Data science/AI Architect

Job Title : Data science/AI Architect

Location: Addison, TX (Onsite from first day)

Job Type : Fulltime permanent

Job Summary

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 FastAPI and LangChain.

Experience with GPU optimization, cloud-native deployments, and MLOps 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.