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Lead AI Engineer

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Lead AI Engineer in Others new

  • Wells Fargo
  • Full time
  • Email
  • Hyderābād, India

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.

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, an...

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