Satish J

Results-driven AI/ML Risk and Operations professional with direct Amazon experience across fraud and transaction risk investigation, LLM/AI output quality evaluation, and visual content operations. Specialised in LLM behavioural validation, prompt quality assurance, hallucination and anomaly detection, and high-volume analytical decision-making. Proven track record of quality benchmark compliance under strict SLA environments.

Proficient in SQL and Advanced Excel; foundational Python. Self-studying SR 11-7 / OCC Model Risk Management frameworks.

ML Data Associate — AI Quality & Risk Evaluation - Amazon - Bengaluru, India

(2024-12 - 2026-03)

• Conducted 500+ daily LLM output evaluations and transaction risk assessments via MTurk-based workflows, maintaining quality benchmark compliance across all reviewed cases.
• Independently investigated complex fraud patterns, anomalies, and policy violations across large unstructured datasets — flagging heightened risk signals with high-accuracy independent decisions.
• Executed Prompt QC and Agent Turn validation within multi-agent AI pipelines, ensuring model responses met Amazon's safety, accuracy, and risk control standards.
• Maintained comprehensive audit-ready documentation for every investigated case, supporting AI/ML model approval workflows and regulatory-style evidence collection.
• Resolved complex edge cases with minimal supervision, applying structured analytical judgment comparable to a 2nd Line of Defence (2LoD) model risk reviewer.
• Consistently met and exceeded productivity SLAs while enforcing Amazon policy guidelines — demonstrating reliability in high-pressure, remote-compatible environments.
• Collaborated cross-functionally with data scientists, engineers, and operations teams to surface process gaps and propose quality improvement actions.

Technical Advisor - Altruist Technology - Bengaluru, India

(2024-01 - 2024-12)

• Delivered structured root cause analysis and technical troubleshooting for complex incidents, resolving cases within SLA timelines.
• Maintained meticulous CRM documentation ensuring full audit readiness, regulatory compliance, and complete traceability of all customer interaction records.
• Sustained top-tier quality assurance metrics across all assigned cases — demonstrating consistent accuracy, ownership, and process adherence.
• Communicated complex technical findings clearly to non-technical stakeholders via written and verbal channels.

Bachelor of Engineering - Computer Science - Paavai Engineering College (2023)