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RevStar

Data & AI Forward Deployed Engineer

Full-TimeUpdated on 10/23/2026
No salary listed
Senior
Remote in USA
RemoteRemote work is limited to AZ, DC, FL, GA, IA, IL, ME, NY, NJ, SC, TX, and VA.
DevOps & InfrastructureCloud Engineering

About the job

Requirements
  • At least 6 years of hands-on experience in Cloud Architecture, DevOps/SRE, or Software Engineering focused on AWS.
  • At least 3 years of experience in client-facing consulting, Solutions Architecture, or Forward Deployed Engineering.
  • Mastery of core AWS services, including IAM, VPC, EC2, ECS/EKS, Lambda, S3, RDS, DynamoDB, CloudFront, and Route 53.
  • Expert-level proficiency in Terraform, AWS CDK, or CloudFormation, and automated CI/CD pipelines such as GitHub Actions, GitLab CI, or AWS CodePipeline.
  • Practical experience with Amazon Bedrock, SageMaker, Glue, Redshift, or OpenSearch for building data platforms and AI solutions.
  • AWS Certified Solutions Architect – Professional and/or AWS Certified DevOps Engineer – Professional certification is required.
  • Proven experience leading technical delivery for Fortune 500 or mid-market enterprise clients in Healthcare, Financial Services, Retail, or SaaS.
  • Ability to whiteboard complex architectures, build working proofs of concept and demos, and present to C-level executives.
  • Ability to identify technical expansion opportunities, conduct AWS Well-Architected Reviews, and advocate for cloud modernization to expand account footprint.
Responsibilities
  • Design, build, and deploy secure, scalable, and resilient AWS cloud architectures using Infrastructure as Code (Terraform, AWS CDK, CloudFormation) and modern microservices or serverless patterns, including Lambda, ECS/EKS, API Gateway, and DynamoDB.
  • Serve as the primary technical leader on strategic enterprise client engagements, partnering with CIOs, CTOs, infrastructure and engineering executives, and client development teams to translate business goals into AWS solutions.
  • Lead large-scale migrations from on-premises data centers or legacy platforms to AWS using services such as AWS Application Migration Service and Database Migration Service; re-architect legacy monolithic applications into serverless or containerized architectures.
  • Architect and deploy enterprise generative AI and machine-learning workloads using Amazon Bedrock, SageMaker, vector databases such as OpenSearch, Pinecone, and pgvector, and custom retrieval-augmented generation implementations.
  • Partner with account leadership to identify valuable cloud workloads within client accounts, expand AWS consumption, and demonstrate return on investment to client executive stakeholders.
  • Coach and mentor Cloud Engineers and Solutions Architects.
  • Develop internal accelerators, reusable Terraform modules, AWS Well-Architected Review frameworks, and cloud delivery best practices.
Desired Qualifications
  • Specialty AWS certifications in Security, Machine Learning, or Data Analytics.

About the company

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