Senior Software Engineer - Gen AI

About this role: Wells Fargo is seeking a Senior Software Engineer In this role, you will: Lead moderately complex initiatives and deliverables within technical domain environments Contribute to large scale planning of strategies Design, code, test, debug, and document for projects and programs associated with technology domain, including upgrades and deployments Review moderately complex technical challenges that require an in-depth evaluation of technologies and procedures Resolve moderately complex issues and lead a team to meet existing client needs or potential new clients needs while leveraging solid understanding of the function, policies, procedures, or compliance requirements Collaborate and consult with peers, colleagues, and mid-level managers to resolve technical challenges and achieve goals Lead projects and act as an escalation point, provide guidance and direction to less experienced staff ​ Desired Qualifications:   Proven experience designing and scaling enterprise GenAI platforms and AI-driven products. Strong expertise in Agentic AI, multi-agent systems, RAG architectures, Knowledge Graphs, and long-term memory frameworks. Experience architecting model orchestration solutions, including model routing, selection, fallback, and optimization strategies. Proficiency with GenAI frameworks including LangGraph, LangChain, AutoGen, MCP, or equivalent orchestration technologies. Deep understanding of LLMOps, AI platform engineering, CI/CD automation, and production-grade AI deployments. Hands-on experience with cloud AI platforms such as Azure OpenAI, AWS Bedrock, and Google Vertex AI. Strong proficiency in Python with experience building services using frameworks such as Fast MCP, FastAPI & Flask.  Experience developing and integrating with REST APIs, asynchronous services, and event-driven architectures.  Expertise in vector databases, graph databases, embeddings, semantic search, and retrieval technologies. Strong cloud-native engineering background with Kubernetes, microservices, containers, and distributed systems. Experience establishing AI observability, monitoring, evaluation, resiliency, and reliability practices. Knowledge of AI security, responsible AI, governance, privacy, and regulatory requirements. Understanding of token economics, AI cost optimization, usage forecasting, and platform efficiency strategies. Experience designing reusable APIs, SDKs, and developer frameworks that accelerate enterprise adoption. Experience in working on relation database like Oracle, MS SQL Server, etc. Experience with automated testing with Playwright, performance testing, code reviews, and CI/CD practices.  Experience building secure, scalable, maintainable applications aligned with enterprise platform standards.  Job Expectations: Lead moderately complex initiatives and deliverables within technical domain environments Design, build, and maintain AI-enabled applications using React, TypeScript, Python, and modern API frameworks.  Develop    frontend applications aligned with enterprise UI standards and reusable component patterns.  Build and maintain Python backend services, APIs, MCP services, and integration layers using frameworks such as MCP, FastAPI & Flask.  Design, implement, and integrate with MCP servers and MCP clients that enable secure context sharing between models, tools, applications, and agent runtimes.  Develop and support  agentic workflows  that execute complex, multi-step tasks using frameworks such as LangChain Deep Agents, Google ADK, or similar agent frameworks.  Build skill-based and modular agents that decompose capabilities into reusable, composable, and versioned skills.  Build reusable components, services, tool schemas, and integration patterns that can be shared across enterprise AI applications.  Integrate logging, tracing, and observability frameworks, including Arize & Splunk compatible logging and agent