Lead AI Engineer
Wells Fargo1 day ago
Hyderābād, IndiaStaff+
Responsibilities
- Lead the design, development, and deployment of enterprise-scale AI platforms and Generative AI solutions.
- Build scalable Python applications, APIs, microservices, automation frameworks, and distributed data engineering pipelines.
- Design and implement ETL/ELT, ingestion, orchestration, transformation, and enrichment pipelines using Databricks, Spark, and distributed processing frameworks.
- Develop LLM-based applications, agentic AI and multi-agent systems, AI assistants, copilots, chatbots, document intelligence solutions, and AI-driven automation.
- Build knowledge retrieval platforms using semantic search, vector databases, embeddings, information retrieval techniques, and Neo4j knowledge graphs.
- Establish secure, reliable, production-ready engineering and AI/LLMOps standards, including deployment, observability, testing, and governance practices.
- Collaborate with senior technology leaders, data engineers, architects, and business stakeholders to solve complex technical challenges.
- Mentor engineering teams and lead strategic technology initiatives that accelerate enterprise AI adoption.
Requirements
- At least 5 years of software engineering experience, or equivalent demonstrated through work experience, training, military experience, education, or a combination of these.
- Preferred: 8 or more years developing and delivering enterprise-scale applications, platforms, and distributed systems.
- Expertise in Python, object-oriented design, design patterns, asynchronous programming, API development, automation, performance tuning, and debugging.
- Extensive data engineering and large-scale data processing experience, including scalable ETL/ELT pipelines, data ingestion, orchestration, and transformation.
- At least 3 years of hands-on experience building production-grade LLM-based applications and Generative AI solutions.
- Experience with GPT, enterprise LLMs, LangChain, LangGraph, RAG, agentic AI, multi-agent systems, prompt engineering, embeddings, and semantic retrieval.
- Experience designing and deploying enterprise AI applications such as assistants, copilots, intelligent chatbots, knowledge retrieval platforms, document intelligence systems, and AI automation solutions.
- Deep understanding of vector databases, retrieval technologies, knowledge management, search architectures, NLP, information retrieval, and Neo4j knowledge graphs.
- Experience building secure, scalable, cloud-native applications and microservices using GCP and associated AI/ML services.
- Expertise with SQL, NoSQL, graph databases, data modeling, and enterprise data architecture.
- Understanding of automated testing, code reviews, observability, security, DevOps, CI/CD, 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.