Sr. Solution Architect _ Generative Ai

The DCRS Inbound Correspondence Team is seeking a Senior Generative AI Solutions Architect to lead the design and scaling of an enterprise-grade Document Intelligence platform within the DCRS Inbound Correspondence organization. This role will define architecture for LLM-powered solutions that enable document classification, intelligent data extraction, and retrieval-augmented generation (RAG) across large, complex document ecosystems. The ideal candidate combines deep expertise in GenAI, distributed systems, and enterprise architecture, with a strong focus on performance, governance, and regulatory compliance. Key Responsibilities

• Architect and deliver scalable GenAI solutions for: o Document classification and routing o Data extraction and entity recognition o Knowledge retrieval and Q&A using RAG

• Design and optimize end-to-end RAG architectures, including: o Embeddings and chunking strategies o Vector database selection and tuning o Retrieval, re-ranking, and response generation

• Lead deployment strategies for LLM inference at scale, partnering with infrastructure teams on: o GPU-based environments (vLLM, Triton) o Performance tuning and cost optimization

• Establish and implement model governance frameworks, including: o Explainability and traceability o Audit trails and compliance alignment o Evaluation pipelines and model benchmarking

• Define reference architectures, standards, and best practices for GenAI adoption across the enterprise

• Produce architecture artifacts: o Diagrams, design documents, and technical roadmaps o Executive-level presentations and decision materials

• Collaborate across Engineering, Product, Risk, and Compliance to ensure safe, scalable, and business-aligned solutions

Must Have Technical/Functional Skills Primary Skill: Data science, architecture, genAI architecture Secondary: Python, LLM, AI/ML, Vector search tech(Elasticsearch, pinecone, FAISS) Experience: 8 to 10 years, * 8+ years of experience in software or solution architecture

• 3+ years of experience in AI/ML or Generative AI

• Strong hands-on expertise with: o LLMs and GenAI frameworks (OpenAI, Hugging Face, LLaMA, Mistral) o Embeddings and vector search technologies (Elasticsearch, Pinecone, FAISS)

• Advanced proficiency in Python, including: o FastAPI o LangChain / LlamaIndex

• Proven experience designing and implementing RAG-based solutions at enterprise scale

• Experience with: o GPU-based model serving and optimization (vLLM, Triton) o Cloud-native architectures and microservices o MLOps practices (CI/CD, monitoring, versioning)

• Strong understanding of risk, compliance, and governance frameworks in regulated environments

• Excellent communication skills, with the ability to present comple x technical concepts to executive stakeholders Preferred Qualifications

• Master’s degree in computer science, Data Science, or related field
• Experience delivering Document AI or correspondence processing platforms

• Demonstrated ability to: o Lead architecture from concept through production o Operate independently with strong ownership

• Strong problem-solving and analytical capabilities
• Experience navigating enterprise data ecosystems and cross-LOB collaboration
• Ability to manage multiple priorities in a fast-paced environment Work Model, BACHELOR OF COMPUTER SCIENCE