Senior Software Engineer - RPA UI Path & Gen AI

📍 Job Overview

Job Title: Senior Software Engineer - RPA UI Path & Gen AI

Company: Wells Fargo

Location: Hyderabad, Telangana, India

Job Type: Full time

Category: Software Engineering / Intelligent Automation

Date Posted: September 01, 2026

Experience Level: Mid-Level (4+ years)

Remote Status: On-site

🚀 Role Summary

• Design, develop, and deploy end-to-end intelligent automation solutions leveraging RPA, workflow platforms, Generative AI, and Agentic AI technologies.

• Lead moderately complex technical initiatives and deliverables within a specialized technology domain.

• Drive large-scale planning of automation strategies and contribute to architectural decisions.

• Collaborate with peers, colleagues, and mid-level managers to resolve intricate technical challenges and achieve project goals.

• Act as a technical escalation point, providing guidance and mentorship to less experienced software engineers.

📝 Enhancement Note: This role is positioned as a Senior Software Engineer, indicating a need for seasoned professionals with a strong technical foundation and the ability to lead and mentor. The emphasis on RPA, GenAI, and Agentic AI signifies a strategic focus on advanced automation within Wells Fargo's technology landscape.

📈 Primary Responsibilities

• Design, code, test, debug, and document robust intelligent automation solutions, ensuring seamless integration of RPA, Generative AI, and Agentic AI components.

• Architect and implement cloud-agnostic automation solutions across environments such as Google Cloud, Microsoft Azure, and AWS.

• Develop and integrate AI-driven solutions using Python or equivalent object-oriented/functional languages, adhering to SOLID principles and appropriate design patterns.

• Implement Generative AI concepts, including prompt engineering, Retrieval Augmented Generation (RAG) patterns, and seamless LLM integration with platforms like Google Vertex AI, Azure OpenAI, or AWS Bedrock.

• Develop Agentic AI solutions using frameworks such as LangChain, LangGraph, Google ADK, or Semantic Kernel, focusing on AI agent orchestration, memory, and reasoning patterns.

• Integrate automation solutions with enterprise systems using REST APIs, databases, message queues, and other relevant technologies.

• Contribute to the end-to-end automation lifecycle, encompassing design, development, testing, deployment, and ongoing maintenance and support.

• Ensure adherence to strong software engineering fundamentals, including AI/LLMOps, version control (e.g., Git), CI/CD pipelines, and secure coding practices.

• Design scalable, maintainable, and resilient enterprise-grade automation solutions.

• Mentor and guide junior engineers, serving as a subject matter expert and technical lead for automation projects.

📝 Enhancement Note: The responsibilities highlight a blend of core software engineering practices with specialized skills in advanced automation technologies. A strong emphasis is placed on the full lifecycle of automation development and deployment, requiring a proactive and solution-oriented approach.

🎓 Skills & Qualifications

Education: While no specific degree is mandated, a strong academic background in Computer Science, Engineering, or a related technical field is highly beneficial. Equivalent practical experience will also be considered.

Experience: Minimum of 4 years of hands-on experience in enterprise software engineering or a closely related technical role.

Required Skills:

• 4+ years of demonstrable experience in enterprise software engineering.

• Strong hands-on experience with Intelligent Automation and Robotic Process Automation (RPA) tools, with a preference for UiPath.

• Proficiency in developing and integrating AI-driven solutions using Python or equivalent programming languages.

• Deep understanding of Generative AI concepts, including prompt engineering, RAG patterns, and LLM integration.

• Experience working with LLM platforms such as Google Vertex AI, Azure OpenAI, or AWS Bedrock.

• Experience in Agentic AI development using frameworks like LangChain, LangGraph, Google ADK, or Semantic Kernel.

• Expertise in integrating solutions using REST APIs, databases, message queues, and enterprise systems.

• Solid understanding of software engineering fundamentals, including version control (Git), CI/CD, and secure coding practices.

• Ability to design scalable, maintainable, and resilient enterprise-grade solutions. Preferred Skills:

• Hands-on expertise in low-code/no-code solutions using Microsoft Power Platform, including Power Apps, Power Automate, and Power BI dashboard design.

• Experience with vector databases such as Azure AI Search, Pinecone, or FAISS.

• Familiarity with containerization technologies like Kubernetes, Docker, and Helm.

• Experience with AI/LLMOps practices for managing and deploying AI models.

• Experience in AI agent orchestration, including building multi-agent systems, memory, and reasoning patterns.

• Preferred Certifications: RPA (UiPath), low-code/no-code (Power Automate, Microsoft Power Platform), GenAI or LLM certifications, Cloud AI certifications (Google, Microsoft, AWS), or equivalent industry-recognized credentials.

📝 Enhancement Note: The desired qualifications are extensive, indicating a highly specialized role. Candidates should be prepared to demonstrate deep technical expertise across multiple cutting-edge automation and AI technologies.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Demonstrable examples of end-to-end intelligent automation solutions developed, showcasing integration of RPA, workflow, and AI components.

• Case studies detailing process optimization initiatives, highlighting quantifiable improvements in efficiency, accuracy, and cost savings.

• Evidence of system implementation and integration projects, particularly those involving complex enterprise architectures and API integrations.

• Projects that clearly articulate the Return on Investment (ROI) achieved through automation and AI solutions. Process Documentation:

• Documentation of workflow design and optimization phases for automation projects, including process mapping and re-engineering.

• Records of implementation and automation methods used, including coding standards, testing procedures, and deployment strategies.

• Analysis of performance metrics and measurement of key performance indicators (KPIs) for automated processes, demonstrating continuous improvement.

📝 Enhancement Note: A strong portfolio is crucial for this role. Candidates should curate examples that specifically highlight their experience with RPA, Generative AI, Agentic AI, and their ability to deliver measurable business outcomes through these technologies.

💵 Compensation & Benefits

Salary Range: Based on industry benchmarks for Senior Software Engineers with specialized skills in RPA and Generative AI in Hyderabad, India, a competitive salary range is estimated to be between ₹18,00,000 to ₹30,00,000 per annum. This range accounts for the required experience, technical expertise, and the strategic importance of the role within Wells Fargo.

Benefits:

• Comprehensive health insurance (medical, dental, vision) for employees and dependents.

• Retirement savings plan with company matching contributions.

• Generous paid time off (PTO), including vacation, sick leave, and public holidays.

• Employee assistance programs for mental health and well-being support.

• Opportunities for professional development, training, and certifications.

• Access to Wells Fargo's internal learning platforms and resources.

• Potential for performance-based bonuses and stock options.

• Relocation assistance may be available for eligible candidates.

Working Hours: Standard working hours are typically 40 hours per week, Monday through Friday. Some flexibility may be expected to accommodate project deadlines, cross-time zone collaboration, or urgent technical issues, particularly given the global nature of enterprise technology.

📝 Enhancement Note: Salary estimates are based on market research for similar Senior Software Engineer roles in Hyderabad, India, considering the specialized skills in RPA and Generative AI. Wells Fargo is a major financial institution, so benefits packages are expected to be comprehensive.

🎯 Team & Company Context

🏢 Company Culture

Industry: Financial Services. Wells Fargo operates as a diversified financial services company, providing a wide range of banking, lending, mortgage, and investment products and services. This industry context demands a strong emphasis on security, compliance, and risk management in all technology implementations.

Company Size: Wells Fargo is a large, global financial institution with tens of thousands of employees worldwide. This scale implies a structured environment with established processes, robust infrastructure, and significant opportunities for career growth and impact.

Founded: Wells Fargo was founded in 1852. Its long history in the financial sector underscores its stability and deep expertise, while its ongoing investment in technology signifies a commitment to innovation and modernization.

Team Structure:

• The Intelligent Automation team is likely a specialized unit within Wells Fargo's broader technology organization, focusing on the strategic implementation of advanced automation.

• This team will likely comprise engineers with expertise in RPA, AI/ML, software development, and potentially business analysis.

• The reporting structure will likely involve a technical lead or manager overseeing a team of engineers, with potential reporting lines to directors or VPs within the technology division.

• Cross-functional collaboration is expected with business units, IT infrastructure teams, security, and compliance departments to ensure seamless integration and adherence to regulatory requirements. Methodology:

• Data analysis and insights are critical for identifying automation opportunities and measuring the impact of deployed solutions.

• Workflow planning and optimization strategies will be essential for designing efficient and scalable automation processes.

• Automation and efficiency practices are at the core of this role, with a focus on leveraging RPA, GenAI, and Agentic AI to streamline operations.

Company Website: https://www.wellsfargo.com/

📝 Enhancement Note: Working within a large financial institution like Wells Fargo means operating within a highly regulated environment. Candidates should be aware of the stringent security, compliance, and risk management protocols that are integral to the company's culture and operations.

📈 Career & Growth Analysis

Operations Career Level: This role is positioned as a "Senior Software Engineer," indicating a mid-to-senior level of expertise. It requires not only strong technical proficiency but also the ability to lead initiatives, mentor junior team members, and contribute to strategic planning. The focus on advanced technologies like GenAI and Agentic AI suggests this is a forward-looking role with significant potential for impact.

Reporting Structure: The Senior Software Engineer will likely report to an Engineering Manager or Lead within the Intelligent Automation or a related technology division. They will collaborate closely with product owners, business stakeholders, and other engineering teams across the organization.

Operations Impact: This role has a direct impact on operational efficiency and effectiveness across Wells Fargo. By designing and deploying intelligent automation solutions, the engineer will help streamline complex processes, reduce manual effort, improve accuracy, enhance customer experience, and potentially drive significant cost savings. The integration of GenAI and Agentic AI points towards transforming how work is done, moving beyond simple task automation to more sophisticated problem-solving and decision support.

Growth Opportunities:

• Specialization: Deepen expertise in specific AI domains like LLM orchestration, multi-agent systems, or advanced RPA capabilities.

• Leadership: Progress into roles such as Lead Software Engineer, Engineering Manager, or Architect, managing teams and driving technical strategy.

• Cross-Functional Moves: Transition into roles focused on AI product management, technical program management, or solutions architecture within different business units.

• Industry Certifications: Pursue advanced certifications in cloud AI, RPA, or specific LLM platforms to enhance credentials and marketability.

• Mentorship & Training: Develop strong leadership and mentoring skills by guiding junior engineers and contributing to internal training programs.

📝 Enhancement Note: The "Senior" title suggests that candidates are expected to operate with a degree of autonomy and provide technical leadership. The growth opportunities are substantial, offering paths for both deep technical specialization and broader leadership responsibilities within a large enterprise.

🌐 Work Environment

Office Type: On-site. This role is based in Wells Fargo's Hyderabad office, indicating a traditional in-office work environment. This setting typically fosters strong team collaboration, direct mentorship, and easier access to on-site resources and support.

Office Location(s): The role is located at the "111443-IND-HYDERABAD-INTL HYD WF CENTRE BLK B8 Twr-4" in Hyderabad, India. This suggests a modern corporate office environment designed to support a large workforce.

Workspace Context:

• The workspace is likely to be a collaborative office environment, designed to facilitate team interaction and knowledge sharing among engineers.

• Access to high-performance computing resources, development tools, and secure network infrastructure will be standard.

• Opportunities for direct interaction with team members, managers, and potentially business stakeholders will be frequent, aiding in rapid problem-solving and alignment.

• The environment will adhere to stringent financial industry standards for data security and operational integrity.

Work Schedule: The standard work schedule is 40 hours per week, typically Monday to Friday. While the role is on-site, Wells Fargo may offer some flexibility in terms of start and end times, provided business needs and project deliverables are met. Given the nature of software engineering and potential global collaborations, occasional work outside standard hours might be necessary.

📝 Enhancement Note: The on-site requirement means candidates should be prepared for a fully office-based role. This environment is conducive to structured collaboration and adherence to enterprise-level security protocols, which are paramount in the financial sector.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A recruiter or HR representative will likely conduct an initial screening to assess basic qualifications, experience, and cultural fit.

• Technical Phone Screen: Candidates can expect a technical interview with an engineer or hiring manager to delve into core software engineering principles, RPA, and AI/GenAI concepts. This may involve coding challenges or system design questions.

• On-site/Virtual Interviews: This stage typically involves multiple rounds with different team members, including senior engineers, architects, and potentially the hiring manager. Expect in-depth discussions on technical expertise, problem-solving abilities, and experience with specific tools and frameworks.

• Portfolio Review: Candidates will be asked to present and discuss their portfolio, detailing specific projects, their role, the challenges faced, the solutions implemented, and the measurable outcomes. This is a critical component for assessing practical application of skills.

• Behavioral & Situational Questions: Questions will assess problem-solving approaches, teamwork, leadership potential, and how candidates handle complex situations or conflicts.

• Final Interview: A final interview with a senior leader or director to confirm fit and discuss overall contributions to the team and organization.

Portfolio Review Tips:

• Curate Select Projects: Choose 3-4 of your most impactful projects that directly align with the job description's requirements (RPA, GenAI,

Python, API integration, etc.).

• Structure Your Narrative: For each project, clearly articulate:

  • The business problem or opportunity.
  • Your specific role and contributions.
  • The technologies and methodologies used.
  • The technical challenges encountered and how you overcame them.
  • The quantifiable results and business impact (e.g., efficiency gains, cost savings, error reduction).

• Demonstrate Technical Depth: Be prepared to discuss the architectural decisions, coding patterns, and trade-offs made during development.

• Highlight AI/RPA Specifics: Emphasize your experience with prompt engineering, RAG, LLM integration, agentic frameworks, or specific RPA tool capabilities.

• Showcase Problem-Solving: Present how you tackled complex integrations or devised innovative solutions.

• Prepare for Q&A: Anticipate questions about your design choices, scalability considerations, and future enhancements.

Challenge Preparation:

• Coding Challenges: Practice coding problems, especially those involving Python, data structures, algorithms, and API interactions. Familiarize yourself with platforms like LeetCode or HackerRank.

• System Design: Prepare for system design questions focusing on building scalable, resilient, and secure automation solutions. Consider how to integrate various components (RPA, LLMs, databases, APIs).

• RPA/AI Scenario-Based Questions: Think through how you would approach common automation challenges or design AI-driven workflows for specific business problems within a financial services context.

📝 Enhancement Note: The interview process is expected to be rigorous, focusing heavily on practical application of skills through portfolio review and technical challenges. Candidates should prepare thoroughly to showcase their expertise in advanced automation technologies.

🛠 Tools & Technology Stack

Primary Tools:

• RPA Platforms: UiPath (primary focus), potentially others like Blue Prism or Automation Anywhere.

• Low-Code/No-Code Platforms: Microsoft Power Platform (Power Apps, Power Automate).

• Programming Languages: Python (essential for AI/LLM integration), potentially Java or C#.

• AI/LLM Platforms: Google Vertex AI, Azure OpenAI, AWS Bedrock, or similar.

• Agentic AI Frameworks: LangChain, LangGraph, Google ADK, Semantic Kernel.

• Version Control: Git (e.g., GitHub, GitLab, Azure Repos).

• CI/CD Tools: Jenkins, Azure DevOps, GitLab CI, or similar for automated builds and deployments.

Analytics & Reporting:

• Data Visualization: Power BI (specifically mentioned), Tableau, or similar tools for dashboard creation and reporting.

• Databases: SQL databases (e.g., SQL Server, Oracle), NoSQL databases.

• Vector Databases (Good to have): Azure AI Search, Pinecone, FAISS.

CRM & Automation:

• API Integration: Deep understanding of RESTful APIs for system integration.

• Message Queues: Kafka, RabbitMQ, or similar for asynchronous communication.

• Containerization (Good to have): Kubernetes, Docker, Helm for deployment and orchestration.

• Cloud Platforms: Experience with at least one major cloud provider (AWS, Azure, GCP).

📝 Enhancement Note: The technology stack is a blend of established RPA tools and cutting-edge AI technologies. Proficiency in Python and familiarity with cloud environments and containerization are critical for success in this role.

👥 Team Culture & Values

Operations Values:

• Innovation & Efficiency: A drive to leverage new technologies like GenAI and Agentic AI to continuously improve operational efficiency and deliver innovative solutions.

• Data-Driven Decision Making: Reliance on data and metrics to identify automation opportunities, measure success, and guide strategic decisions.

• Collaboration & Teamwork: Emphasis on working effectively with cross-functional teams, sharing knowledge, and supporting colleagues to achieve common goals.

• Customer Focus: Commitment to enhancing customer experience and delivering value through automated processes and intelligent solutions.

• Risk & Compliance: A strong adherence to security, regulatory compliance, and risk management protocols, which are paramount in the financial services industry.

Collaboration Style:

• Cross-Functional Integration: Proactive engagement with business units, IT infrastructure, security, and compliance teams to ensure automation solutions are well-integrated, secure, and compliant.

• Process Review Culture: Openness to feedback on automation designs and implemented processes, with a commitment to continuous improvement through iterative development.

• Knowledge Sharing: Active participation in team discussions, code reviews, and knowledge-sharing sessions to disseminate best practices and foster collective learning.

• Agile Methodologies: Likely adoption of Agile or hybrid methodologies to enable iterative development, rapid feedback, and flexibility in responding to evolving business needs.

📝 Enhancement Note: Wells Fargo, as a financial institution, will place a high value on integrity, security, and compliance. The team culture will likely reflect these values, combined with a forward-thinking approach to adopting new automation and AI technologies.

⚡ Challenges & Growth Opportunities

Challenges:

• Integrating Diverse Technologies: Effectively combining RPA, workflow platforms, LLMs, and Agentic AI into cohesive, stable, and scalable solutions presents a significant technical challenge.

• Data Security & Compliance: Ensuring that all automation solutions meet stringent financial industry security standards and regulatory compliance requirements is paramount.

• Scalability & Maintainability: Designing solutions that can scale efficiently across the enterprise and are maintainable over the long term requires robust engineering practices.

• Rapid Evolution of AI: Keeping pace with the fast-changing landscape of Generative AI and Agentic AI tools and techniques requires continuous learning and adaptation.

• Change Management: Driving adoption of new automation technologies and processes within a large, established organization can be challenging.

Learning & Development Opportunities:

• Advanced AI/ML Training: Opportunities to pursue specialized training and certifications in areas like LLM fine-tuning, AI ethics, advanced prompt engineering, or specific cloud AI services.

• RPA & Automation Specialization: Deepening expertise in advanced features of UiPath or other RPA platforms, as well as exploring other automation paradigms.

• Cloud Architecture & DevOps: Enhancing skills in cloud-native development, containerization (Kubernetes, Docker), and advanced CI/CD practices (AI/LLMOps).

• Leadership Development: Participating in leadership training programs to hone skills in team management, project leadership, and strategic influence.

• Industry Conferences & Forums: Attending industry events to stay abreast of the latest trends, network with peers, and gain insights into emerging technologies and best practices.

📝 Enhancement Note: This role sits at the forefront of technological innovation within a traditional industry. The challenges are significant but offer immense opportunities for professional growth and the chance to shape the future of automation at Wells Fargo.

💡 Interview Preparation

Strategy Questions:

• Operations Strategy: "Describe how you would approach designing an end-to-end intelligent automation solution for a complex financial process, considering RPA, GenAI, and Agentic AI. What are the key considerations for scalability and security?" (Prepare to discuss your thought process, component selection, and risk mitigation.)

• Collaboration & Stakeholder Management: "How would you collaborate with business stakeholders to gather requirements for an automation project, and how would you manage their expectations regarding the capabilities and limitations of GenAI?" (Focus on communication strategies, requirement elicitation techniques, and expectation setting.)

• Problem-Solving: "Imagine a scenario where an AI agent you developed is providing inconsistent or inaccurate responses. How would you diagnose the root cause and what steps would you take to resolve it?" (Prepare to detail your debugging methodology, potential causes, and corrective actions.)

Company & Culture Questions:

• "What interests you about working at Wells Fargo, specifically within the Intelligent Automation space, given its position in the financial services industry?" (Research Wells Fargo's innovation initiatives, values, and commitment to technology.)

• "How do you see your skills in RPA and GenAI contributing to the specific challenges and opportunities within a large financial institution like Wells Fargo?" (Connect your expertise to the company's goals and industry context.)

• "Describe a time you had to advocate for a new technology or approach within a team. How did you gain buy-in and manage resistance?" (Prepare to showcase your influence and persuasive skills.) Portfolio Presentation Strategy:

• Start with Impact: Begin by clearly stating the business problem and the quantifiable impact of your solution.

• Show, Don't Just Tell: Use diagrams, screenshots, or short demos (if appropriate and permitted) to illustrate your work.

• Explain Your Role: Clearly define your contributions, especially in team projects.

• Technical Deep Dive: Be ready to explain architectural choices, code snippets (if relevant), and integration patterns.

• Focus on AI/RPA Nuances: Highlight your specific expertise in prompt engineering, RAG, LLM integration, or agentic AI framework usage.

• Quantify Results: Emphasize metrics like ROI, time saved, error reduction, or efficiency gains.

• Anticipate Questions: Prepare for questions about scalability, security, error handling, and future enhancements.

📝 Enhancement Note: Interviews for senior roles at large financial institutions are thorough. Be ready to demonstrate not only technical prowess but also strategic thinking, problem-solving acumen, and an understanding of the enterprise context.

📌 Application Steps

To apply for this Senior Software Engineer position:

• Submit your application through the official Wells Fargo careers portal via the provided URL.

• Portfolio Customization: Tailor your resume and cover letter to highlight your most relevant experience with RPA (UiPath), Generative AI, Agentic AI, Python, API integrations, and cloud platforms. Quantify achievements with specific metrics.

• Resume Optimization: Ensure your resume clearly articulates your 4+ years of software engineering experience and showcases your expertise in the desired technologies and methodologies mentioned in the job description. Use keywords strategically.

• Interview Preparation: Practice articulating your experience with specific project examples from your portfolio. Be prepared to discuss technical challenges, solutions, and outcomes in detail, especially concerning RPA and GenAI.

• Company Research: Gain a deep understanding of Wells Fargo's business, its commitment to technology and innovation, and its role in the financial services industry. Familiarize yourself with their values and any public information regarding their AI and automation strategies.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.