Principal Cloud Engineer

Responsibilities for this Position

Location: Any Location / Remote

Full Part/Time: Full time

Job Req: RQ227174

Type of Requisition: Regular

Clearance Level Must Currently Possess: None

Clearance Level Must Be Able to Obtain: None

Public Trust/Other Required: None

Job Family: IT Infrastructure and Operations

Job Qualifications:

Skills: AWS CloudFormation, Cloud Architectures, Cloud Computing, Infrastructure Automation, Solution Architecture

Certifications: None

Experience: 6 + years of related experience

US Citizenship Required: No

Job Description:

Advance how our customers operate while you advance your career. Join GDIT as a Cloud Engineer Principal and build an impactful career in enterprise IT, collaborating with people who are driven and resourceful like you.

As a Cloud Engineer Principal, the work you'll do at GDIT will be impactful to the mission of Healthcare Fraud prevention Partnership (HFPP) Trusted Third party (TTP). You will play a crucial role in the mission of fighting fraud waste and abuse.

MEANINGFUL WORK AND PERSONAL IMPACT:

• Design, implement, modernize, and operationally support AWS-based cloud environments and hybrid cloud infrastructure.
• Develop and maintain cloud architecture patterns, reference architectures, reusable templates, and engineering standards for secure, scalable, resilient, and cost-effective platforms.
• Independently drive complex cloud initiatives, owning detailed design and implementation across infrastructure, application support, data engineering, cybersecurity, networking, and operations domains.
• Design, deploy, document, and validate multi-environment cloud infrastructure, including development, test, staging, production, and disaster recovery environments.
• Configure and manage AWS services to meet business, mission, security, availability, and performance requirements.
• Design and manage Amazon VPC environments, including subnets, route tables, network access control lists, security groups, private connectivity, DNS, load balancing, and network segmentation.
• Implement and maintain identity and access management practices, including AWS IAM roles, users, groups, policies, least-privilege access, privileged-access controls, and federation strategies.
• Develop and maintain infrastructure-as-code solutions using AWS CloudFormation, and equivalent automation frameworks.
• Build and improve automation for cloud provisioning, configuration management, image deployment, bootstrapping, scaling, monitoring, remediation, and operational workflows.
• Implement and improve observability capabilities using Amazon CloudWatch and related monitoring, logging, alerting, tracing, and dashboarding tools.
• Perform incident response, root-cause analysis, problem management, capacity planning, performance tuning, and reliability improvements for production cloud environments.
• Implement security-by-design practices, including vulnerability management, encryption, secrets management, logging, audit readiness, security monitoring, and compliance alignment.
• Implement cloud and on-premises integration solutions, including connectivity, identity, data movement, backups, storage, and operational support models.
• Support Linux and Windows environments, clustered file systems, storage, networking, SAN, backup, and large-scale data platforms as applicable.
• Execute technical upgrades, platform enhancements, lifecycle management, and migration activities, including containerization of legacy workloads.
• Develop technical documentation, including architecture diagrams, engineering standards, implementation plans, runbooks, system design documents, operating procedures, and knowledge articles.
• Conduct proof-of-concept efforts and technical evaluations for emerging cloud, automation, data, security, and AI technologies.
• Develop and execute system, integration, performance, security, resiliency, and disaster recovery testing.
• Provide technical mentorship, code and design reviews, and practical guidance to cloud engineers, systems administrators, and DevOps practitioners.
• Communicate technical findings, risks, dependencies, tradeoffs, and recommendations clearly to management, customers, and technical stakeholders.
• Identify and implement opportunities to improve engineering efficiency, platform reliability, customer experience, security posture, automation, and cloud cost management.
• Use and extend AI-assisted engineering workflows, including AI-powered code generation, infrastructure-as-code development, documentation, code review, and operational automation.
• Apply AI-assisted development practices while maintaining security, governance, and quality controls.
• Evaluate and adopt AI-enabled tools-such as Claude Code, Amazon Q Developer, or equivalent approved enterprise tools-to accelerate scripting, infrastructure automation, troubleshooting, and operational workflows.
• Support cloud capabilities for AI and data workloads, including secure data access, compute, storage, networking, model deployment, monitoring, and cost controls using services such as Amazon Bedrock, Amazon SageMaker, or comparable platforms.
• Apply guardrails for responsible AI use, including protection of sensitive data, prompt and output review practices, access controls, audit logging, and human oversight.
• Use AIOps concepts and tools to improve event correlation, anomaly detection, operational triage, predictive capacity planning, and automated remediation.

WHAT YOU'LL NEED TO SUCCEED:

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related discipline; equivalent combination of education, technical training, and relevant experience may be considered.
• 6-10 years of progressive experience in cloud engineering, systems engineering, DevOps, infrastructure engineering, site reliability engineering, or a related technical discipline.
• Demonstrated hands-on experience designing, deploying, administering, and supporting AWS cloud environments in production.
• Strong experience with AWS services across compute, networking, identity, storage, monitoring, security, and automation domains.
• Experience designing and managing AWS networking, including VPCs, subnets, route tables, security groups, network ACLs, private connectivity, load balancers, DNS, and firewall integration.
• Strong knowledge of AWS IAM, access control, authentication and authorization concepts, least privilege, encryption, secrets management, and cloud security best practices.
• Hands-on experience with infrastructure as code using AWS CloudFormation, Terraform, or similar tools.
• Experience implementing CI/CD pipelines and automated deployment practices.
• Experience with monitoring, logging, alerting, and operational diagnostics using Amazon CloudWatch and related observability tools.
• Proficiency with scripting and programming languages, including Python, Bash, PowerShell, and JavaScript/Node.js.
• Experience administering or supporting Linux and Windows operating systems in enterprise or production environments.
• Strong networking knowledge, including TCP/IP, DNS, TLS, routing, firewall concepts, load balancing, VPNs, network segmentation, and traffic inspection architectures.
• Experience supporting databases and data platforms such as MySQL, PostgreSQL, Oracle, SQL Server, Snowflake, or comparable technologies.
• Experience in a 24/7 production environment, including operational support, incident response, root-cause analysis, and change management.
• Strong written, verbal, and analytical skills with the ability to document complex technical solutions clearly.
• Ability to translate mission, business, security, and operational requirements into practical technical designs and implementation plans.
• Experience applying secure software development, DevSecOps, and automation practices in an Agile or iterative delivery environment.
• Familiarity with enterprise-approved generative AI tools and practical use cases for engineering productivity, including code generation, documentation development, troubleshooting, and infrastructure automation.
• Ability to assess AI-generated code, scripts, infrastructure configurations, and technical recommendations for accuracy, security, maintainability, and operational suitability.

DESIRED QUALIFICATIONS AND EXPERIENCE:

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related field.
• AWS certifications such as AWS Certified Solutions Architect - Professional, AWS Certified DevOps Engineer - Professional, AWS Certified Security - Specialty, AWS Certified Advanced Networking - Specialty, or comparable cloud certifications.
• Experience with multi-account AWS environments, AWS Organizations, Control Tower, landing zones, service control policies, and centralized governance models.
• Experience with Kubernetes and container platforms, including Amazon EKS, ECS, Docker, Helm, and container security practices.
• Experience with configuration management and automation tools such as Ansible, Chef, Puppet, or Systems Manager.
• Experience with enterprise observability platforms such as Datadog, Dynatrace, Splunk, Elastic, Grafana, Prometheus, or OpenTelemetry.
• Experience with cloud security and compliance frameworks, including NIST, CIS benchmarks, SOC 2, HIPAA, or comparable controls.
• Experience supporting healthcare, regulated, or other security-sensitive environments.
• Experience with data engineering and analytics platforms, including Snowflake, Databricks, or equivalent tools.
• Experience implementing FinOps practices, including cloud cost allocation, tagging standards, budget monitoring, rightsizing, capacity optimization, and chargeback/showback reporting.
• Experience supporting AI/ML or generative AI solutions using Amazon Bedrock, Amazon SageMaker, Databricks Machine Learning, or similar platforms.
• Experience implementing AI governance controls, including data classification, model access management, prompt security, audit logging, content filtering, retrieval-augmented generation, and evaluation/monitoring practices.
• Familiarity with AIOps platforms or approaches for anomaly detection, incident correlation, automated remediation, and intelligent operations.
• Experience using AI-assisted developer tools such as Claude Code, Amazon Q Developer, GitHub Copilot, or equivalent organization-approved tools.

GDIT IS YOUR PLACE:

• At GDIT, the mission is our purpose, and our people are at the center of everything we do.
• AI-powered career tool that identifies career steps and learning opportunities.
• An internal mobility team focused on helping you achieve your career goals.
• Comprehensive benefits and wellness packages, 401K with company match, and competitive pay and paid time off.
• Full-flex work week to own your priorities at work and at home.
• Community: Award-winning culture of innovation and a military-friendly workplace.

OWN YOUR OPPORTUNITY

Explore an enterprise IT career at GDIT and you'll find endless opportunities to grow alongside colleagues who share your desire to drive operations forward.

The likely salary range for this position is $136,000 - $184,000. This is not, however, a guarantee of compensation or salary. Rather, salary will be set based on experience, geographic location and possibly contractual requirements and could fall outside of this range.

Scheduled Weekly Hours: 40

Travel Required: None

Telecommuting Options: Remote

Work Location: Any Location / Remote

Additional Work Locations:

Total Rewards at GDIT: Our benefits package for all US-based employees includes a variety of medical plan options, some with Health Savings Accounts, dental plan options, a vision plan, and a 401(k) plan offering the ability to contribute both pre and post-tax dollars up to the IRS annual limits and receive a company match. To encourage work/life balance, GDIT offers employees full flex work weeks where possible and a variety of paid time off plans, including vacation, sick and personal time, holidays, paid parental, military, bereavement and jury duty leave. GDIT typically provides new employees with 15 days of paid leave per calendar year to be used for vacations, personal business, and illness and an additional 10 paid holidays per year. Paid leave and paid holidays are prorated based on the employee's date of hire. The GDIT Paid Family Leave program provides a total of up to 160 hours of paid leave in a rolling 12 month period for eligible employees. To ensure our employees are able to protect their income, other offerings such as short and long-term disability benefits, life, accidental death and dismemberment, personal accident, critical illness and business travel and accident insurance are provided or available. We regularly review our Total Rewards package to ensure our offerings are competitive and reflect what our employees have told us they value most.

Our Identity Verification Process: As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during virtual interviews. We reserve the right to take your picture to verify your identity and prevent fraud. By proceeding, you authorize the collection, processing, and use of your biometric data for identity verification and security purposes.

About Our Work: We are GDIT. A global technology and professional services company that delivers technology solutions and mission services to every major agency across the U.S. government, defense and intelligence community. Our 26,000 experts extract the power of technology to create immediate value and deliver solutions at the edge of innovation. We operate across 50+ countries worldwide, offering leading mission-ready capabilities in AI, cloud, cyber and software development.

Join our Talent Community to stay up to date on our career opportunities and events at gdit.com/tc .

Equal Opportunity Employer / Individuals with Disabilities / Protected Veterans

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GDIT supports and secures some of the most complex government, defense, and intelligence projects across the country.