Principal Artificial Intelligence Engineer

***Hybrid, 3 days onsite, 2 days remote******We are unable to sponsor as this is a permanent full-time role***Responsibilities:Partner with the Executive Director of AI Engineering to define and execute the AI technical roadmap, translating organizational priorities into concrete architectural decisions Lead the company’s agentic AI efforts: architect, build, and operate systems that connect AI agents to internal systems, data pipelines, and business workflows Leverage the company’s direct relationships with AWS and Anthropic to evaluate and adopt new model capabilities and tooling as they become available Build and ship production AI applications on AWS using Claude and related Anthropic tooling, maintaining high standards for reliability, security, and auditability Architect scalable systems that integrate LLMs and AI agents into company’s internal systems, operational workflows, and business processes, owning decisions from design through production deployment Define and enforce AI safety standards appropriate for a regulated SIFMU environment, including hallucination detection, output validation, bias assessment, and audit trails that satisfy SEC and CFTC oversight expectations Establish responsible AI practices and safety guardrails for LLM applications operating on sensitive financial data Qualifications:Bachelor's or Master's in Computer Science or a related technical field 10+ years of software engineering and systems architecture experience, with demonstrated technical leadership 5+ years as a senior individual contributor on complex, high-stakes production systemsExpert-level Python; proficient in SQL Deep system design expertise: distributed systems, microservices, event-driven architectures, APIs, and MCP servers Hands-on experience with data engineering: pipelines, transformation, and data modeling AWS experience; comfort with Docker, Kubernetes, and CI/CD pipelines Strong production AI/LLM experience, or demonstrated hands-on passion for the space with the engineering depth to ramp quickly Experience designing and operating agentic AI systems in enterprise environments Experience with context engineering strategies including RAG, prompt architecture, and retrieval pipeline design Familiarity with frontier models including Claude, GPT, and Gemini, and hands-on experimentation with emerging tools Hands-on experience with Anthropic's tooling and APIs, including the Claude API, Claude.ai, or the Anthropic Console Experience connecting AI agents to enterprise systems and workflows Infrastructure as code (Terraform)