Senior Software Engineer - GEN AI /Python / LLM / ML Ops/ RPA

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

Required Qualifications:

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

Desired Qualifications:

• Strong Python programming skills
• Expertise in RPA tools such as UI path
• Expertise in Workflow automation tools such as Power Platform
• Minimum 2 Years of hands-on experience in AI/ML and Gen AI
• Proven experience in LLMs (Gemini, GPT or Llama etc.)
• Extensive experience in Prompt Engineering and model fine tuning
• AI/Gen AI Certifications from premier institution
• Hands on experience in ML ops (MLflow, CICD pipelines)

Job Expectations:

• Design and develop AI driven Automation solutions
• Implement AI automation to enhance process automation
• Develop and maintain automation, BOTS and AI based workflows
• Integrate Ai automation with existing applications, API's and databases
• Design, develop and implement Gen AI applications using LLM's
• Build and optimize prompt engineering workflows
• Fine tune and integrate pre-trained models for specific use cases
• Deploy models in production using robust MLops practices

Posting End Date:
28 Aug 2025
*Job posting may come down early due to volume of applicants.
We Value Equal Opportunity
Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.
Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit's risk appetite and all risk and compliance program requirements.
Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates, including women, persons with disabilities, aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process.
Applicants with Disabilities
To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo .
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Wells Fargo maintains a drug free workplace. Please see our Drug and Alcohol Policy to learn more.
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b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.