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Tier-1 employer, metro location, popular AI role with broad LLM and production requirements.
Requires market-risk knowledge, MRM exposure, and finance certifications, limiting cross-industry transferability.
Many mandatory LLM frameworks, vector DB, MCP, and model-risk/regulatory requirements create strict filters.
Design and implement single-agent and simple multi-agent AI workflows using frameworks like LangGraph, LangChain, AutoGen, CrewAI for Traded Risk teams.
Lead end-to-end development of Agentic AI applications including prototyping, deployment, and integration with internal risk systems.
Build and monitor RAG pipelines and guardrails, conduct evaluation of AI agents, and collaborate with market risk SMEs to automate judgment-heavy processes.
Proficient in Python with API integration, async programming, and data manipulation (pandas/numpy).
Hands-on experience with agent orchestration frameworks or LLM APIs (LangChain, LangGraph, Claude, OpenAI, Gemini).
Foundational understanding of market risk concepts; FRM Part I/II, CQF, or equivalent certification in progress or completed.
Work Experience Required: Interns considered with 1 year AI exposure; prior experience in regulated environments or with MCP server development preferred but not strictly mandatory.
Experienced in technical build roles such as software engineering, data engineering, or quant development with focus on AI agent development for risk.
Skilled at translating manual risk assessment processes into structured agentic workflows within a regulated financial environment.
Familiar with model risk management frameworks and capable of managing AI solution auditing and compliance documentation.