AI Engineer

Posted 1hrs ago

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Job Description

Agentic AI Engineer building QuantPilot’s AI trading copilot for serious retail traders. Owning LLM agent architecture, evaluation, statistical backtesting, and production reliability.

Responsibilities:

  • Own the agent architecture end to end, including orchestration, tool loops, context management, sandboxes, model routing, and production quality, cost, and latency trade-offs
  • Own contracts between the engine and product, including frontend rendering of agent events
  • Build and own offline evaluations, backtest-based quality metrics, and regression detection for prompt or model changes
  • Apply statistical rigor to strategy evaluation, including overfitting detection, robustness checks, and walk-forward and out-of-sample validation
  • Build data foundations with provenance, validation, and a consistent model of market entities
  • Improve observability to diagnose non-deterministic production failures
  • Refine requirements with product and set technical direction through RFCs and ADRs
  • Mentor engineers moving into LLM systems
  • Participate in on-call rotation, act as first responder for production incidents, and follow the incident response process

Requirements:

  • 5+ years of backend or ML engineering experience
  • At least 1 year building LLM-based systems in production
  • Track record of eval-driven development
  • Strong Python and production engineering fundamentals, including services, queues, streaming, observability, and Kubernetes
  • Ability to work with TypeScript or Go
  • Experience applying statistical principles to backtesting methodology
  • Product mindset and ability to take ambiguous goals to shipped, measured results
  • Working proficiency in English (B2+)
  • Quant finance background is a plus
  • Experience with knowledge graphs, ontologies, semantic layers, or RAG is a plus
  • Experience with Go is a plus
  • Experience building software on the receiving end of the MCP protocol is a plus
  • Experience with high-load, low-latency systems in fintech or trading is a plus
  • Language model fine-tuning or training experience is a plus
  • Participation in on-call rotation and incident response for owned services

Benefits:

  • Responsible use of AI-assisted development tools as part of the engineering workflow
  • Participation in the team's on-call rotation with end-to-end service ownership
  • Global/remote work arrangement