Data & AI Forward Deployed Engineer

RevStar

2d•Remote

About The Position

RevStar is seeking a Data & AI Forward Deployed Engineer (FDE) for its Digital Solutions Practice. This client-facing role operates at the intersection of enterprise cloud architecture, hands-on engineering, and delivery. The FDE owns the full delivery lifecycle for high-impact enterprise accounts, serving as both a cloud builder and trusted technical advisor. The role involves architecting resilient cloud-native environments, modernizing legacy infrastructure, and deploying AWS Generative AI architectures using services such as Amazon Bedrock, Q, and SageMaker. It also supports AWS adoption and consumption growth by identifying workloads, building proofs of concept, and aligning technical strategy with client executives. RevStar builds cloud, data, and Generative AI solutions for enterprise organizations. Its stated principles are Self-Mastery, Ownership, and Shared Destiny. This is a remote-first, full-time W-2 role available in AZ, DC, FL, GA, IA, IL, ME, NY, NJ, SC, TX, and VA.

Requirements

At least 6 years of hands-on experience in Cloud Architecture, DevOps/SRE, or Software Engineering focused on AWS.
At least 3 years in a client-facing consulting, Solutions Architecture, or Forward Deployed Engineering role.
Mastery of core AWS services, including IAM, VPC, EC2, ECS/EKS, Lambda, S3, RDS, DynamoDB, CloudFront, and Route 53.
Expert-level proficiency with 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 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.
Outstanding verbal and written communication skills, including the ability to whiteboard architectures, build working proofs of concept or demos, and present to C-level executives.
Ability to identify technical expansion opportunities and advocate for cloud modernization.

Nice To Haves

AWS specialty certifications in Security, Machine Learning, or Data Analytics.
Experience with enterprise clients in Healthcare, Financial Services, Retail, or SaaS.

Responsibilities

Design, build, and deploy secure, scalable, and resilient AWS cloud architectures using Infrastructure as Code and modern microservices or serverless patterns.
Serve as the primary technical leader on strategic enterprise client engagements and translate business goals into AWS solutions in partnership with client executives and development teams.
Lead large-scale migrations from on-premises data centers or legacy platforms to AWS and modernize monolithic applications into serverless or containerized architectures.
Architect and deploy enterprise generative AI and machine learning workloads using Amazon Bedrock, SageMaker, vector databases, and custom RAG implementations.
Identify high-value cloud workloads within client accounts to expand AWS consumption and demonstrate ROI 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.
Conduct AWS Well-Architected Reviews and identify technical expansion opportunities.

Benefits

Paid time off.
Remote-first working environment.
Medical, dental, and vision coverage.
Company-sponsored 401(k) plan.
Annual learning and development stipend for conferences, certifications, or courses.
Peer mentorship and coaching.
Professional growth opportunities and exposure to AWS generative AI, data, and cloud technologies across diverse industries.
Company outings and volunteer opportunities.
Collaborative, innovative culture.

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