Gen AI Architect

Job Description The Gen AI Architect will leverage advanced Generative AI models and Azure OpenAI services to develop innovative solutions for investment banking processes. The ideal candidate will have a strong background in investment banking, hands-on experience with Microsoft Azure OpenAI, and expertise in Retrieval-Augmented Generation (RAG). Responsibilities Define and drive the AI/ML architecture and roadmap, including both traditional machine learning and Generative AI (GenAI) use cases. Design comprehensive end-to-end AI solutions covering data ingestion, feature engineering, model training, inference pipelines, and monitoring frameworks. Lead the integration of Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) frameworks, utilizing tools such as LangChain, LangGraph, or similar. Collaborate with business stakeholders to translate requirements into scalable AI-driven technical solutions. Evaluate and select appropriate AI/ML tools, cloud services, frameworks, and libraries based on use case needs and industry best practices. Ensure models adhere to governance, security, explainability, and regulatory compliance, embedding ethical AI principles into system design. Guide engineering teams in the implementation of AI components, emphasizing scalability, reliability, and performance optimization. Partner with DevOps teams to establish CI/CD pipelines for AI, including model versioning, deployment automation, and ongoing A/B testing. Keep abreast of the latest industry research, breakthroughs, and emerging trends in AI, recommending adoption of best practices and innovative solutions. Requirements Proven experience 10+ years, excel in leading AI/ML architecture and strategy in enterprise environments. Strong expertise in designing and deploying large-scale AI/ML solutions, including LLMs and RAG frameworks. Experience with AI/ML tools and frameworks such as TensorFlow, PyTorch, Hugging Face, LangChain, LangGraph, or similar. Deep understanding of data workflows, feature engineering, model training, evaluation, and deployment. Knowledge of cloud platforms (AWS, Azure, GCP) and services tailored for AI deployment. Familiarity with model governance, security, explainability, and ethical AI standards. Experience in developing CI/CD pipelines for AI/ML, including model versioning, monitoring, and performance tuning. Strong problem-solving, communication, and stakeholder management skills. Preferred, but not required Advanced degree (Ph.D., Master's) in Computer Science, Data Science, AI, or related fields. Publications or practical contributions to AI research and open-source projects. Experience working in regulated industries or environments requiring compliance and governance. Familiar with project management and Agile practices. Cloud Hybrid is an equal opportunity employer inclusive of female, minority, disability and veterans, (M/F/D/V). Hiring, promotion, transfer, compensation, benefits, discipline, termination and all other employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity, age, disability, national origin, citizenship/immigration status, veteran status or any other protected status. Cloud Hybrid will not make any posting or employment decision that does not comply with applicable laws relating to labor and employment, equal opportunity, employment eligibility requirements or related matters. Nor will Cloud Hybrid require in a posting or otherwise U.S. citizenship or lawful permanent residency in the U.S. as a condition of employment except as necessary to comply with law, regulation, executive order, or federal, state, or local government contract. #J-18808-Ljbffr Cloud Hybrid Technologies LLC