The AI, Software & Cloud Architect is responsible for designing scalable, secure, and business‑aligned technology solutions that combine artificial intelligence, modern software engineering, and cloud platforms. The role provides technical leadership across solution architecture, AI adoption, application modernization, integration design, and cloud‑native delivery. This role works closely with business stakeholders, engineering teams, security, data teams, and platform owners to translate business needs into robust architecture patterns and implementation roadmaps. Key Responsibilities Design end‑to‑end solution architectures across AI, software applications, data platforms, APIs, and cloud services. Define architecture standards, patterns, principles, and reusable reference designs. Lead the design of AI‑enabled solutions, including generative AI, machine learning, automation, intelligent assistants, and analytics‑driven applications. Architect scalable cloud‑native platforms using services across AWS, Azure, GCP, or hybrid cloud environments. Guide application modernization, including microservices, containers, serverless, event‑driven architecture, and API‑led integration. Collaborate with data scientists, ML engineers, software engineers, and cloud engineers to move AI solutions from prototype to production. Ensure solutions meet non‑functional requirements including scalability, availability, performance, resilience, maintainability, and cost efficiency. Review technical designs and provide architecture governance throughout the delivery lifecycle. Support cloud migration strategies, platform selection, workload assessment, and modernization roadmaps. Evaluate emerging AI, software, and cloud technologies and recommend practical adoption approaches. Partner with security architects to ensure security, privacy, compliance, and responsible AI principles are embedded by design. Communicate complex technical concepts clearly to senior stakeholders, business teams, and delivery teams. Required Skills and Experience Strong experience in solution architecture, software architecture, or enterprise architecture. Experience designing cloud solutions on AWS, Azure, GCP, or private cloud platforms. Strong knowledge of cloud‑native architecture, microservices, APIs, containers, Kubernetes, serverless, and DevOps practices. Understanding of AI/ML solution design, including model lifecycle, prompt engineering, MLOps, LLM integration, vector databases, and AI governance. Experience with enterprise integration patterns, event streaming, messaging, and API management. Strong understanding of architecture documentation, design reviews, and technical decision records. Knowledge of data architecture concepts such as data lakes, warehouses, lakehouses, pipelines, and real‑time analytics. Ability to balance strategic architecture thinking with practical implementation constraints. Excellent communication, stakeholder management, and technical leadership skills. Preferred Qualifications Cloud certifications such as AWS Solutions Architect, Azure Solutions Architect, or Google Professional Cloud Architect. AI/ML certifications or practical experience with platforms such as Azure OpenAI, AWS Bedrock, Google Vertex AI, Databricks, Hugging Face, or OpenAI APIs. Experience in regulated industries such as banking, insurance. Experience with architecture frameworks such as TOGAF, ArchiMate, C4, or similar. Experience with CI/CD, infrastructure as code, Terraform, GitHub Actions, GitLab CI, Jenkins, or Azure DevOps. Familiarity with responsible AI, data privacy, model risk management, and AI ethics. Key Success Measures High‑quality architecture designs delivered on time. Increased adoption of reusable architecture patterns. Successful delivery of AI and cloud‑native solutions into production. Improved scalability, resilience, security, and cost efficiency of technology platforms. Strong stakeholder confidence in architecture direction and technical decisions. #J-18808-Ljbffr