Senior Principal Engineer – AI Hardware Modeling

GAC Solutions; Pennsylvania; On-site; USD 120,000 - 150,000; Full time

Job summary

A leading AI solutions provider in the United States is seeking a GCP AI Engineer to design, architect, and scale enterprise-grade AI solutions on Google Cloud Platform. Responsibilities include architecting scalable AI/ML solutions, leading technical design reviews, and collaborating on AI research initiatives. The ideal candidate has strong GCP architecture expertise and hands-on experience with production LLMs, along with proficiency in tools like TensorFlow and PyTorch.

Qualifications

• Strong expertise in GCP architecture and AI services (Vertex AI, Cloud Storage, GKE).
• Hands-on experience scaling LLMs in production.
• Proficiency with TensorFlow, PyTorch, Hugging Face, OpenAI, and GCP integrations.
• Solid background in data preparation, personalization, and experimentation frameworks.
• Experience with enterprise AI systems and cloud-native design.

Responsibilities

• Architect and implement scalable AI/ML solutions on GCP (Vertex AI, GKE, BigQuery ML).
• Design and productionize LLM solutions, including RAG, prompt engineering, and RLHF.
• Lead technical design reviews and ensure best practices for security, performance, and scalability.
• Oversee model fine-tuning, deployment, A/B testing, and feedback-driven optimization.
• Collaborate on open-source initiatives and AI research where applicable.

Skills

GCP architecture

AI services (Vertex AI, Cloud Storage, GKE)

Scaling LLMs in production

TensorFlow

PyTorch

Hugging Face

OpenAI

Data preparation

Job description

We are seeking an experienced GCP AI Engineer to design, architect, and scale enterprise-grade AI solutions on Google Cloud Platform. The role focuses on building secure, high-performance AI/ML and LLM-based systems in production, while providing technical leadership and architectural guidance.

Key Responsibilities

• Architect and implement scalable AI/ML solutions on GCP (Vertex AI, GKE, BigQuery ML).
• Design and productionize LLM solutions, including RAG, prompt engineering, and RLHF.
• Lead technical design reviews and ensure best practices for security, performance, and scalability.
• Oversee model fine-tuning, deployment, A/B testing, and feedback-driven optimization.
• Collaborate on open-source initiatives and AI research where applicable.

Required Skills & Experience

• Strong expertise in GCP architecture and AI services (Vertex AI, Cloud Storage, GKE).
• Hands-on experience scaling LLMs in production.
• Proficiency with TensorFlow, PyTorch, Hugging Face, OpenAI, and GCP integrations.
• Solid background in data preparation, personalization, and experimentation frameworks.
• Experience with enterprise AI systems and cloud-native design.