Senior Specialty AI Engineer

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.

- 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.

- 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.

- 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).

- This position offers a hybrid work schedule - This position is not eligible for Visa sponsor

11 Aug 2026 *Job posting may come down early due to volume of applicants.

Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates, including women, persons with disabilities, aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process.