Live opening · Posted 5 days ago
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About this role:
Wells Fargo is seeking a Specialty Software Engineering Manager.
In this role, you will:
Manage, coach, and develop a team of individual contributor specialty-domain engineer roles with low to moderate complexity and less experienced managers responsible for building high quality capabilities with modern technology
Ensure adherence to the Banking Platform Architecture, and meeting non-functional requirements with each release
Engage with architects and experienced engineers to incorporate Wells Fargo Technology technical strategies, while understanding next generation domain architecture to enable application migration paths to target architecture; for example cloud readiness, application modernization and data strategy
Function as the technical representative for the product during cross-team collaborative efforts and planning
Identify and recommend opportunities for driving resolution of technology roadblocks including code, build and deployment while also managing overall software development cycle and security standards
Act as an escalation partner for scrum masters and the teams to make decisions and help remove impediments, obstacles, and friction while encouraging constant learning, experimentation, and continual improvement culture
Build engineering skills side-by-side in the codebase, conduct peer reviews to evaluate quality and solution alignment to technical direction, and guide design, as needed
Interpret, develop and ensure security, stability, and scalability within functions of technology with low to moderate complexity, as well as identify, manage and mitigate technology and enterprise risk
Collaborate and consult with the Product Managers/Product Owners to drive user satisfaction, influence technology requirements and priorities in the product roadmap, promote innovative and intelligent solutions, generate corporate value and articulate technical strategy while being a solid advocate of agile and DevOps practices
Interact directly with third party vendors and technology service providers
Manage allocation of people and financial resources for technology engineering including career development and performance management for engineers and managers on the team
Hire, mentor and guide talent development of direct reports to build the specialized domain experience and skills required to effectively design and deliver innovative solutions for the most challenging supported product areas/products
Desired Qualifications:
5+ years of software engineering experience with 3+ years of people management experience.
Strong expertise in Python, Django, Object-Oriented Programming, APIs, microservices, and distributed systems.
Deep experience with Google Cloud Platform (GCP) including Dataproc, GKE, Vertex AI, Workbench, BigQuery, Cloud Storage, and cloud-native architectures.
Proven experience in Compute Optimization and FinOps, including workload sizing, capacity planning, resource optimization, utilization management, and cloud cost governance.
Strong Platform Engineering experience building self-service developer platforms, reusable services, CI/CD pipelines, infrastructure automation, and internal developer platforms.
Hands-on expertise with Hadoop, HDFS, PySpark, distributed computing, enterprise data platforms, and large-scale compute ecosystems.
Experience designing, building, and managing Hybrid Compute Platforms spanning OpenShift (OCP), GCP, and on-prem environments, including workload placement and orchestration strategies.
Strong expertise in Kubernetes, OpenShift, containerization, Infrastructure as Code (IaC), cloud infrastructure engineering, and platform operations.
Experience developing and operating enterprise-scale AI/ML platforms supporting model development, validation, governance, and deployment workflows.
Proven experience building GenAI-powered applications, AI agents, agentic workflows, AI copilots, and developer productivity solutions.
Strong understanding of AI Infrastructure, model serving, inference platforms, vector databases, RAG architectures, and scalable AI platform design.
Experience with workload orchestration, compute scheduling, resource management, and automated workload placement across heterogeneous compute environments.
Strong knowledge of NumPy, Pandas, SciPy, machine learning frameworks, and modern AI engineering practices.
Experience driving engineering excellence through architecture reviews, design reviews, code reviews, quality engineering, SDLC governance, and Agile delivery practices.
Experience with cloud modernization, platform transformation, site reliability engineering (SRE), observability, monitoring, and operational excellence frameworks.
Job Expectations:
Experience leading global engineering teams and delivering large-scale platform and infrastructure transformation initiatives.
Good understanding of Model Development Lifecycle (MDLC), Model Validation, Model Governance, Risk Management, and regulatory technology platforms.
Strong stakeholder management, communication, presentation, negotiation, and leadership skills.
Experience with GPU Programming and Acceleration Technologies (CUDA, RAPIDS, NVIDIA ecosystem) for large-scale AI/ML workloads.
Experience with High Performance Computing (HPC), parallel processing, and advanced compute architectures.
Experience driving enterprise-wide adoption
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