Principal Applied AI Engineer

This is a fully remote position, open to applicants in North America.

📋 Description

• Design effective AI solutions that empower product leaders and teams to accomplish their objectives.

• Act as the primary technical advisor for product and architecture leaders throughout the design and implementation of AI systems.

• Assist teams in developing and sustaining a reusable AI tools platform, which includes a central LLM client and evaluation harness.

• Assess when to implement cutting-edge LLMs, custom machine learning models, or conventional NLP techniques based on performance, cost, and efficiency.

• Spearhead the development of specialized ML models tailored for specific tasks.

• Supervise internal services as they transform into a central hub for LLM interactions.

• Develop and maintain a standardized LLM client featuring a unified API for OpenAI, Anthropic, and open-source models.

• Enhance reusable code libraries, tools, and validated prompts to expedite product team development.

• Standardize and advance the internal skills library for development purposes.

• Manage and improve the model evaluation harness for prototyping, A/B testing, and AI quality assessment.

• Oversee the AI gateway solution, which includes user support, configuration optimization, efficiency monitoring, and cost oversight.

• Provide leadership with reports on the value, ROI, and total cost of ownership of AI initiatives.

• Set and enforce best practices throughout the ML lifecycle, encompassing prompt engineering, data privacy, model safety, and MLOps.

⛳️ Requirements

• In-depth hands-on experience with contemporary LLM-based systems, including prompt engineering, RAG, fine-tuning, and agentic workflows.

• Significant hands-on experience with traditional machine learning, covering classification, regression, and NLP.

• Demonstrated experience in designing, constructing, and maintaining reusable software components, libraries, and APIs utilized by other engineering teams.

• Outstanding communication abilities and a talent for conveying complex technical trade-offs to both technical and non-technical stakeholders.

• Experience serving as an internal consultant or solutions architect is highly advantageous.

• Proven history of implementing systems to monitor performance, quality, and cost, along with using data to make informed decisions.

• Proficiency in AI systems, best practices for the ML lifecycle, data privacy, model safety, and MLOps.

🏝️ Benefits

• Annual target bonus.

• Comprehensive benefits package.

• Medical, Dental, Vision coverage.

• 401(k) plan.

• 401(k) matching.

• Unlimited planned paid time off.

• Global mental health support.

• On-demand learning and development opportunities.

• Quarterly paid volunteer days.

• Attractive employee referral program.

• Company-wide mentorship program.

• Career development opportunities.

• Promotion-from-within opportunities.