Engineering Manager at SmartAssets leading end - to - end delivery of product features with full - stack capabilities and team management responsibilities.
WF
Hybrid Senior Engineering Manager – Generative AI Platform Capabilities, Core, GPU
Posted last month
About the role
- Senior Engineering Manager leading Generative AI efforts at Wells Fargo. Managing engineering teams to build secure and scalable platform capabilities across hybrid cloud environments.
Responsibilities
- Manage, coach, and develop a team or teams of engineering managers and experienced engineers in Generative AI to build use cases and foundational platform capabilities
- Ensure adherence to the Banking Platform Architecture, and meeting non-functional requirements with each release
- Partner with, engage and influence architects and experienced engineers to incorporate Wells Fargo Technology technical strategies, while understanding next generation Generative AI domain architecture
- Enable Generative AI target architecture, cloud readiness , and data strategy
- Function as the technical representative for the product during cross-team collaborative efforts and planning
- Identify and recommend opportunities for driving escalated resolution of technology roadblocks including code, build and deployment while also managing overall software development cycle and security standards
- Determine appropriate strategy and actions to act as an escalation partner for scrum masters and the teams to meet moderate to high-risk deliverables and help remove impediments, obstacles, and friction while encouraging constant learning, experimentation, and continual improvement
- Build Generative AI 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 moderate complexity, as well as identify, manage and mitigate technology and enterprise risk
- Collaborate with, partner with and influence 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 to ensure commitments are met and align with strategic objectives in technology engineering
- Hire, build and guide a culture of talent development to have the specialized domain experience and skills required to effectively design and deliver innovative solutions for product areas and products to meet business objectives and strategy, as well as conduct performance management for engineers and managers
- Own production readiness & Day‑2 operations for existing GPU environments and new H100/H200 clusters (capacity planning, scheduling, quota isolation, autoscaling, failover, instrumentation, reporting, adoption).
- Build and govern the AI Gateway (API/SDK) for core services (authN/Z, rate limiting, quotas); enforce semantic versioning, deprecation windows, and SLA management.
- Scale observability & evaluations platforms on‑prem and in cloud.
- Lead agentic AI capabilities (Agent/Tool Marketplace, Workflow Designer, Desktop); scale the registry of tools/agents/ref apps, governance metadata (provenance/versioning), and execution flows.
- Enable multi‑cloud/hybrid architecture & region strategy with consistent runtimes, artifacts, and operational tooling.
Requirements
- 6+ years of Specialty Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
- 3+ years of Management experience
- 2+ years of Generative AI Platform Development Experience
- 3+ years of Software Development Management experience
- 5+ years of experience in Python
- 3+ years of experience in AI ML and MLOPs
- 2+ years of Gen AI GPU Platform experience
- 1+ Years of experience in Gateway, vLLM, AI Agents, MCP servers
Benefits
- Health insurance
- 401(k) matching
- Flexible work arrangements
- Professional development opportunities
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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