Software Engineer - AI Engineer
Wells Fargo1 day ago
Hyderābād, IndiaMid Level / Senior
Responsibilities
- Design, develop, and deploy enterprise AI applications and Generative AI solutions using LLMs, Agentic AI, RAG, and knowledge retrieval architectures.
- Build scalable Python applications, APIs, microservices, automation frameworks, and distributed systems.
- Design and implement data engineering and ETL pipelines using Databricks, Spark, and distributed processing technologies.
- Develop AI assistants, intelligent chatbots, knowledge retrieval platforms, document intelligence solutions, and AI-driven automation capabilities.
- Build and optimize semantic search and knowledge retrieval systems using embeddings, vector databases, information retrieval techniques, and Neo4j knowledge graphs.
- Create secure, scalable cloud-native applications and contribute to AI/LLMOps frameworks, reusable accelerators, and enterprise AI capabilities.
- Collaborate with cross-functional teams, participate in code reviews and architectural discussions, and support production deployment.
- Contribute to engineering standards, best practices, observability, security, automated testing, and reliable AI delivery.
Requirements
- At least 2 years of software engineering experience, or equivalent demonstrated through work experience, training, military experience, education, or a combination of these.
- Strong Python development experience, including object-oriented design, design patterns, asynchronous programming, API development, automation, performance tuning, and debugging.
- Preferred experience of 3-6 years developing and delivering enterprise-scale applications, platforms, and distributed systems.
- Preferred 1-3 years of experience building LLM-based Generative AI applications using GPT or enterprise LLMs, LangChain, LangGraph, RAG, prompt engineering, embeddings, and semantic retrieval.
- Experience with data engineering and large-scale data processing, including ETL/ELT pipelines, data ingestion frameworks, orchestration, and transformation processes.
- Experience using Spark, Pandas, Databricks, and other distributed computing platforms.
- Experience developing enterprise AI applications such as AI assistants, intelligent chatbots, knowledge retrieval platforms, document intelligence solutions, and AI-driven automation.
- Understanding of knowledge management and search architectures, including Pinecone, OpenSearch, FAISS, ChromaDB, Neo4j knowledge graphs, semantic search, NLP, and information retrieval frameworks.
- Experience building REST APIs, microservices, and cloud-native applications using GCP and associated AI/ML services.
- Knowledge of SQL, NoSQL, graph databases, data modeling, and enterprise data architecture principles.
- Understanding of software engineering practices including automated testing, code reviews, observability, security, DevOps, CI/CD, Agile methodologies, AI/LLMOps, and production deployment frameworks.
Tech Stack
Categories
AI ApplicationsData Engineering
About Wells Fargo
Wells Fargo & Company is a U.S.-based financial services firm providing consumer and commercial banking, mortgages, credit, and wealth/investment services to individuals, small businesses, and enterprises. It earns revenue from interest income and fees across retail banking, payments, lending, and capital markets. Founded in 1852 and headquartered in San Francisco, it is publicly traded on the NYSE (WFC) and operates nationally with offices in multiple countries.