Rengo AI - AI Engineer

deCircle•New York, NY

17d

About The Position

Rengo AI is building the intelligence layer for fund management — starting with next-generation portfolio monitoring systems for investment teams. Today, portfolio monitoring is fragmented across dashboards, spreadsheets, internal tools, and manual analyst workflows. Rengo replaces this with an AI-native monitoring layer that continuously interprets portfolio activity, risk, exposure, and performance across assets and strategies. As a Founding AI Engineer, you will build the core system that powers AI-driven portfolio monitoring for institutional investors. You will design systems that continuously ingest portfolio + market + position-level data, detect meaningful changes and anomalies, generate structured investment insights, and explain performance and risk drivers in natural language + structured outputs. This is a high-reliability AI system, not a chatbot.

Requirements

Strong engineering background
3–7+ years in backend, data engineering, or ML systems
Strong Python (mandatory)
Experience building production data systems or analytics platforms
LLM / AI systems experience
Experience building LLM applications in production
Strong understanding of RAG systems
Strong understanding of structured generation (schemas, JSON outputs)
Strong understanding of tool use / function calling
Strong understanding of agent workflows
Awareness of failure modes in LLM reasoning (critical in finance)
Data-heavy systems mindset
Experience with time-series data
Experience with event-driven pipelines
Experience with analytics / observability systems
Comfort working with imperfect, high-volume financial data

Nice To Haves

Experience in asset management / hedge funds / fintech
Experience in portfolio analytics or risk systems
Experience in trading / market data infrastructure
Familiarity with exposure/risk models
Familiarity with PnL attribution systems
Familiarity with BI / analytics platforms for finance
Experience with vector databases or hybrid retrieval systems

Responsibilities

Build AI Portfolio Monitoring Engine: Real-time and batch systems that monitor portfolio performance (PnL, attribution, drawdowns), exposure shifts (sector, geography, asset class), risk signals (volatility, correlation, concentration), and position-level changes.
Develop AI layer that converts raw portfolio data into alerts, summaries, and explanations.
Build Change Detection & Intelligence Layer systems that detect significant portfolio movements, abnormal price/volume behavior in holdings, drift from target allocations, and risk regime changes.
Create a prioritization layer to distinguish what matters from noise.
Develop AI-Generated Portfolio Narratives to generate structured outputs such as daily/weekly portfolio reports, performance explanations, exposure breakdowns, and risk commentary, ensuring outputs are auditable, grounded in data, and consistent across runs.
Build Data + Retrieval Systems for Funds, integrating positions & holdings data, market data feeds, internal fund metadata, and optionally external news & filings.
Build RAG pipelines over portfolio + market context.
Design LLM Systems for Financial Reliability, ensuring LLM pipelines avoid hallucinated financial reasoning, produce structured, verifiable outputs, and ground insights in actual portfolio data.
Build evaluation frameworks for the correctness of financial narratives.