IBM watsonx Governance Engineer II REMOTE

DMS Vision•Frisco, TX

9h•Remote

About The Position

Experis AI CoE is seeking an experienced IBM watsonx Governance Engineer to help enterprise clients operationalize trustworthy AI. The role focuses on designing and implementing AI governance frameworks, model risk management systems, and responsible AI monitoring solutions using IBM watsonx.governance (formerly OpenScale / Watson OpenPages). The engineer will help ensure models are explainable, fair, compliant, and auditable throughout the AI lifecycle. The position also supports pre-sales activities and client engagements, including demos, proofs of concept, and technical workshops. The engineer will collaborate with data science, MLOps, business, and compliance stakeholders and contribute governance documentation, playbooks, and client-facing accelerators.

Requirements

At least 3 years of experience in data engineering, MLOps, AI/ML platform engineering, or data governance.
Hands-on experience with IBM watsonx.governance, IBM OpenScale, or equivalent governance tools such as Fiddler, Arthur AI, or Aporia.
Working knowledge of model fairness concepts, including disparate impact, equalized odds, and demographic parity.
Experience with Python, SQL, and machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch.
Familiarity with AI/ML lifecycle tools such as MLflow, Kubeflow, SageMaker, Azure ML, or Vertex AI.
Strong understanding of enterprise data platforms and cloud environments, including IBM Cloud, AWS, Azure, or GCP.
Excellent written and verbal communication skills for cross-functional stakeholder engagement.

Nice To Haves

IBM watsonx certifications, such as watsonx.governance or watsonx.ai, or IBM AI Ethics / Responsible AI credentials.
Knowledge of regulatory frameworks such as the EU AI Act, GDPR, CCPA, NIST AI RMF, or FINRA/OCC model risk guidance.
Experience integrating IBM OpenPages for GRC with AI workflows.
Background with enterprise data governance platforms such as Collibra, Alation, or IBM Knowledge Catalog.
Exposure to LLM evaluation frameworks such as RAGAS, TruLens, or DeepEval.
Prior consulting, pre-sales, or solutions architecture experience with enterprise AI clients.
Understanding of federated learning, differential privacy, or confidential computing concepts.

Responsibilities

Implement and configure IBM watsonx.governance for model monitoring, bias detection, explainability, and drift detection.
Design AI governance frameworks aligned with enterprise risk management and regulatory requirements, such as the EU AI Act, NIST AI RMF, and SOC 2.
Integrate watsonx.governance with third-party model registries, MLOps pipelines, and enterprise data platforms.
Build automated model evaluation pipelines covering fairness metrics, quality thresholds, and compliance checkpoints.
Partner with data science and MLOps teams to embed governance checkpoints into the model development lifecycle.
Support pre-sales engagements, including demos, proofs of concept, and technical workshops focused on responsible AI.
Develop dashboards and reporting workflows that provide AI risk visibility to business and compliance stakeholders.
Contribute to AI governance policy documentation, playbooks, and client-facing accelerators.
Advise clients on model lineage, audit trails, and AI inventory management best practices.