Lead Software Engineer

Wells Fargo•Irving, TX

3d•Hybrid

About The Position

Wells Fargo is seeking a Lead Software Engineer as part of Cybersecurity. In this role, you will provide technical leadership for the design, development, deployment, and support of cloud-native IAM applications. You will lead architecture and design decisions across frontend, backend, API, event-driven, and data platforms. You will establish technical standards, coding practices, design patterns, and engineering guardrails. You will conduct code reviews and mentor engineers to drive engineering excellence and technical growth. You will serve as a trusted advisor to engineering leadership and stakeholders on technology strategy and modernization initiatives. You will design and develop responsive web applications using React and modern JavaScript frameworks. You will develop scalable backend services using Java, Spring Boot, Python, REST APIs, and microservice architectures. You will design and implement event-driven integrations using Kafka and enterprise messaging patterns. You will build and optimize MongoDB data models, queries, and application persistence layers. You will integrate with enterprise IAM platforms, identity providers, and security services. You will lead Agile teams through sprint planning, backlog refinement, estimation, release planning, and production deployments. You will drive CI/CD automation and DevSecOps practices utilizing GitHub, Jenkins, OpenShift, SonarQube, Fortify, and Black Duck. You will ensure adherence to SDLC, change management, security, resiliency, audit, and compliance requirements. You will partner with product and business teams to translate requirements into technical solutions. You will drive application reliability, observability, monitoring, and production support readiness. You will lead root cause analysis and resolution of complex production issues. You will implement performance optimization, resiliency, disaster recovery, and scalability improvements. You will champion automation across testing, deployment, operational support, and engineering workflows. You will drive adoption of AI-assisted software development practices. You will design and develop AI-enabled user experiences and intelligent workflows. You will evaluate emerging technologies and recommend innovations that improve customer experience, productivity, and engineering efficiency. You will support implementation of MCP-based integrations, intelligent agents, and AI-powered automation capabilities where appropriate.

Requirements

5+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
5+ years leading complex software engineering initiatives or Agile teams.
5+ years of Java and Spring Boot development experience.
5+ years building RESTful APIs and microservices.
3+ years of React development experience.
3+ years of MongoDB or equivalent NoSQL database experience.
Experience implementing event-driven architectures using Kafka or similar messaging platforms.
Experience deploying applications to OpenShift, Kubernetes, or cloud-native platforms.
Experience with GitHub, CI/CD pipelines, DevSecOps, and automated testing frameworks.
Strong understanding of application security, authentication, authorization, and IAM concepts.
Excellent communication, collaboration, and leadership skills.
Demonstrate proficiency in using AI‑assisted development and analysis tools (e.g., GitHub Copilot and approved code‑centric agents)
Leverage AI to accelerate system design, coding, testing, analysis, and troubleshooting
Apply strong technical judgment when validating and integrating AI‑assisted outputs into solutions
Understand and account for model limitations, security risks, and operational considerations
Apply AI responsibly in development and production environments
Ensure AI usage aligns with security, compliance, privacy, and ethical standards

Nice To Haves

Experience building IAM, IGA, access management, certification, entitlement, or compliance solutions.
Experience with AI-enabled applications, generative AI platforms, MCP architectures, and intelligent automation.
Experience with API gateways such as Apigee.
Experience operating applications within highly regulated financial services environments.
Experience leading engineering transformation initiatives and developing T-shaped engineering teams.

Responsibilities

Provide technical leadership for the design, development, deployment, and support of cloud-native IAM applications.
Lead architecture and design decisions across frontend, backend, API, event-driven, and data platforms.
Establish technical standards, coding practices, design patterns, and engineering guardrails.
Conduct code reviews and mentor engineers to drive engineering excellence and technical growth.
Serve as a trusted advisor to engineering leadership and stakeholders on technology strategy and modernization initiatives.
Design and develop responsive web applications using React and modern JavaScript frameworks.
Develop scalable backend services using Java, Spring Boot, Python, REST APIs, and microservice architectures.
Design and implement event-driven integrations using Kafka and enterprise messaging patterns.
Build and optimize MongoDB data models, queries, and application persistence layers.
Integrate with enterprise IAM platforms, identity providers, and security services.
Lead Agile teams through sprint planning, backlog refinement, estimation, release planning, and production deployments.
Drive CI/CD automation and DevSecOps practices utilizing GitHub, Jenkins, OpenShift, SonarQube, Fortify, and Black Duck.
Ensure adherence to SDLC, change management, security, resiliency, audit, and compliance requirements.
Partner with product and business teams to translate requirements into technical solutions.
Drive application reliability, observability, monitoring, and production support readiness.
Lead root cause analysis and resolution of complex production issues.
Implement performance optimization, resiliency, disaster recovery, and scalability improvements.
Champion automation across testing, deployment, operational support, and engineering workflows.
Drive adoption of AI-assisted software development practices.
Design and develop AI-enabled user experiences and intelligent workflows.
Evaluate emerging technologies and recommend innovations that improve customer experience, productivity, and engineering efficiency.
Support implementation of MCP-based integrations, intelligent agents, and AI-powered automation capabilities where appropriate.