Senior Specialty AI Engineer

Wells Fargo • Charlotte, NC

1d • Hybrid

About The Position

Wells Fargo is seeking a Senior Specialty AI Engineer to design, build, and productionize GenAI applications end-to-end. You will contribute to the development of LangChain/LangGraph-based workflows, RAG pipelines, and scalable services on Google Vertex AI. You will collaborate with senior engineers and cross-functional teams to deliver reliable, secure, and cost-efficient AI solutions while building depth across architecture, MLOps, and evaluation.

Requirements

• 4+ years of Specialty Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
• 4 years of AI/ML Software Engineering experience, or equivalent
• Hands-on experience with LangChain (required) and exposure to LangGraph or similar orchestration frameworks.
• Experience building RAG pipelines (chunking, embeddings, retrieval, evaluation basics).
• Familiarity with vector databases (Pinecone, Weaviate, FAISS, or similar).
• Backend development experience in Python (FastAPI) or Node.js.
• Frontend experience with React or Next.js.
• Experience with Docker, basic Kubernetes concepts, and CI/CD pipelines.
• Understanding of GenAI evaluation concepts, observability basics, and prompt design.
• Knowledge of security fundamentals (API security, PII handling, secrets management).
• Strong problem-solving and communication skills.

Nice To Haves

• Exposure to LangGraph advanced patterns (state machines, multi-agent flows).
• Experience with LlamaIndex or structured RAG (SQL/Graph RAG).
• Familiarity with rerankers (Cohere, bge) and retrieval optimization techniques.
• Experience integrating LLMs with enterprise tools, databases, or APIs.
• Basic knowledge of knowledge graphs or ontology design.
• Exposure to LLM observability tools (LangSmith, OpenTelemetry).

Responsibilities

• Develop multi-step workflows using LangChain and LangGraph (chains, tools, basic state graphs, retries, and error handling).
• Implement prompt templates, tool integrations, and memory patterns for GenAI applications.
• Contribute to observability setup (logging, tracing, prompt/version tracking) and basic guardrails.
• Build and maintain ingestion pipelines: document parsing, chunking, embeddings, and metadata tagging.
• Implement retrieval strategies such as dense search, hybrid retrieval (BM25 + vector), and reranking.
• Configure and manage vector databases (e.g., Pinecone, Weaviate, FAISS).
• Develop and deploy services using Google Vertex AI (model endpoints, pipelines, vector search).
• Assist in containerization (Docker) and deployment via Kubernetes/GKE.
• Contribute to CI/CD workflows (GitHub Actions, Cloud Build).
• Build backend APIs using Python (FastAPI) or Node.js.
• Develop user-facing components using React/Next.js.
• Implement authentication, authorization, and API management (rate limiting, retries).
• Work closely with product, data, and platform teams to deliver features.
• Contribute to engineering best practices (code quality, testing, documentation).
• Learn and adopt emerging GenAI tools, frameworks, and patterns.

Benefits

• Wells Fargo is an equal opportunity employer.
• Accommodation for applicants with disabilities is available upon request in connection with the recruitment process.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed