GenAI Observability & Governance Engineer (On‑Prem OpenShift)

Bank of America

Charlotte (NC)

On-site

USD 103,000 - 180,000

Full time

9 days ago
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Job summary

Bank of America is seeking an experienced software engineer to lead GenAI operations within an on-prem OpenShift environment in Jersey City, NJ. You will guardrails, monitor observability, and integrate AI governance tools across enterprise applications.

The role requires a strong background in Python, containerized workloads, and building production-grade AI workflows, with collaboration across teams and leadership responsibilities.

Qualifications

  • Degree in CS/Data Science/MIS or equivalent experience.
  • 10+ years of software engineering in production applications.
  • Strong Python development experience with ML libraries.
  • Experience deploying containerized workloads on OpenShift/Kubernetes.
  • Experience bringing LLM/RAG-based apps to production.
  • Knowledge of AI risks, governance, and guardrails.

Responsibilities

  • Develop, deploy, and support vendor apps in an on-prem OpenShift environment.
  • Build APIs and integrations connecting guardrails and observability tools.
  • Implement and maintain monitoring for performance, safety, latency.
  • Develop and calibrate model-based evaluation workflows.
  • Utilize LangChain for guardrails, prompts, and scoring workflows.
  • Create observability dashboards and alerting capabilities.
  • Troubleshoot production issues and improve scalability and reliability.
  • Lead and mentor team members; drive engineering standards.

Skills

Python development
Leadership
Agile
DevOps

Education

Bachelor's or Master’s in CS/Data Science/MIS

Tools

OpenShift
Kubernetes
LangChain
LangSmith
Galileo
Splunk
OpenAI APIs

Job description

Bank of America is seeking an experienced software engineer to lead GenAI operations within an on-prem OpenShift environment in Jersey City, NJ. You will guardrails, monitor observability, and integrate AI governance tools across enterprise applications.

The role requires a strong background in Python, containerized workloads, and building production-grade AI workflows, with collaboration across teams and leadership responsibilities.

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