Principal Engineer- High-Performance Computing
Wells Fargo is hiring a Principal Engineer- High-Performance Computing in Bengaluru, India. Level rates it ; you can apply on Level.
AI in this role
Architect and build large-scale distributed computing and GPU-accelerated platforms supporting model training and risk analytics workloads.
About this role:
Wells Fargo is seeking a Principal Engineer
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
Required Qualifications:
- 7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education experience, training, military experience, education
Desired Qualifications:
- 7+ years building distributed systems and platforms.
- Deep expertise in distributed computing (Kubernetes, Spark, Ray, Dask, distributed schedulers, HPC, large-scale data platforms).
- Strong CUDA/GPU programming experience, including performance tuning and GPU orchestration.
- Experience with cloud-native platforms (Azure preferred), containers, orchestration, and infrastructure automation.
- Demonstrated principal-level influence with the ability to define technology strategy and drive adoption across multiple engineering organizations.
Job Expectations:
- Architect and build large-scale distributed computing platforms that power model development, training, execution, and risk analytics workloads across cloud and hybrid environments, delivering high performance, resiliency, scalability, and operational excellence.
- Lead GPU-accelerated computing strategy by designing and optimizing CUDA-based workloads, distributed GPU scheduling, high-performance data processing, and model execution frameworks to maximize utilization and reduce compute costs.
- Drive technical direction for PyFARM and related model platforms, establishing architecture standards, platform patterns, observability, reliability engineering practices, and long-term roadmaps for model risk and quantitative analytics ecosystems.
- Partner with quantitative researchers, model developers, data scientists, and platform engineering teams to enable secure, governed, and efficient execution of large-scale machine learning, simulation, and analytical workloads while ensuring regulatory and risk-management requirements are met.
- Serve as a technical leader and multiplier across the organization, mentoring senior engineers, leading critical design reviews, influencing enterprise architecture decisions, and driving innovation in distributed systems, high-performance computing, AI infrastructure, and data-intensive platforms.
Posting End Date:
29 Oct 2026*Job posting may come down early due to volume of applicants.
We Value Equal Opportunity
Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.
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.
Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates, including women, persons with disabilities, aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process.
Applicants with Disabilities
To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo.
Drug and Alcohol Policy
Wells Fargo maintains a drug free workplace. Please see our Drug and Alcohol Policy to learn more.
Wells Fargo Recruitment and Hiring Requirements:
a. Third-Party recordings are prohibited unless authorized by Wells Fargo.
b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.
How we rate this
Principal Engineer- High-Performance Computing at Wells Fargo rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where distributed computing was part of your work. What did you do?
- Tell me about a project where hpc was part of your work. What did you do?
- Tell me about a project where gpu programming was part of your work. What did you do?
- Tell me about a project where cloud native was part of your work. What did you do?
- Tell me about a project where infrastructure automation was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Distributed Computing, Hpc, GPU Programming, Cloud Native, and Infrastructure Automation. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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