GenAI Architect: LLMs, RAG & Enterprise AI

ApTask; New York (NY); On-site; USD 170,000 - 200,000; Full time

Job summary

ApTask is hiring a Principal GenAI Engineer in New York to lead enterprise-scale AI initiatives for Fortune 500 clients. The role centers on building RAG systems that combine structured semantic reasoning with advanced LLM architectures to deliver scalable, production-grade AI solutions.

You will mentor teams, drive code quality in Python and SQL, and collaborate with cross-functional stakeholders to deliver impactful GenAI products in a cloud environment (AWS/Azure/GCP).

Qualifications

• 8-13 years of experience in ML/AI systems.
• 2+ years hands-on experience with LLMs (RAG, agents, prompt engineering).
• Strong proficiency in Python, LangGraph, and SQL.

Responsibilities

• Develop and optimize LLM-based solutions: lead design and deployment of large language models, leveraging prompt engineering, retrieval-augmented generation (RAG), and agent-based architectures.
• Codebase ownership: build and maintain/review high-quality, efficient code in Python (LangChain/LangGraph) and SQL, focusing on reusable components, scalability, and performance.
• Cloud integration: assist in deployment of GenAI applications on cloud platforms (Azure, GCP, AWS), ensuring robust CI/CD processes.
• Cross-functional collaboration: work with product owners, data scientists, and business SMEs to define requirements and deliver AI products.
• Mentoring and guidance: provide technical leadership and knowledge-sharing to the engineering team.

Skills

ML/AI systems

LLMs

Python

LangGraph

SQL

Tools

AWS

Azure

GCP

LangChain

LangGraph

Job description

ApTask is hiring a Principal GenAI Engineer in New York to lead enterprise-scale AI initiatives for Fortune 500 clients. The role centers on building RAG systems that combine structured semantic reasoning with advanced LLM architectures to deliver scalable, production-grade AI solutions.

You will mentor teams, drive code quality in Python and SQL, and collaborate with cross-functional stakeholders to deliver impactful GenAI products in a cloud environment (AWS/Azure/GCP).