Clinical-AI Model Stewardship GCC Blueprint Director

The mandate

Trial-planning models for site feasibility, enrolment and operational risk are moving into the Hyderabad GCC, but lifecycle ownership is split among data scientists, clinical teams and platform operations. Models can be technically refreshed without a named owner for changed clinical context or human override patterns. Leadership needs a stewardship design before scale makes every model exception a committee escalation.

The six-month deliverable consists of a clinical-AI stewardship charter, three model-product blueprints and an exercised acceptance pack. Milestone one maps decisions and evidence by week five; milestone two fixes lifecycle and assurance boundaries in month three; milestone three completes changed-population and override scenarios in month five; the final milestone delivers launch waves, leadership profiles and council-approved operating artefacts.

The client will provide model cards, validation and performance records, protocol context, override histories, quality procedures, platform controls and access to clinical and statistical decision owners. Acceptance requires Hyderabad stewards to diagnose three unseen scenarios, state limitations, propose proportionate action and preserve the named human decision. Medical, quality and data executives jointly sign the model blueprints.

Clinical-trial design, investigator selection, patient-level decision making, formal quality approval, enterprise AI-platform implementation and regulatory submissions are excluded. Consultants may define evidence and operating interfaces but cannot validate a model, approve clinical use or interpret jurisdiction-specific law. All sensitive data remains in client-controlled environments using approved access.

Reusable artefacts include model-product envelopes, change classifications, monitoring and override review, decision matrices, escalation thresholds, role profiles and transfer gates. A client team will adapt the method to a fourth model during the last workshop, demonstrating independence from consultant authorship. Optional implementation support is separately scoped and cannot qualify or delay the accepted blueprint.

Why this is external work

Clinical owners, AI engineers and platform teams each see a valid portion of the model lifecycle, but none owns the cross-functional design. Internal policy work has produced controls without an operable steward role in Hyderabad. External clinical-AI operating experience can create clear accountability while protecting medical and independent quality decisions.

What you will own

• Map trial-planning models from intended use and population through data, training, validation, deployment, monitoring and retirement.
• Define steward decisions for limitations, refresh proposals, performance interpretation, override patterns and temporary use restrictions.
• Separate engineering execution, clinical judgment, biostatistical challenge, quality assurance and accountable human action.
• Design Hyderabad leadership and specialist roles with access to protocol context, users and global governance forums.
• Exercise population shift, sparse evidence, conflicting metrics, excessive override and platform-degradation scenarios.
• Establish transfer gates around documentation, reproducibility, clinical context, monitored use and source-team withdrawal.
• Deliver three blueprints, scenario evidence, role architecture, rollout economics and unresolved clinical-policy decisions.

Candidate qualifications

• Designed lifecycle governance for AI or statistical models used in clinical development, trial operations or regulated research.
• Established India-based model stewards with authority over limitations, monitoring interpretation and change proposals.
• Separated independent validation, medical accountability, model engineering and platform operation without creating approval loops.
• Addressed population shift, operational override or changed protocol context using proportionate use restrictions and evidence.
• Built model-product documentation that connected intended use, performance, uncertainty, human action and retirement.
• Delivered a stewardship method that clinical and data teams reused independently on models outside the consulting sample.

Non-negotiables

• Can complete two global clinical-governance residencies and four Hyderabad milestones within six months.
• Will disclose pharmaceutical, CRO, model-vendor, data-provider, clinical-technology and validation relationships.
• Brings clinical-model lifecycle and India capability design; generic AI governance without clinical use is insufficient.
• Accepts client-controlled data, joint medical-quality acceptance and no authority over clinical or regulatory decisions.

1. 49 words maximum. Describe a trial-planning model whose technical performance remained stable while its clinical context changed.
2. 49 words maximum. Which stewardship decision can Hyderabad own without inheriting the accountable medical judgment?
3. 49 words maximum. What model, override and protocol evidence must the client provide before your first milestone?