Cloud & AI Engineer

Job Summary The Cloud & AI Engineer will be part of the Cloud Business Enablement squad, responsible for designing, building, and maintaining enterprise-scale multi-cloud infrastructure across Azure and AWS. This role enables cloud-native AI solutions and agentic AI platforms, ensuring secure, resilient, and innovative adoption of cloud and AI capabilities. The engineer partners with product management, platform engineering, security, networking, and application teams to deliver scalable solutions that meet enterprise standards for compliance, governance, and operational excellence.

Key Responsibilities De sign, build, and maintain Azure and AWS Landing Zones aligned with enterprise security and governance standards. Engineer secure, scalable, and resilient multi-cloud foundations across Azure, AWS, and hybrid environments. Architect and implement Hub-and-Spoke, Transit Network, and shared services patterns with appropriate segmentation and security controls. Enable on-premises to cloud connectivity using VPN, ExpressRoute, Direct Connect, Transit Gateway, DNS, routing, and firewall controls.

Develop and maintain reusable Terraform modules and CI/CD automation pipelines using GitHub Actions. Implement and manage Kubernetes platforms (AKS, EKS) and containerized workloads. Deploy, secure, and operate Azure and AWS cloud services including API Management, Databricks, EC2, S3, RDS, Lambda, and more. Design, develop, and deploy enterprise-grade AI agents and workflows using frameworks such as LangChain, LangGraph, and OpenAI ADK. Apply LLM fundamentals, prompt engineering techniques, and AI agent state management for enterprise use cases.

Collaborate with cross-functional teams to continuously improve cloud operations, automation, governance, and AI enableme nt. Required Qualifications 57 years of IT industry experience in cloud infrastructure, platform engineering, or DevOps. 35 years of proven experience with Azure and AWS cloud technologies. Strong knowledge of Landing Zone architecture, governance, and security controls. Hands-on experience with Terraform, GitHub Actions, and CI/CD automation. Practical experience with Kubernetes (AKS, EKS) and containerized workloads.

Strong Python programming skills for automation and AI application development. Solid understanding of hybrid connectivity (VPN, ExpressRoute, Direct Connect, DNS, firewalls). Hands-on experience with core Azure and AWS services supporting application, data, and AI workloads. Deep understanding of enterprise networking, identity, access management, and observability. Strong knowledge of LLM fundamentals, embeddings, RAG patterns, and responsible AI practices. Practical experience with prompt engineering and AI workflow design.

Exposure to AI agent development, orchestration, and evaluation frameworks.

Preferred Qualifications Experience deploying resilient, multi-region, disaster-recovery aware architectures. Familiarity with Azure AI Foundry, AWS Bedrock, Anthropic Claude, and OpenAI platforms. Experience building AI copilots, intelligent assistants, or agentic automation workflows. Knowledge of Model Context Protocol (MCP), vector databases, semantic search, and RAG pipelines. Valid Azure and/or AWS certifications beyond fundamentals. Experience in financial services, regulated industries, or large-scale enterprise technology organizations. Certifications Azure and/or AWS certifications preferred.

Education: Bachelors Degree Certification: AWS certifications