Principal Artificial Intelligence Engineer

Job Description

***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, AI Engineering to help define and execute on the company AI technical roadmap
• Lead and partner on the architecture of scalable systems incorporating LLMs and AI into organizational processes and infrastructure
• Provide technical mentorship to junior engineers on engineering best practices and system design
• Conduct code/architectural reviews ensuring production readiness, safety, and adherence to high security and compliance standards
• Implement testing, evaluation, and monitoring frameworks for AI systems including hallucination detection and bias assessment
• Establish safety guardrails and responsible AI practices for LLM applications in a regulated environment
• Connect AI agents to organizational systems and workflows
• Foster continuous learning culture in a rapidly evolving AI landscape

Qualifications:

• Bachelor's or Master's in Computer Science or related technical field
• 10+ years software engineering/systems architecture experience with strong technical leadership
• 5+ years as senior technical contributor on complex production systems
• Expert in Python and proficient in SQL
• System design expertise: monolithic and microservice architectures, distributed systems, event-driven architectures, APIs
• Hands-on experience in data (e.g., data engineering, data pipelines, data transformation)
• Foundational experience with LLMs and familiarity with multiple frontier lab models (e.g., Gemini, Claude, GPT)
• Familiarity of risk vectors in AI applications including hallucinations, bias, prompt injection, data privacy
• Production experience with AI applications or LLM-powered systems
• Experience with RAG architectures and context engineering
• Familiarity with diverse LLM provider APIs and experience connecting agents to systems
• Experience tinkering with frontier lab tools and products
• Cloud platforms/technologies: AWS, Docker, Kubernetes, CI/CD, Terraform