Job highlights

- 4+ years specialty software engineering experience with expertise in AI agentic platforms, Retrieval-Augmented Generation (RAG), and Model Context Protocol (MCP)

- Lead complex initiatives, design and develop AI-driven agentic platforms, integrate generative AI/LLM capabilities, ensure platform scalability and compliance, mentor junior engineers, and collaborate with stakeholders

Job Summary

Wells Fargo is seeking a Senior Software Engineer

Responsibilities

- Lead or participate in complex initiatives on selected domains

- Assure quality, security and compliance for supported systems and applications

- Serve as a technical resource in finding software solutions

- Review and evaluate user needs and determine requirements

- Provide technical support, advice, and consultation with the issues relating to supported applications

- Create test data and conduct interfaces and unit tests

- Design, code, test, debug and document programs using Agile development practices

- Understand and participate to ensure compliance and risk management requirements for supported area are met and work with other stakeholders to implement key risk initiatives

- Conduct research and resolve problems in relation to processes and recommend solutions and process improvements

- Assist other individuals in advanced software development

- Collaborate and consult with peers, colleagues and managers to resolve issues and achieve goals

Required Qualifications

- 4+ years of Specialty Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

Desired Qualifications

- Architect and build a Valence (CIBX) agentic platform that allows business users to configure, deploy, and manage AI agents without deep technical expertise.





- Design and develop deep agents capable of multi-step planning, tool use, memory, and autonomous task execution (e.g., using frameworks like LangGraph, DeepAgents SDK, or similar).

- Build and optimize Retrieval-Augmented Generation (RAG) pipelines for grounding agent responses in enterprise knowledge bases and documents.

- Integrate Generative AI / LLM capabilities (via internal or third-party model gateways) into scalable backend services.

- Design orchestration layers for routing, planning, task execution, and result aggregation across multiple specialized agents.

- Enable business teams to build agents for automation, analytics, insights, and predictive use cases with reusable templates and configuration-driven workflows.

- Define and implement MCP (Model Context Protocol) or similar tool-calling protocols to connect agents with enterprise systems and APIs.

- Ensure platform scalability, reliability, and observability (logging, monitoring, tracing) for production-grade agentic workloads.

- Collaborate with product, architecture, and business stakeholders to translate BAU pain points into agent-driven automation solutions.

- Mentor junior engineers and drive best practices in agentic system design, prompt engineering, and AI safety/guardrails.

- Contribute to CI/CD pipelines, containerization, and deployment strategy for the platform.

Valuable to Have

- Experience with OpenShift/Kubernetes for container orchestration and platform deployment.

- Familiarity with MongoDB or other NoSQL databases for state/checkpoint management.

- Exposure to enterprise authentication/authorization patterns (AD/SSO, RBAC).

- Experience with CI/CD tooling (GitHub Actions, Jenkins) and code quality tools (SonarQube).

- Prior experience in financial services / capital markets domain.

- Familiarity with MCP (Model Context Protocol) or similar

📌 Senior Specialty Software Engineer - Gen AI (Hyderabad)
🏢 Wells Fargo
📍 Hyderabad