DevOps Senior Software Engineer

Wells Fargo & Company•Concord, CA

1d•Onsite

About The Position

About this role: Wells Fargo is looking for a DevOps Senior 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. Learn more about career areas and lines of business at wellsfargojobs.com. Summary: 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. This role leads complex, large‑scale technology initiatives and shapes enterprise-wide engineering standards. It involves designing, developing, and reviewing sophisticated technology solutions while contributing to the buildout of Generative AI platform capabilities. The position is responsible for delivering AI/ML models to both on‑prem and cloud platforms (GCP Vertex AI, Azure ML), participating in daily Agile routines, and providing subject‑matter expertise to data science and engineering teams. You will work closely with platform, strategy, and development teams to define infrastructure needs and enable application migration to cloud environments. The role also requires researching emerging technologies, establishing best practices, and driving automation-focused engineering innovations. As a technical expert within DTI, you help guide teams across the organization. The ideal candidate has strong hands‑on experience in Linux environments, CI/CD automation, DevOps tooling, Terraform/IaC, cloud engineering (GCP preferred), Python development, and containerization. Additional strengths include experience with Generative AI/LLM capabilities, vector databases, AIML operations, cloud certifications, and modern cloud-native technologies such as Kubernetes and Docker. The role demands the ability to lead complex technical discussions, troubleshoot across full-stack architectures, and drive enterprise-scale engineering solutions. Pay Range Reflected is the base pay range offered for this position. Pay may vary depending on factors including but not limited to demonstrated examples of prior performance, skills, experience, or work location. Employees may also be eligible for incentive opportunities.

Requirements

4+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
4+ years of build-deploy automation and configuration experience within the Linux and Unix environment.
4+ years of Gradle or Maven experience.
4+ years of experience troubleshooting environments across the entire architecture (i.e. applications to infrastructure).
4+ years of experience with Linux OS environment.
3+ years of Python experience.
3 + years of experience with server administration and job creation using Jenkins Continuous Integration server, Github Actions.
3+ 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.

Nice To Haves

2+ years of experience in LLM , Generative AI (developing capabilities for dev/ops).
2+ years of experience in Elastic Search, Vector Database, Model Development would be added benefit.
2+ years of experience with Terraform Cloud/Terraform Enterprise in an enterprise environment.
2+ years of experience supporting AIML solutions in an enterprise environment (GCP preferred but Azure also useful).
3+ years of experience with docker/container image development.
Understanding of Urban Code Deploy (UCD) or Harness CD tools.
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.
Researches 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.