Cloud and Artificial Intelligence Architect

Cloud + AI Architect

• Lead solution architecture and technical design for Cloud and AI programs across AWS, Azure, or GCP. • Translate business requirements into end-to-end solution architectures, covering application, data, AI/ML, security, DevOps, and operations. • Define reference architectures, design standards, and best practices for Cloud, AI, and automation. • Architect and guide delivery of AI-driven solutions, including AI Agents, RAG pipelines, LLM-based systems, and intelligent automation. • Drive cloud modernization and migration strategies, leveraging IaC and AI-led accelerators. As a Cloud + AI Architect, you will lead end-to-end solutioning, architecture, and design for large-scale Cloud and AI transformation programs. You will play a key role in shaping technology strategy, reference architectures, and high-impact AI-enabled solutions, while guiding teams across the SDLC. You will collaborate with senior stakeholders to deliver scalable, secure, resilient, and business-aligned solutions. • Review designs, perform architecture trade-offs and risk assessments, and ensure alignment with enterprise standards and well-architected frameworks. • Provide technical leadership and mentoring to engineering teams; enable high-quality, predictable delivery. • Own production outcomes with a build-and-own mindset, ensuring reliability, security, and operational excellence. Cloud & Architecture • Strong hands-on and design experience with AWS / Azure / GCP. • Proven experience in cloud-native and hybrid architectures, scalability, resiliency, security, and cost optimization. • Expertise in Well-Architected Frameworks, enterprise security, and compliance considerations. Infrastructure as Code & DevOps • 3–5 years of experience with Terraform (IaC), including modular design and testing. • Solid understanding of CI/CD pipelines and DevOps practices (Jenkins, GitHub, Harness, etc.). Application Engineering • Strong expertise in Java/Spring Boot or .NET Core (architecture and design focus). • Working knowledge of Python or Go for automation and AI workloads. AI / GenAI & Agentic Systems • Hands-on experience in AI Agents, RAG architectures, LLMOps, and enterprise GenAI solutions. • Experience with agent frameworks such as LangGraph, LangChain, AutoGen, OpenAI Agents SDK. • Experience with cloud AI platforms such as AWS Bedrock Agents, Vertex AI, Google ADK. • Exposure to cloud-native AI services like AWS SageMaker, Azure OpenAI, Foundry, or equivalent.