Data science/AI Architect 431141

We are looking for an experienced GenAI / Data Science Architect to lead the design and architecture of enterprise-grade AI and Generative AI solutions, with a strong focus on Document AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and intelligent document processing. The ideal candidate will have 10+ years of overall experience, including significant experience in software/solution architecture and AI/ML or GenAI. This role requires strong technical expertise, hands-on development capabilities, and the ability to collaborate with engineering, product, infrastructure, compliance, and executive stakeholders. Key Responsibilities Design and scale enterprise-grade Document AI platforms for the financial services industry. Lead architecture for document classification, data extraction, OCR/intelligent document processing, and RAG solutions. Architect Generative AI solutions for large-scale document processing, information extraction, and question-answering. Design and optimize RAG pipelines using embeddings, vector databases, rerankers, and LLMs. Work with technologies such as OpenAI, Hugging Face, Llama, Elasticsearch, LangChain, and FastAPI. Partner with infrastructure teams to deploy and optimize AI workloads on GPU clusters, leveraging technologies such as vLLM and Triton. Define scalable, secure, highly available, and cloud-native AI architectures. Drive MLOps, model lifecycle management, model evaluation, monitoring, and performance optimization. Establish frameworks for model risk management, explainability, auditability, security, and responsible AI. Create architecture diagrams, technical specifications, solution documentation, and executive-level presentations. Collaborate closely with engineering, product, data, infrastructure, security, risk, and compliance teams. Translate complex business requirements into scalable AI/ML and GenAI solutions.

Provide technical leadership and mentorship to engineering and data science teams. Required Experience & Technical Skills 10+ years of overall technology experience, with 8+ years in software/solution architecture. Minimum 3+ years of experience in AI/ML, Generative AI, or Data Science architecture. Strong hands-on experience with LLMs, embeddings, vector search, and RAG architectures. Experience with platforms and technologies such as OpenAI, Hugging Face, Llama, and Elasticsearch. Strong Python development skills. Experience with FastAPI, LangChain, and modern AI/ML frameworks. Experience designing enterprise-scale AI/GenAI architectures. Strong understanding of GPU optimization and inference technologies, including vLLM and Triton. Experience with cloud-native deployments, containers, Kubernetes, and MLOps practices. Knowledge of AI evaluation, model monitoring, security, governance, and responsible AI. Strong understanding of enterprise data architecture and the ability to navigate data assets across multiple business functions. Excellent communication, presentation, and stakeholder-management skills, including the ability to present solutions to executive leadership. Education & Professional Attributes Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related technical discipline preferred. Strong experience working with diverse business and technology stakeholders across multiple Lines of Business. Highly motivated self-starter with strong ownership and the ability to execute independently. Excellent critical thinking, analytical, and problem-solving skills. Strong customer-focused mindset with the ability to understand and translate business requirements into technical solutions. Highly organized and capable of managing multiple priorities in a fast-paced enterprise environment. Strong written and verbal communication skills. Ability to explain complex AI/ML concepts to both technical and non-technical audiences. Preferred Skills Experience in financial services, banking, insurance, or other highly regulated industries. Experience with enterprise Document AI and Intelligent Document Processing (IDP). Knowledge of OCR, document classification, information extraction, and multimodal AI. Experience with vector databases and search technologies. Understanding of AI governance, model risk management, compliance, and audit requirements. Experience architecting highly scalable and secure GenAI platforms. What We’re Looking For We are seeking a technology leader who combines strong architecture expertise, hands-on GenAI/Data Science capabilities, and excellent stakeholder communication. The successful candidate will play a key role in defining and delivering the next generation of enterprise AI solutions.