GDIT is looking foraSeniorCloudSolutions Engineerto join ourNational Institutes of Health (NIH)CIT Hosting and Storage ServicesProgramsupportingChIRP, a custom generative AI platformdesigned to support the NIH intramural research community.

We areseekinga highly experienced and customer-focused cloud engineer to architect, build, and evolve secure, scalable, and reliable cloud solutions supporting generative AI and scientific research. Our ideal candidate combines deep Microsoft Azureexpertisewith a strong understanding of modern application architecture, AI/LLM technologies, infrastructure, networking, identity, security, automation, and DevOps practices.

As a senior member of our Cloud DevOps team, this engineer will serve as a technical lead for the cloud architecture supportingChIRPand its evolving capabilities. They will work closely with application developers, AI engineers, security teams, customers, and other stakeholders to translate application and research requirements into well-designed cloud solutions. The successful candidate will take ownership of complex solutions from architecture through implementation and operations, develop Infrastructure as Code and automation, and apply sound engineering judgment andsecond-orderthinking to ensure technical decisions account for security, scalability, resiliency, performance, cost, maintainability, and long-term customer needs.

Location: Remote working candidates will be considered; however the preference is for candidates to go onsite to Bethesda, MD 3 days out of the week. If you're within 60 miles of customer site, we would look for you to go onsite, as needed.

This role will require you to obtain andmaintaina Public Trust and will require you to provide onsite fingerprinting at a designated facility.This investigation may review personal and criminal behavior, financial conduct, foreign influence, as well as other adjudications.

Responsibilities:

• Architect, implement, and evolve Azure cloud solutions supportingChIRPand modern AI application architectures, including multimodal LLMs, Retrieval-Augmented Generation (RAG), vector search, knowledge integration, agentic capabilities, MCP integrations, and distributed cloud AI services.

• Partner with application developers, AI engineers, security teams, customers, and stakeholders to gather requirements, evaluate technical alternatives, and translate evolving application and scientific research needs into scalable cloud architectures and engineering plans.

• Engineer end-to-end Azure solutions incorporating compute, storage, networking, identity and access management, security, APIs, data services, observability, AI services, and other cloud capabilitiesrequiredto support the application.

• Develop andmaintainTerraform modules, scripts, configuration, and automation to provision and manage cloud infrastructure, codify engineering standards, reduce manual effort, and improve scalability, reliability, and operational efficiency.

• Design and integrate DevOps and CI/CD capabilities supporting infrastructure and application deployment, automated testing, security scanning, application health validation, and lifecycle management.

• Monitor andoptimizeapplication and infrastructure performance, reliability, security, and cost using logging, telemetry, alerting, incident response, and cloud resourcegovernance, while troubleshooting complex issues across application and infrastructure layers.

• Serve as a senior technical resource for the solution, applying second-order thinking to architectural decisions, mentoring engineers, communicating technical tradeoffs and recommendations, and supporting security, compliance, and ATO activities.

Required Qualifications:

• BS/BA and 8+ years of relevant IT experience, or equivalent experience, includingsignificant experiencearchitecting and engineering cloud solutions in complex enterprise environments.

• Deep hands-on Microsoft Azure experience acrosscompute, networking, storage, identity, security, monitoring, APIs, and application-hosting services, with experience designing scalable, resilient, and secure cloud architectures.

• Experience implementing or supporting modern AI/LLM architectures and services, including Azure AI capabilities, vector search or databases, knowledge integration, RAG patterns, or comparable generative AI technologies.

• Strong Infrastructure as Code and automation experience using Terraform and related technologies, including developing custom modules, contributing to shared Git-based codebases, and automating infrastructure deployment and operations.

• Strong knowledge of cloud networking, identity and access management, and security, includingVNets, load balancing, API gateways, firewalls, routing, Entra ID, RBAC, conditional access, certificates, secrets, encryption, logging, and security controls.

• Experience with application development lifecycles and DevOps/CI/CD practices, including automated infrastructure and application deployment, testing, security scanning, monitoring, and operational support.

• Strong architecture, troubleshooting, consulting, and communication skills, withdemonstratedability to independently own complex solutions, translate requirements into technical architectures, evaluate downstream impacts and tradeoffs, mentor engineers, and collaborate effectively with technical and non-technical stakeholders.

Preferred Qualifications:

• Experience designing and integrating generative AI solutions using technologies such as Azure AI Foundry, Azure OpenAI, ChatGPT, Gemini, vector search, RAG, AI agents, MCP, or comparable AI platforms and integration patterns.

• Strong software development and automation experience using Python, PowerShell, TypeScript/JavaScript, or similar languages to develop APIs, integrations, automation, and supporting cloud services.

• Relevant Microsoft Azure, AI, Terraform, DevOps, or architecture certifications and experience supporting scientific research, federal government, healthcare, life sciences, or similarly regulated environments.