Cloud Engineer

Booz Allen Hamilton

Confirmed live today High trust

Quick summary

Work type: On-site
Location: McLean, VA
Salary: $86,800–$198,000 / yr
Employment: Full-time
Posted: 1 day ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $170k

This role $142k

$73k $216k

below market most similar roles pay here above market

This role pays less than 68% of similar roles. Most pay $140,871–$199,550 — the blue band above. At the midpoint, this role pays about $142k versus about $170k for comparable roles.

Based on 240 similar postings.

Employer

About Booz Allen Hamilton

Booz Allen Hamilton is a management and technology consulting firm that provides analytics, digital, engineering, and cybersecurity solutions primarily to U.S. government agencies and commercial clients. Industry: Management & Technology Consulting

Booz Allen Hamilton currently has 1724 open roles on FindRole.

Listed pay typically runs $86,800–$198,000 across 898 roles with salary data.

Most-posted roles

View all roles at Booz Allen Hamilton

At a glance

TL;DR · Cloud Engineer

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JOB TITLE: Cloud Engineer The Cloud Engineer joins a team dedicated to engineering secure, scalable cloud platforms for mission-critical artificial intelligence solutions. This role involves building secure cloud foundations, automating deployment workflows, and supporting tools for model access, prompt management, retrieval-augmented generation, and agent orchestration. You will design and operate reusable tooling for generative AI and machine learning, implementing infrastructure as code and CI/CD workflows. Key responsibilities include troubleshooting distributed systems, managing identity and access, and building observability for infrastructure health and token consumption. You will utilize Python and services across AWS, Azure, or GCP, including Amazon Bedrock, SageMaker, and Vertex AI. Technical skills required include Docker, Kubernetes, Terraform, and Bicep. The work focuses on moving AI use cases from prototype to production while ensuring security, reliability, and cost efficiency.

What does a Cloud Engineer earn?

Median $142450 from 46 postings across 13 companies.

See salary data

Skills

Python AWS Azure GCP Kubernetes Terraform Docker CI/CD MLOps GenAIOps Amazon Bedrock Amazon SageMaker Azure Machine Learning Vertex AI Infrastructure as Code GitHub Actions GitLab CI Azure DevOps Jenkins Vector Databases Retrieval-Augmented Generation API Gateways Linux Windows Networking Identity and Access Management Secrets Management Encryption Observability Jira Confluence

What you'll do

Design and operate secure cloud platforms and reusable tooling for generative AI and machine learning applications.
Implement infrastructure as code and automation to streamline provisioning, configuration, and model endpoint deployment.
Develop services for foundation model access, prompt management, retrieval-augmented generation, and vector search.
Create CI/CD, MLOps, and GenAIOps workflows to support testing, evaluation, release management, and traceability.
Implement security controls including least-privilege access, secrets management, encryption, and network isolation for AI workloads.
Build observability systems to monitor infrastructure health, model behavior, latency, token usage, and retrieval quality.
Optimize AI workloads for scalability, inference performance, and cloud cost efficiency.
Create and maintain technical documentation, reference architectures, runbooks, and knowledge base articles.

What we're looking for

U.S. citizenship is required.
Bachelor's degree in Computer Science, Engineering, or Information Systems.
3+ years of experience developing and operating cloud solutions using Python and services in AWS, Azure, or GCP.
2+ years of experience in customer-facing technical support, platform engineering, or solutions engineering.
1+ years of experience implementing or supporting AI, machine learning, or generative AI solutions in a cloud environment.
Experience with managed AI platforms such as Amazon Bedrock, SageMaker AI, Microsoft Foundry, Azure Machine Learning, Azure OpenAI, or Vertex AI.
Experience implementing infrastructure as code and CI/CD using tools such as Terraform, CloudFormation, Bicep, GitHub Actions, GitLab CI, Azure DevOps, or Jenkins.
Experience with containers and orchestration technologies such as Docker, Kubernetes, Amazon EKS, Azure Kubernetes Service, or Google Kubernetes Engine.

4+ yrs exp

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