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 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.
- Design and implement MLOps and LLMOps frameworks for model lifecycle management, deployment, monitoring, governance, and optimization.
- Build scalable data pipelines and knowledge ingestion frameworks to support AI workloads.
- Enable AI adoption across ETRM processes including trading operations, risk management, analytics, and decision support.
Required Skills & Qualifications
- 12+ years of overall experience in software design, development, and architecture, with at least 2+ years of hands-on experience designing and delivering Generative AI and Agentic AI solutions at enterprise scale.
- 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.
- Strong MLOps and LLMOps experience including model deployment, monitoring, evaluation, and governance.
- Expertise in cloud-native architectures on Azure, AWS, or Google Cloud.
- Strong understanding of microservices, APIs, Kubernetes, event-driven architectures, and enterprise integration patterns.
- Experience building large-scale data ingestion and processing pipelines.
Preferred Qualifications
Exposure to Responsible AI, AI governance, and regulatory compliance frameworks. Relevant cloud, AI, or enterprise architecture certifications.
