Lead GenAI Engineer - Build Autonomous AI Agents at Scale

HighLevel; United States; Remote; USD 180,000 - 240,000; Full time

Job summary

HighLevel is seeking a seasoned Engineer to lead the development of LLM-powered AI agents and next-gen Generative AI systems that drive core product functionality and customer-facing automation at scale.

This role is high autonomy and high impact, blending applied AI, agent design, and data science to build foundational models, retrieval systems, and multi-step agents that interact with millions of users for personalized communication, scheduling, smart replies, and more.

Qualifications

• 8+ years in Data Science, ML, or Applied AI with production-grade models.
• Hands-on with LLMs: fine-tuning, prompt engineering, and function calling.
• Experience building retrieval augmented generation (RAG) with vector DBs.
• Proficient in Python with CI/CD, testing and versioning.
• Experience deploying models in cloud environments (GCP/AWS).

Responsibilities

• Architect and deploy autonomous AI agents for sales, messaging, scheduling, and ops.
• Build and fine-tune LLMs for HighLevel data and use cases.
• Develop robust RAG systems and vector search infrastructure.
• Design prompt strategies with LangChain and multi-step agents.
• Apply data science methods to improve agent intelligence and features.
• Collaborate with backend, infra, and product teams to build scalable GenAI infra.
• Monitor agent performance and iterate with rigorous experiments.
• Mentor engineers and contribute to technical standards.

Skills

LLM tuning

Prompt engineering

RAG systems

LangChain

Python engineering

Cloud-native

Vector databases

PyTorch/Transformers

Team leadership

Tools

FAISS

Pinecone

Weaviate

LangChain

PyTorch

Transformers

Job description

HighLevel is seeking a seasoned Engineer to lead the development of LLM-powered AI agents and next-gen Generative AI systems that drive core product functionality and customer-facing automation at scale.

This role is high autonomy and high impact, blending applied AI, agent design, and data science to build foundational models, retrieval systems, and multi-step agents that interact with millions of users for personalized communication, scheduling, smart replies, and more.