Senior Software Engineer - Senior AI Engineer
Wells Fargo · Hyderabad · onsite · Posted 22d ago
Undisclosed4–9 yrsfulltimeSourced from
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About this role
Job Summary
About this role:
Wells Fargo is seeking a Senior Software Engineer - Senior AI Engineer.
Responsibilities - Design, develop, and deploy enterprise AI applications and GenAI solutions leveraging LLMs, Agentic AI, RAG, and knowledge retrieval architectures.
- Develop scalable Python-based applications, APIs, microservices, and data engineering pipelines using cloud-native and distributed processing technologies.
- Contribute to engineering standards, best practices, and AI/LLMOps frameworks to ensure secure, reliable, and production-ready AI solutions.
- Collaborate with technology leaders, data engineers, architects, and business stakeholders to solve technical challenges and deliver innovative solutions.
- Support AI adoption initiatives and contribute to the development of reusable frameworks, accelerators, and enterprise AI capabilities.
- 4+ years of software engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
- Strong software engineering background with 4 years of experience developing and delivering enterprise-scale applications, platforms, and distributed systems, with proficiency in Python, object-oriented design, design patterns, asynchronous programming, API development, automation, performance tuning, and debugging.
- Experience in data engineering and large-scale data processing, including the design and implementation of ETL/ELT pipelines, data ingestion frameworks, orchestration solutions, and transformation processes using technologies such as Spark, Pandas, Databricks, and other distributed computing platforms.
- Hands-on experience building Generative AI solutions, with at least 1-3 years of experience focused on LLM-based applications, utilizing GPT and enterprise LLMs, LangChain, LangGraph, Retrieval-Augmented Generation (RAG), prompt engineering, embeddings, and semantic retrieval techniques.
- Experience developing and supporting enterprise AI applications, including AI assistants, intelligent chatbots, knowledge retrieval platforms, document intelligence solutions, and AI-driven automation capabilities.
- Good understanding of knowledge management and search architectures, including vector databases and retrieval technologies such as Pinecone, OpenSearch, FAISS, ChromaDB, Neo4j knowledge graphs, semantic search, NLP, and information retrieval frameworks.
- Experience building REST APIs, microservices, and cloud-native applications leveraging platforms such as GCP and associated AI/ML services.
- Knowledge of database technologies, including SQL, NoSQL, and graph databases, data modeling, and enterprise data architecture principles.
- Understanding of modern software engineering practices, including CI/CD, DevOps, automated testing, code reviews, observability, security, Agile methodologies, AI/LLMOps, and production deployment frameworks.
- Demonstrate strong expertise in Python development, building scalable, high-performance applications, automation frameworks, APIs, and enterprise-grade solutions using modern software engineering principles.
- Design and implement robust data engineering and ETL pipelines leveraging Databricks, Spark, and distributed processing frameworks to ingest, transform, and manage structured and unstructured datasets.
- Develop and enhance Generative AI solutions using Large Language Models (LLMs), Agentic AI, LangChain, LangGraph, and Retrieval-Augmented Generation (RAG) frameworks to solve business challenges and improve productivity.
- Build and optimize knowledge retrieval platforms through semantic search, vector databases (Pinecone, OpenSearch, FAISS), Neo4j knowledge graphs, embeddings, and advanced information retrieval techniques.
- Develop secure, scalable, and cloud-native enterprise AI applications, including copilots, intelligent assistants, automation platforms, and document intelligence solutions using microservices, APIs, AI/LLMOps practices, CI/CD pipelines, and production deployment frameworks.
- Collaborate effectively with cross-functional teams, participate in code reviews, contribute to architectural discussions, and support the delivery of high-quality AI solutions from development through production deployment.
- Total Experience: 4 Years
- AI / GenAI Experience: 1-3 Years
- Level: Software Engineer / AI Engineer
- Focus Areas: Python Development, Data Engineering, Generative AI, RAG, Agentic AI, APIs, Cloud-Native Development, Knowledge Retrieval Systems, AI/LLMOps.
Sourced from naukri
Skills
AutomationAgileCI/CD Pipelinesai assistantsapisautomated testingdata architectureai engineerAsynchronouscloudArchitecturecomplianceCustomer RelationshipsAi SolutionsAPI DevelopmentArtificial Intelligence
About Wells Fargo
Wells Fargo
Financial Services
20k+
employees
1852
174 years old
Bengaluru/Bangalore, Karnataka
India
About
Wells Fargo works to create positive social impact in the communities it serves by supporting housing affordability, small business growth, financial health, and a low-carbon economy.
Industries
Financial Services
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8,681 reviews
3.6/ 5
Culture
3.5
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Work-life
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