Principal Engineer - Machine Learning & Inference...

Wells Fargo
Charlotte, NC, United States
about 2 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
2 years minimum
Compensation
$159,000.0 - $305,000.0
Working hours
Regular working hours
Job source

Tech stack

Java (Programming Language) Artificial Intelligence Amazon Web Services Microsoft Azure Cloud Computing Cyber Security Computer Programming Databases Information Engineering Digital Technology Github Python (Programming Language)
+28 more
Machine Learning NoSQL OpenShift Ansible Tensorflow Azure Machine Learning Shell Script SQL Databases Web Platforms Workflow Management Systems Scripting Google Cloud Cloud Platform System Feature Engineering Pytorch Large Language Models Prompt Engineering Curam Application Development Generative AI Infrastructure as Code (IaC) AI Platforms Playwright Performance Monitor Web Technologies Machine Learning Operations Virtual Agents Terraform Artificial Intelligence Markup Language (AIML)

Job description

Wells Fargo is seeking a Principal Engineer in the Digital Technology and Innovation group which supports evolving digital platforms and enhances integration of the innovation pipeline into our customer-facing capabilities. The Principal Engineer for Tachyon AI Engineering will lead the design, development, and operationalization of enterprise-scale AI/ML solutions across hybrid environments. This role requires deep technical expertise, strategic vision, and leadership to accelerate predictive and generative AI adoption.

The ideal candidate will have experience with AI Compute Environment, Data Engineering, Generative AI, RAG pipelines, and agentic AI systems, and will drive innovation and modernization initiatives, including model migration from on-prem platforms to cloud-native environments

In this role, you will:

Act as an advisor to leadership to develop or influence applications, network, information security, database, operating systems, or web technologies for highly complex business and technical needs across multiple groups

  • Lead the strategy and resolution of highly complex and unique challenges requiring in-depth evaluation across multiple areas or the enterprise, delivering solutions that are long-term, large-scale and require vision, creativity, innovation, advanced analytical and inductive thinking

  • Translate advanced technology experience, an in-depth knowledge of the organizations tactical and strategic business objectives, the enterprise technological environment, the organization structure, and strategic technological opportunities and requirements into technical engineering solutions

  • Provide vision, direction and expertise to leadership on implementing innovative and significant business solutions

  • Maintain knowledge of industry best practices and new technologies and recommends innovations that enhance operations or provide a competitive advantage to the organization

  • Strategically engage with all levels of professionals and managers across the enterprise and serve as an expert advisor to leadership

Key Responsibilities:

Platform Leadership

  • Drive the evolution of the Tachyon Predictive AI Platform on GCP Vertex AI, Azure ML, and On-Prem AIML Platform

  • Architect scalable, secure, and compliant AI/ML infrastructure across hybrid environments

Model Lifecycle Management

  • Oversee end-to-end ML lifecycle: feature engineering, model development, validation, deployment, and monitoring

  • Implement proactive, event-driven model monitoring and drift detection

Migration & Modernization

  • Lead model migration initiatives from legacy and on-prem systems to cloud-native platforms

  • Ensure smooth transitions with minimal downtime and compliance adherence

Innovation & Automation

  • Drive initiatives for Generative AI and agentic AI integration into workflows

  • Automate governance processes and optimize operational SLAs

Cross-Functional Collaboration

  • Partner with data scientists, MLOps engineers, and application teams to deliver AI solutions

  • Act as a trusted advisor to senior leadership on AI strategy and technical decisions

Mentorship & Thought Leadership

  • Provide technical guidance and mentorship to engineering teams.

  • Represent the organization in AI forums and contribute to enterprise AI strategy., Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit’s risk appetite and all risk and compliance program requirements.

Requirements

  • 7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

  • 5+ years of hands-on programming and/or scripting experience in one or more of the following: Python, Java, Shell scripting etc.

  • 5+ years of experience with Infrastructure as code (IaC) implementation using Terraform, Crossplane or any other industry equivalent solutions

  • 5+ years of experience with OpenShift Container Platform and/or Google Cloud Platform, and/or Microsoft Azure hands on experience

  • 5+ years of experience with enterprise-grade automation solutions design and implementation experience using tools such as Ansible, Harness CD, GitHub Actions, Playwright etc.

  • 2+ years of experience with AI, Gen AI, Agentic automation solutions design and development

Desired Qualifications:

  • Excellent communication and stakeholder management skills.

  • Demonstrated ability to lead complex projects with limited supervision and high accountability

  • Experience with Generative AI, RAG pipelines, and agentic AI systems.

  • Exposure to Google Cloud Platform: Vertex AI / Gemini Enterprise Agent Platform, Agentspace, MCP, A2A exposure

  • Cloud certification; AWS, GCP, Azure or Generative AI Leader

  • Deep understanding of LLMs, prompt engineering, vector databases, and orchestration tools

  • Expertise in cloud AI platforms (GCP Vertex AI, Azure ML), On-Prem AIML systems, and MLOps frameworks

  • Strong programming skills (Python, SQL/NoSQL) and experience with ML frameworks (TensorFlow, PyTorch)

  • Proven track record in enterprise-scale AI deployments, model migration projects, and innovation initiatives

  • 2+ years of experience building full stack Agentic AI Automations (from chat experiences to muti-agent systems) using Agentic AI Frameworks like LangGraph, Crew AI, Microsoft AutoGen, LangChain, Chainlit

Job Expectations:

  • This position is not eligible for Visa sponsorship

  • Ability to work on-site at approved location

Benefits & conditions

Wells Fargo provides eligible employees with a comprehensive set of benefits, many of which are listed below. Visit Benefits - Wells Fargo Jobs (https://www.wellsfargojobs.com/en/life-at-wells-fargo/benefits) for an overview of the following benefit plans and programs offered to employees.

  • Health benefits

  • 401(k) Plan

  • Paid time off

About the company

Wells Fargo maintains a drug free workplace. Please see our Drug and Alcohol Policy (https://www.wellsfargojobs.com/en/wells-fargo-drug-and-alcohol-policy) to learn more.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on juju.com

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

2:08 min

Essential engineering roles in the generative AI space

Mary Grygleski Mary Grygleski · LIVE

2:37 min

Comparing traditional SQL tables versus NoSQL non-tabular databases

Stanimira Vlaeva · JS Congress

6:36 min

Funding open source through GitHub Accelerator and Sponsors

Stormy Peters · WWC 2023

2:35 min

Preventing remote code execution in PyTorch models

Balázs Kiss · WWC 2023

2:14 min

Exploring internal AI product initiatives and global engineering roles

Maria Apazoglou · Coffee With Developers

3:16 min

Terminology differences between relational and NoSQL databases

Tim Faulkes · LIVE

Videos

See all

Related articles

See all