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AI Governance & Responsible AI

AI Governance & Responsible AI is an individual-contributor Data + AI career progressing from guided delivery to enterprise expertise without requiring people management.

Archetype
Specialist
Highest level
L6 · Senior Principal AI Governance Specialist

Why it exists

Establishes governance, risk, policy, assurance and lifecycle controls enabling trustworthy, compliant and responsible AI.

Typical responsibilities

Deliver ai governance & responsible ai outcomes; apply data/AI standards; manage quality, reliability and risk; collaborate across product, engineering, security, legal and business teams; at senior levels shape enterprise standards and strategy.

Where the work happens

Technology companies, data/cloud platforms, financial services, consulting, shared services, product engineering and regulated enterprises adopting Data + AI.

How the career progresses

Associate AI Governance Specialist → AI Governance Specialist → Senior AI Governance Specialist → Lead AI Governance Specialist → Principal AI Governance Specialist → Senior Principal AI Governance Specialist

Levels in this career

Six standard stages. The seventh exists only where the career provides for it.

What is expected at L2 · AI Governance Specialist

Apply ai governance & responsible ai capability at independently delivers standard work within a team or defined domain.

The five dimensions that change

Autonomy
Independent routine ownership
Scope
Independently delivers standard work within a team or defined domain.
Complexity
Moderate
Influence
Immediate team
Business impact
Task/team
Ambiguity
Moderate

What good looks like

Produces trustworthy ai governance & responsible ai outcomes, makes sound trade-offs, communicates evidence and risks, and demonstrates the autonomy and impact expected at L2.

Typical evidence

Completed ai governance & responsible ai work products or production outcomes; documented decisions; measurable improvements in quality, reliability, risk, speed, cost or business outcomes; peer/stakeholder evidence of L2 scope.

Skills expected at L2

Grouped as human, professional and technical. Target proficiency uses the P1–P7 scale, and each row says what that level means for that particular skill.

Human8

HumanPSupporting
Clear verbal communicationCommunication & LanguageP2FoundationalSupportingApplies Clear verbal communication to routine situations using established methods and controls.
Clear written communicationCommunication & LanguageP2FoundationalSupportingApplies Clear written communication to routine situations using established methods and controls.
CollaborationCollaboration & RelationshipsP2FoundationalSupportingApplies Collaboration to routine situations using established methods and controls.
Critical thinkingThinking & Problem SolvingP2FoundationalSupportingApplies Critical thinking to routine situations using established methods and controls.
Cross-functional collaborationCollaboration & RelationshipsP2FoundationalSupportingApplies Cross-functional collaboration to routine situations using established methods and controls.
Learning agilityExecution & Self-ManagementP2FoundationalSupportingApplies Learning agility to routine situations using established methods and controls.
Stakeholder alignmentInfluence & Leadership Without AuthorityP2FoundationalSupportingApplies Stakeholder alignment to routine situations using established methods and controls.
Structured problem solvingThinking & Problem SolvingP2FoundationalSupportingApplies Structured problem solving to routine situations using established methods and controls.

Professional7

ProfessionalPSupporting
AI governanceData & Analytics PracticeP2FoundationalCoreApplies AI governance to routine situations using established methods and controls.
AI impact assessmentData & Analytics PracticeP2FoundationalSupportingApplies AI impact assessment to routine situations using established methods and controls.
AI lifecycle governanceData & Analytics PracticeP2FoundationalSupportingApplies AI lifecycle governance to routine situations using established methods and controls.
AI model governanceData & Analytics PracticeP2FoundationalSupportingApplies AI model governance to routine situations using established methods and controls.
AI risk assessmentData & Analytics PracticeP2FoundationalCoreApplies AI risk assessment to routine situations using established methods and controls.
AI use-case intake and approvalData & Analytics PracticeP2FoundationalSupportingApplies AI use-case intake and approval to routine situations using established methods and controls.
Responsible AI principlesData & Analytics PracticeP2FoundationalCoreApplies Responsible AI principles to routine situations using established methods and controls.

Technical8

TechnicalPSupporting
AI guardrails and content safety engineeringData Science, ML & AIP2FoundationalSupportingUses AI guardrails and content safety engineering for routine tasks with documented patterns and review.
AI observabilityData Science, ML & AIP2FoundationalSupportingUses AI observability for routine tasks with documented patterns and review.
AI red teamingData Science, ML & AIP2FoundationalCoreUses AI red teaming for routine tasks with documented patterns and review.
Data catalog platformsDatabases & Data PlatformsP2FoundationalSupportingUses Data catalog platforms for routine tasks with documented patterns and review.
Data lineage toolingDatabases & Data PlatformsP2FoundationalSupportingUses Data lineage tooling for routine tasks with documented patterns and review.
LLM evaluation and benchmarkingData Science, ML & AIP2FoundationalCoreUses LLM evaluation and benchmarking for routine tasks with documented patterns and review.
Model validation testingData Science, ML & AIP2FoundationalCoreUses Model validation testing for routine tasks with documented patterns and review.
Prompt injection and jailbreak defenseData Science, ML & AIP2FoundationalCoreUses Prompt injection and jailbreak defense for routine tasks with documented patterns and review.

What changes from L2 to L3

Moving from AI Governance Specialist to Senior AI Governance Specialist means greater autonomy, complexity, scope, influence and evidence of impact—not simply more tools.

How readiness is shown

Sustained evidence of operating at L3-type scope: handles representative complexity, influences expected stakeholders and produces durable measurable outcomes.

How to prepare

Take on one assignment at next-level scope; seek feedback; document decisions/outcomes; mentor others where appropriate; close highest-priority skill gaps.

Career framework v21, active since August 17, 2026.

AI Governance & Responsible AI · Costa Rica TecHub