Senior Cloud Solutions Engineer

Jobtailor

Bethesda (MD)

On-site

USD 140,000 - 180,000

Full time

7 days ago

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Job summary

Jobtailor in Bethesda, MD is seeking an experienced Architect to lead Azure cloud solutions for cutting-edge AI workloads. You will design scalable architectures, integrate AI services, and drive DevOps/CI/CD practices across teams.

Expect collaboration with security and compliance teams, mentoring of engineers, and hands-on development of Terraform modules. A Public Trust clearance may be required for NIH-related work.

Qualifications

BS/BA in IT or related field with 8+ years of IT experience.
Significant experience architecting cloud solutions in complex enterprises.
Deep hands-on Azure experience across compute, networking, storage, identity, security, monitoring, APIs.
Experience with AI/LLM architectures, including vector search, RAG patterns, or related tech.
Strong IaC and automation using Terraform; ability to contribute to Git-based repositories.

Responsibilities

Architect, implement, and evolve Azure cloud solutions supporting AI architectures.
Support multimodal LLMs, vector search, RAG, and distributed cloud AI services.
Partner with developers, security teams, and stakeholders to gather requirements.
Translate needs into scalable cloud architectures and engineering plans.
Design end-to-end Azure solutions covering compute, storage, networking, IAM, APIs, data services.
Develop Terraform modules and automation for cloud infrastructure.
Mentor engineers and support security/compliance activities.
Lead cloud architecture efforts for NIH-related cloud deployments with GDIT.

Skills

Microsoft Azure Architecture

Infrastructure as Code

AI/LLM Services Implementation

DevOps and CI/CD Practices

Cloud Security and IAM

Education

BS/BA in IT or related field

Tools

Terraform

Git

Python

PowerShell

TypeScript

JavaScript

Job description

Architect, implement, and evolve Azure cloud solutions supporting ChIRP and modern AI application architectures
Support multimodal LLMs, Retrieval-Augmented Generation, 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 and evaluate technical alternatives
Translate 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, and AI services
Develop and maintain Terraform modules, scripts, configuration, and automation for cloud infrastructure
Codify engineering standards, reduce manual effort, and improve scalability, reliability, and operational efficiency
Design and integrate DevOps and CI/CD capabilities for infrastructure and application deployment
Implement automated testing, security scanning, application health validation, and lifecycle management
Monitor and optimize application and infrastructure performance, reliability, security, and cost
Use logging, telemetry, alerting, incident response, and cloud resource governance
Troubleshoot complex issues across application and infrastructure layers
Serve as senior technical resource and technical lead for the cloud architecture supporting ChIRP
Apply second-order thinking to architectural decisions and communicate technical tradeoffs and recommendations
Mentor engineers and support security, compliance, and ATO activities
Work with a Cloud DevOps team supporting NIH’s intramural research community through GDIT’s technology and professional services

Requirements

BS/BA and 8+ years of relevant IT experience, or equivalent experience
Significant experience architecting and engineering cloud solutions in complex enterprise environments
Deep hands‑on Microsoft Azure experience across compute, networking, storage, identity, security, monitoring, APIs, and application‑hosting services
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
Experience developing custom Terraform modules, contributing to shared Git-based codebases, and automating infrastructure deployment and operations
Strong knowledge of cloud networking, identity and access management, and security, including VNets, 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
Strong architecture, troubleshooting, consulting, and communication skills
Demonstrated ability to independently own complex solutions, translate requirements into technical architectures, evaluate downstream impacts and tradeoffs, mentor engineers, and collaborate with technical and non‑technical stakeholders
Ability to obtain and maintain a Public Trust
Ability to provide onsite fingerprinting at a designated facility
Preferred: Experience with Azure AI Foundry, Azure OpenAI, ChatGPT, Gemini, vector search, RAG, AI agents, MCP, or comparable platforms
Preferred: Strong software development and automation experience using Python, PowerShell, TypeScript/JavaScript, or similar languages
Preferred: Relevant Microsoft Azure, AI, Terraform, DevOps, or architecture certifications
Preferred: Experience supporting scientific research, federal government, healthcare, life sciences, or similarly regulated environments

Core Competencies

Demonstrates expertise in architecting and engineering Azure cloud solutions, with a strong focus on modern AI application architectures and Infrastructure as Code using Terraform. Capable of translating complex requirements into scalable cloud architectures while ensuring security, compliance, and operational efficiency.

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