Principal Applied AI Engineer

Bullhorn

. Architect practical AI solutions that enable product leaders and teams to meet their goals .

Posted 9/29/2026full-timeRemoteLead💰 $175,000 - $200,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in architecting AI solutions, including LLM-based systems and traditional machine learning, while ensuring best practices in the ML lifecycle and effective communication with stakeholders.

Highest-signal resume keywords

LLM-Based SystemsPrompt EngineeringMachine Learning LifecycleReusable Software ComponentsAI Quality Measurement

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Prompt EngineeringRAGFine-TuningClassificationRegressionNatural Language ProcessingAPI DevelopmentModel EvaluationMLOpsData Privacy

Soft Skills

Exceptional Communication Skills

Tools & Technologies

OpenAIAnthropicEvaluation HarnessCentral LLM Client

Industry Keywords

AI SolutionsMachine LearningModel SafetyCost MonitoringPerformance Tracking

About the role

Key responsibilities & impact

Architect practical AI solutions that enable product leaders and teams to meet their goals
Serve as the primary technical consultant for product and architecture leaders during AI system design and implementation
Guide teams developing and maintaining a reusable AI tools platform, including a central LLM client and evaluation harness
Determine when to use frontier LLMs, bespoke machine learning models, or traditional NLP based on performance, cost, and speed
Lead development of dedicated and bespoke ML models for specialized tasks
Oversee internal services evolving into a central hub for LLM interactions
Create and maintain a standardized LLM client with a unified API for OpenAI, Anthropic, and open-source models
Expand reusable code libraries, tools, and vetted prompts to accelerate product team development
Standardize and improve the internal skills library for development
Own and enhance the model evaluation harness for prototyping, A/B testing, and AI quality measurement
Own the AI gateway solution, including user support, configuration refinement, efficiency monitoring, and cost monitoring
Report to leadership on AI initiative value, ROI, and total cost of ownership
Establish and govern best practices across the ML lifecycle, including prompt engineering, data privacy, model safety, and MLOps

Requirements

What you’ll need

Extensive hands-on experience with modern LLM-based systems, including prompt engineering, RAG, fine-tuning, and agentic workflows
Extensive hands-on experience with traditional machine learning, including classification, regression, and NLP
Proven experience designing, building, and maintaining reusable software components, libraries, and APIs used by other engineering teams
Exceptional communication skills and ability to explain complex technical trade-offs to technical and non-technical stakeholders
Experience acting as an internal consultant or solutions architect is highly desirable
Track record of implementing systems to track performance, quality, and cost and using data to make informed decisions
Expertise in AI systems, ML lifecycle best practices, data privacy, model safety, and MLOps

Benefits

Comp & perks

Annual target bonus
Comprehensive benefits package
Medical, Dental, Vision
401(k)
401(k) Match
Unlimited Planned Paid Time Off
Global Mental Health Support
On-Demand Learning & Development
Quarterly paid volunteer days
Lucrative Employee Referral Program
Company-wide mentor program
Career development opportunities
Promotion-from-within opportunities