About this role:
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.
In this role, you will:
Agentic Workflows & Orchestration
Required Qualifications
- 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.
Job Expectations:
- This position offers a hybrid work schedule
- This position is not eligible for Visa sponsor
Desired Qualifications:
- 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).