AWS Cloud Infrastructure Engineer

Overview

Empower AI is AI for government. Empower AI gives federal agency leaders the tools to elevate the potential of their workforce with a direct path for meaningful transformation. Headquartered in Reston, Va., Empower AI leverages three decades of experience solving complex challenges in Health, Defense, and Civilian missions. Our proven Empower AI Platform® provides a practical, sustainable path for clients to achieve transformation that is true to who they are, what they do, how they work, with the resources they have. The result is a government workforce that is exponentially more creative and productive. For more information, visit www.Empower.ai.

 

Empower AI is proud to be recognized as a 2024 Military Friendly Employer by Viqtory, the publisher of G.I. Jobs. This designation reflects the company’s commitment to hiring and supporting active-duty and veteran employees.

Responsibilities

In this role, you will architect, implement, and optimise enterprise-scale cloud infrastructure leveraging AWS services and leading DevOps practices. You will work closely with multidisciplinary teams to ensure highly available, resilient, and cost-effective environments underpin our clients’ digital transformation initiatives. This is a unique opportunity for technically adept individuals to contribute directly to expanding cloud and infrastructure capabilities.

 

Key Responsibilities – AWS Architecture, DevOps Engineering, Security, and Automation

 

• Design, build, and maintain secure, scalable cloud infrastructure using AWS (EC2, S3, VPC, IAM, Lambda, RDS, etc.).
• Develop and manage Infrastructure as Code (IaC) solutions with tools such as CloudFormation, Terraform, or AWS CDK.
• Implement automation pipelines for provisioning, configuration management, and deployment by utilising DevOps tools (e.g., Jenkins, GitHub Actions, Ansible, Docker, Kubernetes).
• Collaborate with software engineers, architects, and security specialists to deliver resilient, high-performance solutions tailored to client and project requirements.
• Monitor and optimise cloud infrastructure for cost, reliability, and performance, recommending improvements where needed.
• Maintain and enhance operational security, enforcing best practices, policies, and controls in cloud environments.
• Troubleshoot and resolve infrastructure issues efficiently, ensuring minimum disruption to mission-critical services.
• Champion knowledge sharing and continuous improvement within the cloud engineering community of the organisation.
• Evaluate and integrate AI/ML and generative AI capabilities (e.g., AWS Bedrock, SageMaker) into cloud architectures to support intelligent automation and data-driven operations.
• Leverage AI-assisted DevOps and coding tools to accelerate infrastructure-as-code development, testing, and anomaly detection.

Qualifications

Requirements:

• • Bachelor’s degree in Computer Science, Information Systems, Engineering, or related technical field, or relevant professional experience.
  • 10+ years of hands-on experience designing, deploying, and managing cloud infrastructure, with a significant focus on AWS services.
  • US Citizen with ability to obtain Public Trust Clearance
  • Advanced knowledge of AWS architecture, service deployment, networking, and security concepts.
  • Proficiency in Infrastructure as Code tools (e.g., CloudFormation, Terraform, or equivalent).
  • Experience with CI/CD pipeline creation, automation workflows, and relevant DevOps toolchains.
  • Strong scripting skills (e.g., Python, Bash, PowerShell) for automation and system integration tasks.
  • Thorough understanding of cloud security best practices, incident response, compliance, and monitoring.
  • Skilled in collaborative working with cross-functional, technical, and non-technical teams.
  • Analytical thinker with a solution-oriented approach to technical challenges.
  • Commitment to maintaining an inclusive, high-trust, and growth-driven team culture.
  • Advanced AWS, Cloud Migration, and Containerisation skills
  • Working knowledge of AWS AI/ML services (e.g., Bedrock, SageMaker, Comprehend) and how to incorporate them into cloud infrastructure design.
  • Experience with hybrid and multi-cloud environments or cloud migration projects.
  • Ability to design and manage container-based workloads using Docker and/or Kubernetes on AWS EKS.
  • Knowledge of monitoring and logging tools (e.g., CloudWatch, Splunk, Datadog, Prometheus), and cost management strategies in AWS.
  • Hands-on experience deploying or fine-tuning generative AI/LLM solutions on A