Role Summary We are seeking an experienced AI Architect to lead the design and implementation of enterprise-grade AI solutions, with a strong focus on Agentic AI, Generative AI, and AI-native applications within the Energy Trading & Risk Management (ETRM) domain. The ideal candidate will be responsible for architecting AI-ready platforms, establishing robust AI governance and guardrails, and partnering with clients to design scalable, secure, and production-ready AI solutions that drive business value. Key Responsibilities • Partner with clients and business stakeholders to identify AI use cases and translate requirements into scalable technical solutions. • Lead architecture discussions, solution design workshops, and technical governance reviews. • Define and implement AI Native Enterprise Applications or Integrations on various tech stacks and cloud platforms, based on client needs. • Define and implement enterprise AI architecture and technology roadmaps aligned with business objectives. • Design and deploy AI-ready infrastructure with appropriate governance, security, compliance, observability, and responsible AI guardrails. • Establish reference architectures, best practices, and reusable frameworks for GenAI and Agentic AI implementations. • Architect and implement scalable Agentic AI solutions using modern orchestration frameworks. • Design multi-agent workflows, autonomous reasoning systems, tool integrations, and human-in-the-loop capabilities. • Develop Retrieval-Augmented Generation (RAG) architectures leveraging enterprise knowledge sources. • Build scalable data pipelines and knowledge ingestion frameworks to support AI workloads if needed. • Enable AI adoption across ETRM processes including trading operations, risk management, analytics, and decision support. Required Skills & Qualifications • 8-13 years of overall experience in enterprise grade software development, design and architecture. • At least 2+ years of hands-on experience designing and delivering Generative AI and Agentic AI solutions at enterprise scale. • Minimum 6 Years of hands-on full stack application development experience. • Strong understanding of microservices, APIs, Kubernetes, event-driven architectures, and enterprise integration patterns. • Expertise in Large Language Models (LLMs), foundation models, and Generative AI architectures. • Hands-on experience designing and deploying Agentic AI applications in production environments. • Deep expertise in Retrieval-Augmented Generation (RAG), vector databases, prompt engineering, and agentic workflows. • Strong experience with LangChain, LangGraph, Semantic Kernel, AutoGen, or similar frameworks. • Experience with Azure OpenAI, OpenAI, Anthropic, Gemini, or equivalent enterprise LLM platforms. • Expertise in cloud-native architectures on Azure, AWS, or Google Cloud.