About this role:
Wells Fargo is seeking a Generative AI Senior Engineer for Guardrails and API Services within Digital Technology – AI Capability Engineering. We are building s enterprise-grade observability, evaluation, command, control, and safeguards layer for generative and agentic AI systems. In this role, you will build, integrate, and operate core these capabilities to ensure AI agents run safely, reliably, and in alignment with enterprise expectations for security, auditability, resiliency, and operational excellence. Your work will span agent tracing, evaluation pipelines, guardrails/intervention services, and the Agent Registry and Control Center experiences.
In this role, you will:
Lead moderately complex Generative AI initiatives and deliverables within technical domain environments
Contribute to large scale planning of strategies
Design, code, test, debug, and document for projects and programs associated with technology domain, including upgrades and deployments
Review moderately complex technical challenges that require an in-depth evaluation of technologies and procedures
Resolve moderately complex issues and lead a team to meet existing client needs or potential new clients needs while leveraging solid understanding of the function, policies, procedures, or compliance requirements
Collaborate and consult with peers, colleagues, and mid-level managers to resolve technical challenges and achieve goals
Lead projects and act as an escalation point, provide guidance and direction to less experienced staff
Required Qualifications:
4+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
Desired Qualifications:
Hands-on experience instrumenting applications/agents using SDK hooks and span models; ensuring end-to-end trace propagation for prompts, context documents, tools, and agent workflows
Experience configuring Arize spaces/projects, dashboards/monitors, and evaluation pipelines (LLM-as-Judge and/or code-based scoring); exports for offline analysis
Experience building and operating event/data flows across services, storage, and metadata stores (e.g., spans → Arize DB/HPOS → Postgres metadata) with strong ingestion/query reliability
Experience designing registry metadata models (YAML schemas, UIDs, versioning, dependency graphs) and building governance views/UIs
Experience implementing behavior guardrails and runtime intervention patterns using Redis/Kafka signals and signal handlers (e.g., kill/clean/HITL)
Proficiency in Python, REST and/or gRPC; event-driven design
Experience operating services on Kubernetes with GitOps/CI/CD, OpenTelemetry, Postgres, Kafka/Redis, and object storage (HPOS)
Experience with identity/entitlements (OAuth scopes, RBAC/ABAC), and sensitive data handling (masking/redaction) for UI/exports
Strong operational rigor: runbooks, incident response, performance regression gating, and clear written communication
Hands on experience of developing UI (html,javascript)
