Senior Cloud Solutions Engineer

Responsibilities

• Architect, implement, and evolve Azure cloud solutions supporting ChIRP and 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 capabilities required to support the application.
• Develop and maintain Terraform 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 and optimize application and infrastructure performance, reliability, security, and cost using logging, telemetry, alerting, incident response, and cloud resource governance, 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.

Qualifications

• BS/BA and 8+ years of relevant IT experience, or equivalent experience, including 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, 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, 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, including automated infrastructure and application deployment, testing, security scanning, monitoring, and operational support.
• Strong architecture, troubleshooting, consulting, and communication skills, with demonstrated ability 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.