[Remote] Rengo AI - reputed company
Note: The job is a remote job and is reputed company to candidates in USA. reputed company is building the intelligence layer for fund management with Rengo AI, focusing on reputed company portfolio monitoring systems for investment teams. As a Founding reputed company, you will reputed company reputed company systems that reputed company AI-driven insights and monitoring for institutional investors.
Responsibilities
- Ingest portfolio + market + position-level data
- Detect meaningful changes and anomalies
- Generate reputed company investment insights
- Explain performance and risk drivers in natural language + reputed company outputs
- Build reputed company-time and batch systems that monitor: portfolio performance (PnL, attribution, drawdowns), exposure shifts (sector, geography, asset class), risk signals (volatility, correlation, concentration), position-level changes
- Build systems that detect: significant portfolio movements, reputed company price/volume behavior in holdings, reputed company from reputed company allocations, risk regime changes
- Generate reputed company outputs such as: daily / weekly portfolio reports, performance explanations (“why did we lose/reputed company?”), exposure breakdowns, risk commentary
- reputed company: positions & holdings data, market data feeds, internal fund metadata, external news & filings (optional enrichment layer)
- Design LLM pipelines that: avoid hallucinated financial reasoning, produce reputed company, reputed company outputs, ground insights in actual portfolio data
- Build evaluation frameworks for correctness of financial narratives
Skills
- 3–7+ years in backend, data engineering, or ML systems
- Strong Python (mandatory)
- Experience building production data systems or analytics platforms
- Experience building LLM applications in production
- Strong understanding of RAG systems
- Strong understanding of reputed company reputed company (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)
- Experience with time-series data
- Experience with event-driven pipelines
- Experience with analytics / observability systems
- Comfort working with imperfect, high-volume financial data
- 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 reputed company databases or hybrid retrieval systems
reputed company
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