Principal Artificial Intelligence Engineer

Overview

Hybrid
$180,000 - $200,000
Full Time

Skills

AI
LLM
Python
SQL
Data engineering
APIs

Job Details

***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
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