AI Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Take full ownership of the agent architecture from start to finish, encompassing orchestration, tool loops, context management, sandboxes, model routing, as well as considerations for production quality, cost, and latency trade-offs.

• Manage contracts between the engine and product, which includes the frontend rendering of agent events.

• Develop and maintain offline evaluations, quality metrics based on backtesting, and regression detection for any prompt or model alterations.

• Utilize statistical rigor for strategy evaluation, including detecting overfitting, conducting robustness checks, and executing walk-forward and out-of-sample validation.

• Establish data foundations that include provenance, validation, and a coherent model of market entities.

• Enhance observability to troubleshoot non-deterministic failures in production.

• Collaborate with the product team to refine requirements and establish technical direction through RFCs and ADRs.

• Mentor engineers transitioning into LLM systems.

• Engage in on-call rotations, serving as the initial responder for production incidents while adhering to the incident response process.

⛳️ Requirements

• A minimum of 5 years of experience in backend or ML engineering.

• At least 1 year of experience in developing LLM-based systems in a production environment.

• Proven track record of evaluation-driven development.

• Strong foundation in Python and production engineering principles, including services, queues, streaming, observability, and Kubernetes.

• Proficiency in TypeScript or Go.

• Experience in applying statistical principles to backtesting methodologies.

• A product-oriented mindset with the capability to transform ambiguous objectives into measurable, shipped results.

• Working proficiency in English (B2+).

• A background in quantitative finance is advantageous.

• Familiarity with knowledge graphs, ontologies, semantic layers, or RAG is a plus.

• Experience with Go is considered an asset.

• Experience in developing software that interacts with the MCP protocol is a benefit.

• Prior experience with high-load, low-latency systems within fintech or trading is advantageous.

• Experience in fine-tuning or training language models is a plus.

• Participation in on-call rotations and incident response for services under your ownership is expected.

🏝️ Benefits

• Responsible utilization of AI-assisted development tools integrated into the engineering workflow.

• Participation in the team's on-call rotation with complete service ownership.

• Global/remote work flexibility.