Senior Software Engineer (Python)

Wells Fargo & Company•Minneapolis, MN

23h•$100,000 - $179,000•Hybrid

About The Position

Wells Fargo is seeking a Senior Software Engineer (Python) within the Secured Network Services organization. The role focuses on designing and delivering automation solutions that support a software-driven infrastructure environment. The position calls for Python development, automation, API integration, and cloud-native engineering experience to build scalable, reliable, and secure solutions. The engineer will design API-driven integrations between network platforms and internal systems; develop and maintain Python automation frameworks; and turn manual operational processes into automated, repeatable workflows. Solutions should meet performance, security, reliability, and maintainability standards. The role partners with network engineering, platform, and technology teams, and supports automation initiatives for product deployments, service delivery, customer journeys, and API development. The engineer will use approved AI-assisted development tools, including GitHub Copilot and code-focused AI agents, to support design, development, testing, analysis, and troubleshooting. They are expected to exercise sound technical judgment when reviewing and integrating AI-assisted outputs into production solutions. The position offers a hybrid work schedule and is not eligible for visa sponsorship.

Requirements

At least 4 years of software engineering experience, or equivalent demonstrated through work experience, training, military experience, education, or a combination of these.
At least 3 years of Python development experience, including building automation tools, system integrations, APIs, or workflow orchestration solutions.
Experience designing, developing, testing, and supporting software solutions in an enterprise environment.
Experience developing and consuming REST APIs, including authentication, schema validation, error handling, and versioning.
Experience using source control and modern software development practices, preferably GitHub.

Nice To Haves

Experience with network engineering concepts and network infrastructure automation.
Experience with Nautobot for network source-of-truth, automation, or infrastructure management.
Experience developing API-driven integrations between network platforms and enterprise systems.
Experience with FastAPI, Django, GraphQL, PostgreSQL, NoSQL databases, React, and OAuth.
Experience with Model Context Protocol (MCP) and integrating applications with enterprise AI models or model APIs.
Experience working with OpenAI API specifications or similar API-based AI integrations.
Experience developing microservices, RESTful APIs, and event-driven architectures.
Experience with container and cloud-native platforms such as Red Hat OpenShift, Cloud Foundry, and Kubernetes.
Working knowledge of Unix/Linux, MongoDB, and Postman.
Experience working with legacy infrastructure as well as modern cloud and container-based infrastructure.
Experience in large-scale enterprise environments with structured change management, security, risk, and release processes.
Experience using GitHub Copilot or other approved AI-assisted development tools for software design, coding, testing, troubleshooting, and analysis.
Ability to evaluate AI-generated code or recommendations for accuracy, maintainability, security, and operational risk.

Responsibilities

Design and develop API-driven integrations between network platforms and internal systems.
Develop and maintain Python-based automation frameworks to improve reliability, scalability, and operational efficiency.
Transform manual operational processes into automated, repeatable, and maintainable workflows.
Design automation solutions that meet performance, security, reliability, and maintainability standards.
Partner with network engineering, platform, and technology teams to align automation solutions with broader architecture and infrastructure strategies.
Support and execute automation initiatives for product deployments, service delivery, customer journeys, and API development.
Use approved AI-assisted development tools, including GitHub Copilot and code-focused AI agents, in software engineering activities.
Leverage AI capabilities to accelerate solution design, development, testing, analysis, and troubleshooting.
Review, validate, and integrate AI-assisted outputs into production solutions using sound technical judgment.