Applied AI Engineer

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Derivative Path

WebsiteLinkedInAll Job Openings

51 - 200 employees

💸 Finance

💳 Fintech

☁️ SaaS

💰 $35M Private Equity Round on 2020-06

Finance • Fintech • SaaS

Derivative Path is a leading provider of cloud-based platforms and technologies for managing derivatives and hedging programs. The company offers specialized services in interest rate derivatives, foreign exchange, and commodities trading. With a strong focus on risk management and compliance, Derivative Path provides solutions such as hedge accounting, FX payments, and platform solutions for balance sheet and customer loan hedging. Catering to financial institutions, end-users, and buy-side clients, Derivative Path's software as a service (SaaS) technology supports real-time payments and advanced derivatives trading strategies. The firm integrates artificial intelligence to enhance operational efficiency and reduce time spent on trade-related tasks.

📋 Description

• Build and ship LLM-powered features across the DerivativeEDGE platform, working directly with domain experts to translate complex financial workflows into reliable AI capabilities. • Design and implement agentic workflows that can reason, act, and recover gracefully across multi-step processes in a production environment. • Own the data engineering layer that feeds AI systems: pipelines, retrieval architectures, context design, and data quality. • Move fluidly between experimentation and production. You will prototype quickly, evaluate honestly, and know when something is ready to ship. • Contribute to the AI Lab's broader technical direction, including evaluations, tooling, MLOps practices, and the patterns the team builds on. • Depending on where projects take you, work may also touch NLP, model fine-tuning, synthetic data, or reinforcement learning.

🎯 Requirements

• Building with LLMs: prompt engineering, RAG, fine-tuning, agents, or inference pipelines • Data engineering: designing and building pipelines that feed real workflows • ML or data science work, especially in complex or data-constrained environments • Working knowledge of Python and common AI/ML frameworks (PyTorch, HuggingFace, LangChain, or similar) • MLOps or production AI experience: getting models out of notebooks and into the real world • Cloud platform experience (Azure, AWS, or GCP) • Experience with reinforcement learning or financial derivatives is a bonus, not a baseline.

🏖️ Benefits

• Competitive bonus, base salary, and equity compensation • 23 days of PTO • Fully remote • RRSP contribution at 3% • Competitive health benefits