AI Engineer 4 (AI Foundations)

AI Engineer 4 (AI Foundations)

Overview

What You’ll Do

• Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.
• Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.
• Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.
• Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment
• Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift
• Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines
• Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met
• Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation

The Ideal Candidate

• Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production
• You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss
• You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown

Basic

Qualifications

• Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies
• At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java

Preferred

Qualifications

• Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy
• 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)
• Experience designing, developing, delivering, and supporting AI services
• Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang
• Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost
• Experience in building agentic AI systems and agentic workflows
• Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale
• Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules
• Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms

McLean, VA: $197,300 - $225,100 for AI Engineer 4

New York, NY: $215,200 - $245,600 for AI Engineer 4

San Jose, CA: $215,200 - $245,600 for AI Engineer 4