Principal GenAI Engineer

About Client

The client provides information technology (IT) services, including business outsourcing, infrastructure technology, and application services. The application service offered by the company includes application development, maintenance, and support. The markets served by the company are financial services and insurance, healthcare, manufacturing, government, transportation, communications, and consumer and retail industries.

Salary Range

$170K-$200K/Annum

Job Description

• Our Client is hiring a Principal GenAI Engineer with strong expertise in LLMs to lead enterprise-scale AI implementations for Fortune 500 clients.
• This role focuses on building RAG systems that combine structured semantic reasoning with advanced LLM architectures to deliver scalable, explainable, production-grade AI solutions.

Requirements

• 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
• Experience deploying GenAI systems on AWS / Azure / GCP

Roles & Responsibilities

• Develop and optimize LLM-based solutions: Lead the design and deployment of large language models, leveraging techniques like prompt engineering, retrieval-augmented generation (RAG), and agent-based architectures.
• Codebase ownership: Build and maintain/review high-quality, efficient code in Python (using frameworks like LangChain/LangGraph) and SQL, focusing on reusable components, scalability, and performance best practices.
• Cloud integration: Aide in deployment of GenAI applications on cloud platforms (Azure, GCP, or AWS), optimizing resource usage and ensuring robust CI/CD processes.
• Cross-functional collaboration: Work closely with product owners, data scientists, and business SMEs to define project requirements, translate technical details, and deliver impactful AI products.
• Mentoring and guidance: Provide technical leadership and knowledge-sharing to the engineering team, fostering best practices in machine learning and large language model development.

Interview Requirements

Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government issued ID during each interview.

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