jobapplier

Agentic AI Engineer

3Commas

Skills

Required

  • Python
  • TypeScript / Go
  • backtesting
  • queues
  • streaming
  • observability
  • Kubernetes
  • following a bug
  • backend / ML engineering
  • LLM-based

Preferred

  • Language model
  • fine-tuning / training
  • backtesting methodology

Join QuantPilot's Applied AI team as an Agentic AI Engineer. In this role, you will focus on AI research, strategy generation, and the agent platform. You will own the agent architecture, contracts between the engine and product, and the evaluation layer. You will also build the data foundations for the agent and shape what gets built. The ideal candidate has strong Python and production fundamentals, a product mindset, a track record of eval-driven development, and a quant finance background.

Participer à la recherche et au développement de stratégies d'agent qui sont statistiquement solides et prouvées par l'évaluation.

About 3Commas

A track record of eval-driven development: you can show a quality metric you kept honest over time and how you used it to improve an agent

Responsibilities

  • Posséder l'architecture de l'agent de bout en bout, y compris l'orchestration, les boucles d'outils, la gestion du contexte, les bacs à sable et le routage des modèles.
  • Construire et posséder la couche d'évaluation, y compris les évaluations hors ligne, les métriques de qualité basées sur les tests de retour et la détection de régression.
  • Application of statistical principles on backtesting methodology

Requirements

Working proficiency in English (B2+)

  • Strong Python and production fundamentals (services, queues, streaming, observability, Kubernetes). You're comfortable following a bug into TypeScript or Go, and you treat pipelines, migrations and guards as real engineering
  • 5+ years of backend or ML engineering, including at least one year building LLM-based systems in production. You understand agent failures one level below the framework and can fix them in your own code
  • A product mindset: you judge your work by what the user gets, and you take ambiguous goals to shipped, measured results
  • Quant finance background: backtesting frameworks, market data and strategy research, including the pitfalls of backtesting indicator-based strategies
  • Experience with knowledge graphs, ontologies or semantic layers. RAG experience is a plus
  • Experience with Go
  • You have built software on the receiving end of the MCP protocol, such as MCP servers or tools consumed by agents
  • High-load, low-latency systems in fintech or trading

Preferred

  • Language model fine-tuning or training experience