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Wells Fargo is seeking an Automation Lead Software Engineer specializing in AI and machine learning to lead complex technology initiatives and develop companywide best practices.
Job Responsibility:
Lead complex technology initiatives including those that are companywide with broad impact
Act as a key participant in developing standards and companywide best practices for engineering complex and large scale technology solutions for technology engineering disciplines
Design, code, 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
Make decisions in developing standard and companywide best practices for engineering and technology solutions requiring understanding of industry best practices and new technologies, influencing and leading technology team to meet deliverables and drive new initiatives
Collaborate and consult with key technical experts, senior technology team, and external industry groups to resolve complex technical issues and achieve goals
Lead projects, teams, or serve as a peer mentor
Design end-to-end AI solutions aligned with business goals
Define architecture for machine learning pipelines, model deployment, and data integration
Evaluate and recommend AI platforms, tools, and frameworks
AI/ML Strategy & Delivery: Define and implement GenAI and Agentic AI use cases, including MVP scoping, roadmap planning, and cross-functional execution
Automation Frameworks: Build self-service portals and automation engines for 20+ platform services, integrating caching/computing platforms and observability tools
Platform Integration: Work with tools like Tachyon GenAI Studio, Ansible, Terraform, and CI/CD pipelines to enable scalable and compliant AI development
Requirements:
5+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
3+ years of experience developing customer-facing, production-grade machine learning solutions
3+ years of experience with Python and ML Frameworks
Experience tuning, validating, optimizing, visualizing, and debugging models
3+ years of large data systems and cloud computing
Nice to have:
Experience with cloud platforms (e.g., AWS, Azure, GCP)
Experience with containerization and orchestration (e.g. Docker, Kubernetes, Openshift)
Strong knowledge of RESTful API design
Excellent problem-solving and debugging skills
Strong communication and collaboration skills
Good understanding and hands on experience on UI development framework (React / Angular)
Experience with asynchronous programming (e.g., asyncio)
Experience with message queues (e.g., RabbitMQ, Kafka)
Experience with CI/CD pipelines (e.g., Jenkins, GitLab CI, Git Action)
Experience with GraphQL
Experience using Infrastructure as Code tools (e.g. Ansible, Terraform, CloudFormation)