AI Solutions Architect (Agentic AI)

Key Responsibilities

• AI Solution Architecture Design
• Lead the technical architecture of AI-powered applications utilizing Azure OpenAI and Large Language Models (LLMs).
• Define scalable architectures for autonomous AI agents, multi-agent systems, orchestration workflows, and tool integrations.
• Evaluate emerging AI technologies and recommend innovative solutions aligned with business objectives.
• Application Development
• Design and develop enterprise applications using Java and modern software architecture principles.
• Architect RESTful APIs and service integrations supporting AI-driven workflows.
• Collaborate with engineering teams to integrate AI services into enterprise applications and business processes.
• Guide implementation of event-driven, cloud-native, and microservices-based architectures.
• Agentic AI & Azure OpenAI Design, Implement, and Deploy
• Design, implement, and deploy production-grade Agentic AI solutions using Azure OpenAI services.
• Develop autonomous AI agents capable of planning, reasoning, tool usage, workflow orchestration, and decision-making.
• Integrate enterprise knowledge sources, APIs, databases, and business systems with AI agents.
• Implement prompt engineering, retrieval-augmented generation (RAG), memory management, and agent orchestration strategies.
• Optimize AI models for performance, scalability, latency, reliability, and cost efficiency.
• Cloud & Production Deployment
• Design cloud-native AI architectures on Microsoft Azure.
• Support CI/CD pipelines and automated deployment of AI applications.
• Ensure production readiness through monitoring, observability, logging, security, and governance.
• Define disaster recovery, scalability, and high-availability strategies for AI workloads.
• Technical Leadership
• Lead architecture workshops and technical design sessions with business and engineering teams.
• Mentor software engineers, AI developers, and solution architects.
• Conduct architecture reviews, code reviews, and technical governance assessments.
• Drive technical decision-making while ensuring alignment with enterprise standards and business goals.

Required Qualifications

• Minimum 7+ years of experience in software architecture and enterprise application development.
• Proven hands-on experience deploying Agentic AI solutions into production environments.
• Strong expertise in Java and enterprise application architecture.
• Extensive experience with Azure OpenAI Service and Large Language Models (LLMs).
• Experience designing AI agent workflows, orchestration frameworks, and intelligent automation solutions.
• Strong understanding of REST APIs, microservices architecture, and cloud-native application design.
• Experience integrating AI applications with enterprise systems and external APIs.
• Knowledge of AI governance, security, responsible AI, and model lifecycle management.
• Experience working within Agile software development environments.
• Excellent communication, presentation, and stakeholder management skills.