AI Engineer

Job not on LinkedIn

🕒 May 20

🗽 New York – Remote

🗽 New York – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

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decircle

WebsiteLinkedInAll Job Openings

1 - 10 employees

Founded 2019

📣 Marketing

📦 Logistics

💼 Consulting

Marketing • Logistics • Consulting

Decircle is a talent partner specializing in staffing and recruiting for decentralized organizations and projects related to Web3. As a boutique recruitment agency, Decircle focuses on identifying and attracting talent in the blockchain and Web3 sectors, fostering connections within the community of decentralization enthusiasts and guiding them in finding their roles in the evolving decentralized landscape.

📋 Description

• Build the core system that powers AI-driven portfolio monitoring for institutional investors • Design systems that continuously: ingest portfolio + market + position-level data detect meaningful changes and anomalies generate structured investment insights explain performance and risk drivers in natural language + structured outputs • 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) position-level changes AI layer that converts raw portfolio data into: alerts summaries explanations actionable insights • Change Detection & Intelligence Layer Build systems that detect: significant portfolio movements abnormal price/volume behavior in holdings drift from target allocations risk regime changes Prioritization layer: what matters vs noise • AI-Generated Portfolio Narratives Generate structured outputs such as: daily / weekly portfolio reports performance explanations (“why did we lose/gain?”) exposure breakdowns risk commentary Ensure outputs are: auditable grounded in data consistent across runs • Data + Retrieval Systems for Funds Integrate: positions & holdings data market data feeds internal fund metadata external news & filings (optional enrichment layer) Build RAG pipelines over portfolio + market context • LLM Systems for Financial Reliability Design LLM pipelines that: avoid hallucinated financial reasoning produce structured, verifiable outputs ground insights in actual portfolio data Build evaluation frameworks for correctness of financial narratives

🎯 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 structured generation (schemas, JSON outputs) tool use / function calling agent workflows • Awareness of failure modes in LLM reasoning (critical in finance) • Data-heavy systems mindset • Experience with: time-series data event-driven pipelines analytics / observability systems • Comfort working with imperfect, high-volume financial data

🏖️ Benefits

• Competitive salary • Flexible working hours • Professional development budget • Home office setup allowance • Global team events