Risk Specialist, ASCI Program and Operations Team

Alexa is the voice activated digital assistant powering devices like Amazon Echo devices and Fire TV which are at the forefront of this latest technology wave. To preserve our customers experience and trust the Alexa Sensitive Content Intelligence (ASCI) team creates policies and builds services and tools through Machine Learning techniques to detect and mitigate sensitive content across Alexa.
We are seeking a Risk Specialist to join our Risk team focused on maintaining the quality accuracy and integrity of AI-driven initiatives and risk management this role you will work on essential Program and operations that support the development and continuous improvement of AI systems including creating reviewing and managing datasets monitoring compliance and contributing to the mitigation of risks across products and services.
You will be responsible for executing and delivering risk projects within a well-defined risk framework applying proven risk management methodologies to identify and address risks across areas such as regulatory reputational safety policy and business continuity. You will collaborate closely with your team and cross-functional stakeholders to drive meaningful measurable outcomes.
This is an excellent opportunity for a detail-oriented professional who communicates clearly thrives in a structured environment and is eager to grow their expertise in risk management and AI operations within a collaborative fast-paced environment.

Key job responsibilities
Identify define and document risk pathways and threat scenarios; develop and maintain structured frameworks categorizing risks by type severity and likelihood
Collaborate with stakeholders to keep risk frameworks aligned with current and emerging risk landscapes using them to guide assessment testing and mitigation
Monitor AI-driven workflows and automated decision-making pipelines for quality accuracy and compliance; identify gaps escalate issues and coordinate corrective actions with technical teams
Triage and escalate vulnerabilities detected through monitoring audits or team submissions; assess severity determine escalation paths and drive timely resolution with cross-functional teams
Own creation maintenance and QA of reference datasets for model evaluation and performance calibration; enforce standards for composition labeling accuracy and version control
Design and oversee human review processes at critical AI decision points; define review criteria sampling strategies and feedback mechanisms to maintain output quality
Act as liaison between your team and cross-functional partners; facilitate alignment on risk priorities policy requirements and project goals while managing expectations proactively
Coach and support team members in risk assessment data review and process execution; lead calibration sessions to ensure consistency and identify skill gaps
Oversee annotation and labeling quality through audits spot-checks and structured feedback; track quality metrics and implement corrective measures
Own operational guidelines annotation standards and policy documentation; regularly review and update to reflect current policies edge cases and lessons learned
Monitor team output against volume targets and SLAs; identify risks to attainment and develop proactive mitigation plans
Manage intake triage and resolution of escalations; maintain clear records of decisions and outcomes
Design and deliver onboarding programs and training materials for new team members; continuously improve content based on feedback and performance gaps
Continuously evaluate workflows and processes to identify inefficiencies; implement improvements that enhance effectiveness reduce errors and improve scalability

- 2 years of data-driven business operations processes experience
- Bachelors degree or equivalent
- Experience communicating clearly and concisely with leadership stakeholders and cross-functional teams
- Experience in compliance audit or risk management
- Ability to recognize operational and risk management challenges and determine how AI-based solutions can be leveraged to drive efficiency accuracy and scalability.

- Experience working across functional teams and senior stakeholders
- Knowledge of process improvement and quality measures
- Experience using data and metrics to measure impact and determine improvements
- Experience working with AI/ML concepts including data annotation model evaluation or quality assurance for AI systems.
- Experience identifying process gaps or risk management opportunities and translating them into agentic AI solutions including scoping requirements defining agent behaviors and validating outputs against quality and compliance standards.
- Experience developing SOPs workflows or policy documentation.
- Strong analytical and problem-solving skills particularly for complex or ambiguous risk-related issues.

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