AI Governance Lead- HYBRID Bloomfield, CT

AI Governance Lead

Conexess Group is aiding a large healthcare client in their search for an AI Governance Lead in a hybrid capacity. This is a long-term contract opportunity with a competitive compensation package. The AI Governance Lead will own and evolve the enterprise AI governance framework—policies, standards, guardrails, and operating mechanisms—to enable responsible AI adoption s role partners closely with Security, Privacy, Compliance, Legal, Risk, Audit, Data Governance, and Technology to create clear, usable controls that accelerate delivery while containing risk.

Responsibilities:

• Draft, maintain, and operationalize enterprise Responsible AI policies, standards, and procedures (e.g., scope, definitions, approvals, roles/accountabilities, documentation requirements).
• Establish governance requirements across the AI lifecycle (intake → design → build → validate → deploy → monitor → retire), including change control and exception handling.
• Translate policy into practical delivery guidance (playbooks, decision trees, "how-to" guides) that teams can adopt without slowing down product velocity.

• Design and continuously improve an AI risk tiering model (e.g., Tier 0–4) based on factors such as impact, autonomy, data sensitivity, regulatory exposure, and customer/member risk.
• Define control sets by tier (e.g., human-in-the-loop requirements, testing depth, monitoring frequency, model governance artifacts, approval gates).
• Establish governance patterns that teams can reuse (approved prompts/patterns, model cards, data sheets, red teaming, evaluation protocols, safe deployment architectures).
• Build "fast paths" for low-risk use cases and tighter governance for higher tiers—balancing scale and safety.

• Serve as the primary convener across Security, Privacy, Compliance, Legal, Risk Management, Audit, and Data Governance to align on expectations and integrate controls.
• Lead working sessions to resolve ambiguity, drive decisions, and translate stakeholder needs into implementable governance requirements.
• Partner with platform and engineering leaders to embed governance into tools and workflows (e.g., intake forms, CI/CD gates, logging/monitoring, policy-as-code where feasible).

• Define and run governance decisioning forums (e.g., risk review boards, architectural review checkpoints, tier adjudication).
• Implement a governance intake and review process for AI solutions (including evaluation of risk tier, required artifacts, and control readiness).
• Track and report governance KPIs: adoption of standards, compliance rates, exceptions, time-to-approval, post-deployment incidents, drift/monitoring health.

• Establish requirements and templates for: bias/fairness evaluation, explainability, robustness/safety testing, privacy impact assessment, and security threat modeling.
• Ensure production AI systems have adequate monitoring, logging, and incident response processes (including escalation paths and rollback plans).
• Maintain documentation and evidence to support internal/external audits, regulatory inquiries, and executive reporting.

• Create training and communications that drive consistent governance adoption across product, engineering, and business teams.
• Build communities of practice and "governance champions" within delivery teams to scale the operating model.

Requirements:

• Bachelor's Degree or equivalent work experience
• Policy craftsmanship: clear, implementable policy writing and standards design
• Risk-based thinking: tiering, controls mapping, and pragmatic decisioning
• Influence & facilitation: ability to align diverse stakeholders and drive outcomes
• Operational rigor: metrics, governance cadence, audit readiness
• Enablement mindset: scalable patterns and "paved roads" that accelerate safe adoption