Principal, Artificial Intelligence Engineer

Principal, Artificial Intelligence Engineering

Role Overview
We are looking for a Principal AI Engineer to serve as the technical lead for our newly established AI Research & Engineering team. This senior individual contributor role requires a highly experienced engineer with deep software engineering expertise, strong technical leadership, and foundational knowledge of AI and large language models (LLMs).

You will play a critical role in shaping and delivering our AI strategy, building production-grade systems, and mentoring junior engineers. This position offers the opportunity to work on cutting-edge technologies while fostering a culture of innovation and continuous learning.

Key Responsibilities

• Collaborate with the Executive Director of AI Engineering to define and execute the organization's AI roadmap.
• Architect and implement scalable systems that integrate LLMs and AI into enterprise processes and infrastructure.
• Design and develop production-ready applications for business-critical use cases.
• Provide technical guidance and mentorship to junior engineers (no direct reports).
• Conduct code and architecture reviews to ensure security, compliance, and production readiness.
• Develop testing and monitoring frameworks for AI systems, including hallucination detection and bias evaluation.
• Establish responsible AI practices and safety guardrails for LLM applications in regulated environments.
• Integrate AI agents into organizational workflows and systems.
• Research emerging technologies and recommend adoption strategies.
• Promote a culture of continuous learning and experimentation in a rapidly evolving AI landscape.

Required Qualifications

• Bachelor's or Master's degree in Computer Science or related technical field.
• 10+ years of software engineering and systems architecture experience with proven technical leadership.
• 5+ years as a senior technical contributor on complex production systems.
• Expert in Python and proficient in SQL.
• Strong system design experience: monolithic and microservice architectures, distributed systems, event-driven architectures, APIs.
• Hands-on experience with data engineering, pipelines, and transformations.
• Foundational knowledge of LLMs and familiarity with leading models (e.g., Gemini, Claude, GPT).
• Understanding of AI risk factors: hallucinations, bias, prompt injection, and data privacy.
• Experience mentoring and reviewing work of junior engineers.
• Excellent communication skills for explaining complex technical concepts.
• Demonstrated passion for AI/LLMs and commitment to continuous learning.

Preferred Qualifications

• Production experience with AI applications or LLM-powered systems.
• Knowledge of RAG architectures and context engineering.
• Familiarity with diverse LLM provider APIs and agent integration.
• Experience experimenting with frontier AI tools and products.
• Cloud technologies: AWS, Docker, Kubernetes, CI/CD.
• Infrastructure as code: Terraform.
• Background in financial market infrastructure or derivatives industry.
• Experience working in regulated environments.