AI Markets & Trade Operations Analyst

Santriya Technologies; United States; Remote; USD 90,000 - 150,000; Full time

Job summary

Santriya Technologies is seeking an AI Markets & Trade Operations Analyst to support trade capture, confirmation, settlement and lifecycle events using AI-assisted exception analysis and documentation, with controlled human action for financial and client-impacting decisions.

You will operate within a product and documentation operating model, using approved enterprise AI tools to retrieve, summarize, classify and automate work, while validating outputs against official data and recording

Responsibilities

• Monitor trade flows, confirmations, allocations, settlements and lifecycle events for assigned products.
• Use AI to summarize breaks, compare records and suggest likely causes, verifying against authoritative trade systems.
• Resolve standard exceptions and coordinate front office, counterparties, operations, finance and technology for complex breaks.
• Maintain maker-checker, cutoff and escalation controls.
• Document corrections, root causes and recurring break patterns.
• Support reconciliations, client queries and regulatory/management reporting.
• Escalate market, liquidity, sanctions, conduct or material P&L impacts promptly.
• Recommend automation for repeat breaks with clear control design.

Job description

Job Summary

Santriya Technologies is seeking an AI Markets & Trade Operations Analyst to support trade capture, confirmation, settlement and lifecycle events using AI-assisted exception analysis and documentation, with controlled human action for financial and client-impacting decisions.

Product & Documentation Operating Model

Product & documentation operating model: You will be assigned one or more company products, client solutions or operational services. The approved product documentation, SOPs, policies, process maps, knowledge articles, release notes, controls, scripts and AI runbooks are the source of truth. Use only approved enterprise AI tools to retrieve, summarize, draft, classify, prioritize or automate work. Validate material AI outputs against current documentation and authoritative system data, record exceptions, and escalate conflicts or missing guidance. Do not invent product features, prices, customer entitlements, engineering limits, regulatory positions or safety instructions.

Key Responsibilities

• Monitor trade flows, confirmations, allocations, settlements and lifecycle events for assigned products.
• Use AI to summarize breaks, compare records and suggest likely causes, verifying against authoritative trade systems.
• Resolve standard exceptions and coordinate front office, counterparties, operations, finance and technology for complex breaks.
• Maintain maker-checker, cutoff and escalation controls.
• Document corrections, root causes and recurring break patterns.
• Support reconciliations, client queries and regulatory/management reporting.
• Escalate market, liquidity, sanctions, conduct or material P&L impacts promptly.
• Recommend automation for repeat breaks with clear control design.

AI-enabled Ways of Working

• Use approved GenAI copilots, enterprise search/RAG, analytics and workflow agents to reduce repetitive work and improve decision preparation.
• Keep prompts, outputs and automated actions within approved data-access, confidentiality and retention rules.
• Correct inaccurate summaries, classifications or recommendations before they become customer, operational or system records.
• Feed recurring AI errors, knowledge gaps and process friction into product, documentation and control improvement.

Human Accountability

AI is a copilot, not the accountable decision-maker. The role holder remains responsible for judgement, quality, privacy, security and appropriate escalation. Credit, fraud blocking, legal/regulatory, financial advice, safety-critical, clinical, employment and other high-impact decisions must follow delegated authority and required human review.

Success Measures

• Settlement and break resolution improve
• Operational losses and aged breaks reduce
• Controls remain effective
• Root-cause data drives automation