Role: Data science/AI Architect
Location: Addison, TX (ONSITE)
Exp: 12+ years
Full Time
Must Have Technical/Functional Skills
Primary Skill: Data science, architecture, genAI architecture
Secondary: Python, communication
Experience: 10+ years
Roles & Responsibilities
Required Experience & Technical Skills
· 8+ years of software/solution architecture experience, including 3+ years in AI/ML or Generative AI.
· Hands-on experience with LLMs, embeddings, and vector search technologies (OpenAI, Hugging Face, Llama, Elasticsearch).
· Strong Python development skills, including Fast API and Lang Chain.
· Experience with GPU optimization, cloud-native deployments, and ML Ops practices.
· Excellent communication and presentation skills, including presenting to executive leadership.
Education & Professional Attributes
· Master’s degree in computer science, Data Science, or a related technical discipline.
· Experience collaborating with diverse business and technology stakeholders across multiple Lines of Business.
· Highly motivated self-starter with strong ownership and ability to execute independently.
· Strong critical thinking and problem-solving capabilities.
· Ability to navigate enterprise data assets across multiple functions.
· Highly organized with the ability to manage multiple priorities in a fast-paced environment.
· Strong analytical and customer-focused mindset.
Key Responsibilities
· Design and scale enterprise-grade Document AI platforms for the financial services industry.
· Lead architecture for document classification, data extraction, and Retrieval-Augmented Generation (RAG) solutions.
· Architect GenAI solutions for large-scale document processing, extraction, and question-answering.
· Build and optimize RAG pipelines using embeddings, vector databases, rerankers, and LLMs.
· Partner with infrastructure teams to deploy AI solutions on GPU clusters using technologies such as vLLM and Triton.
· Drive model risk management, explainability, auditability, and evaluation frameworks.
· Create architecture diagrams, technical documentation, and executive-level presentations.
· Collaborate closely with engineering, product, and compliance teams to deliver secure, scalable AI solutions.