DevOps Lead Software Engineer

Wells Fargo•Concord, CA

2d•Hybrid

About The Position

Wells Fargo is looking for a DevOps Lead Software Engineer to support the Digital Technology & Innovation organization. It involves full‑stack software engineering—designing, testing, debugging, and documenting solutions—while also reviewing and evaluating advanced technical architectures that support both tactical and strategic business goals. The ideal candidate brings strong experience in Linux, DevOps, CI/CD pipelines, infrastructure as code (Terraform), containerization (Docker, Kubernetes, OpenShift), cloud platforms (GCP, Azure), AI/ML operations, and cloud‑native toolchains. Additional strengths include hands‑on Generative AI/LLM capabilities, vector databases, observability stacks, and leading technically complex discussions. Strong analytical, problem-solving, and communication skills are essential.

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 of build-deploy automation and configuration experience within the Linux and Unix environment.
5+ years of Gradle or Maven experience.
5+ years of experience troubleshooting environments across the entire architecture (i.e. applications to infrastructure).
5+ years of experience with Linux OS environment.
5+ years of Python experience.
5 + years of experience with server administration and job creation using Jenkins Continuous Integration server, Github Actions.
5+ years of experience with DevOps practices in an enterprise environment including CI/CD pipelines and DevOps-focused collaboration.
3+ years of experience with Terraform including module engineering, state management, and execution in an enterprise environment.
3+ years of proficient to advanced experience with IaC (infrastructure as code) processes and tooling in an enterprise environment.
3+ years of experience with Google Cloud Platform (GCP) including management of GCP resources with Terraform in an enterprise environment.
3+ years of proficient to advanced experience with git/github.
3+ years of experience with docker/container image development.
3+ years experience in Urban Code Deploy (UCD) or Harness CD tools.

Nice To Haves

3+ years of experience in LLM, Generative AI (developing capabilities for dev/ops).
3+ years of experience in Elastic Search, Vector Database, Model Development would be added benefit.
3+ years of experience with Terraform Cloud/Terraform Enterprise in an enterprise environment.
3+ years of experience supporting AIML solutions in an enterprise environment (GCP preferred but Azure also useful).
Associate cloud engineer certification for GCP (or better GCP certification).
Knowledge and understanding of Cloud computing, PaaS design principles and micro services and containers.
Working knowledge/experience with Azure and/or GCP, as well as some experience building complex infrastructure programmatically with IaC tools (Terraform/Ansible etc.).
Working knowledge/experience with on-premises and Public Cloud technologies, such as Cloud Foundry, Kubernetes, Docker.
Experience in leading / facilitating analysis of current systems and problem identification and resolution.
Ability to lead / facilitate technically complex discussions and working sessions.

Responsibilities

Contribute to Generative AI platform development, including delivering AI/ML models to on‑prem and cloud platforms such as GCP Vertex AI and Azure ML.
Participate in daily Agile standups, provides SME guidance to data science teams
Collaborates closely with engineering, platform, and strategy teams to define infrastructure requirements and support cloud migration.
Leads large‑scale, complex technology initiatives and helps establish enterprise-wide engineering standards and best practices
Design, test, debug, and document for projects and programs.
Review and analyze complex, large-scale technology solutions for tactical and strategic business objectives, enterprise technological environment, and technical challenges that require in-depth evaluation of multiple factors, including intangibles or unprecedented technical factors.
Research industry trends, evaluates new technologies, and drives the adoption of automation‑first practices
Participate in developing Generative AI Platform Capabilities.
Act as an expert resource for other technical teams within DTI.