***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 systems
Expert-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)