Note: The job is a remote job and is open to candidates in USA. Luxoft is seeking an AI Governance Engineer to support the technical build-out of AI standards and controls for a banking environment. The role will draft standards, engineer testable controls, map obligations to evidence, contribute to policy-as-code and automation, validate platform enforcement, and support governance operations, assessments, and audit readiness.
Responsibilities
- Draft and iterate the AI standards library under the Lead's direction: model onboarding and approval, oversight tiers, logging/retention, agentic guardrails, data-classification handling, and acceptable use
- Engineer each control as a testable requirement: definition, enforcement point, owner, evidence artifact, and validation method
- Build and maintain obligation-to-control-to-evidence mappings against regulatory guidance and internal policy
- Contribute to policy-as-code and controls-automation approaches with the platform team where controls can be enforced or checked mechanically
- Produce evidence artifacts, control attestations, and assessment documentation for deviations, exceptions, and governance reviews
- Validate platform-generated evidence (audit logs, entitlement records, quota enforcement) against control requirements; document gaps and drive fixes
- Support deviation and exception lifecycle management: drafting, compensating-control documentation, tracking, and closure evidence
- Assemble components of examiner-readiness and audit-response packages
- Support AI Control Group, working group, and committee operations with prepared materials, assessments, and documented decisions
- Maintain the AI use case and agent registry data quality in partnership with intake and platform onboarding
- Document governance processes, runbooks, and templates in bank repositories for FTE handover
- Transfer working knowledge to bank FTEs throughout the engagement
Skills
- Minimum of 5 years' experience in technology governance, IT risk/controls, security governance engineering, or compliance engineering in a technology environment
- Demonstrated experience writing technical standards, control frameworks, or control documentation that maps to regulatory or policy obligations
- Working technical knowledge of cloud platforms and modern application patterns: APIs and gateways, identity/RBAC, logging and monitoring, environment separation
- Familiarity with AI/GenAI systems sufficient to write accurate, enforceable requirements for model access, oversight, and logging
- Strong technical writing and documentation discipline; able to produce artifacts that survive audit and second-line challenge
- Experience with GRC processes: exceptions, findings, evidence collection, and remediation tracking
- Financial services or other highly regulated industry experience; familiarity with model risk management concepts
- Experience with policy-as-code, compliance automation, or controls testing automation
- Familiarity with NIST AI RMF, SR 11-7/SR 26-2 lineage, or comparable AI governance frameworks
- Azure experience (APIM, Entra ID, Azure Monitor, Key Vault)
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