWS CloudFormation, Python, Terraform, or similar).
β’ Partnering with application and infrastructure teams to develop reusable cloud patterns.
β’ Deployment and troubleshooting of infrastructure code.
β’ Partner with the Site Reliability Engineering (SRE) team to conduct post-incident reviews and root cause analysis and building monitoring and automation to prevent future incidents.
β’ Identify opportunities to build self-service capabilities and automate infrastructure and application deployments.
β’ Develop tools and best practices for platform development, developer productivity, automation (MLOps, CI/CD, A/B testing), and production operations.
β’ Design, Develop & deliver critical components, frameworks, services, and products using AWS SageMaker, Bedrock, Lambda, and container technologies in AWS.
β’ Expertise in LLM, Agentic framework, Agentic AI
β’ Develop processes, model monitoring, and governance framework for successful ML model operationalization.
β’ Define standards for engineering and operational excellence for running best-in-class ML platforms and continue to improve ML platforms to keep up with the latest innovations.
β’ Assist in gathering and analyzing non-functional requirements and translating that into technical specifications for robust, scalable, supportable solutions that work well within the overall system architecture
Technical Qualifications
β’ The cloud is a rapidly changing world, with the major players announcing new features almost on a daily basis. A successful Cloud Engineer doesnt need to know everything about everything but instead keeps a pulse on new developments and emerging paradigms to identify areas where they can continuously improve their skill sets.
β’ Ability to debug, optimize code, and automate routine tasks.
β’ A systematic problem-solving approach coupled with a strong sense of ownership and drive.
β’ Ability to quickly pickup and understand where newly released cloud services would be appropriate for business applications.
β’ Experience with infrastructure automation tools such as Puppet, Ansible, CloudFormation, or Terraform.
β’ Working knowledge of pipeline-automation tools such as Jenkins, CodePipeline, Azure DevOps, or other comparable tools.
β’ Experience using Git for source control management.
β’ Ability to proficiently write code in Python, Node.js, Bash (shell), PowerShell, or other similar languages.
β’ Experience using Docker within container orchestration platforms such as AWS ECS, EKS, Google Anthos, or others.
β’ Comfortable in a Linux environment.
β’ Understanding of foundational AWS services such as VPCs, EC2, S3, RDS, Auto Scaling Groups, CloudWatch Logs, etc.
β’ In-depth knowledge of security and IAM within AWS, including the management and operation of Security Groups, KMS Keys, VPC NACLs, and SCPs.
β’ Familiar with ETL and big data tool-chains such as those provided by Hadoop/EMR, Glue, Spark, Impala, or similar.
β’ Understanding of relational database systems and how applications interact with them.
β’ Familiarity with one or more log and event aggregation and monitoring systems such as Splunk, Elasticsearch (ELK), Prometheus, Grafana, or similar.
Qualifications
β’ 5+ years experience in Amazon Web Services (AWS), AIML services
β’ Experience in working in an Agile/Scrum-focused organization.
β’ Strong verbal and written communication skills; comfortable with translating technical problems to non-technical audiences.
β’ MS/BS degree in Information Technology, Computer Science, related technical field, or equivalent practical experience.
Preferred Qualifications
β’ One or more Associate or Professional-level AWS certificates.
β’ Prior experience within a DevOps, DevSecOps, SRE, or UNIX/Linux Sys-Admin teams.
Must Haves
β’ GenAI, MLOps, Agentic AI, AWS, Bedrock, Sagemaker, LLM
β’ The position is a combination of GenAI (70%) and MLOps (30%)
β’ Candidate should have at least one AWS certification.
β’ Terraform, CloudFormation are a big plus.
Contact The Recruiter Working On This Position
The recruiter working on this position is Singaram Saikiran(Shaji Team)
His/her contact number is His/her contact email is saikiran@msysinc.com
Our recruiters will be more than happy to help you to get this contract.
If you have questions about this posting, please contact support@lensa.com