Principal Generative AI (GenAI) Engineer

Overview

Velocity Clinical Research is an owned and integrated research site organization, providing excellence in patient care, high quality data and fully integrated research sites. At Velocity, we align our values and behaviors to give our employees the best chance of delivering on our brand promise: to bring innovative medical treatments to patients. We are committed to making clinical trials succeed by generating high quality data from as many patients as possible, as quickly as possible while providing exemplary patient care at every step.

As an employee of Velocity, you are the most integral part of our mission. For talented candidates who perform at a high level, Velocity will invest to support career advancement and reward performance. Whether you are new to clinical research or are an industry veteran, we invite you to apply to Velocity.

Benefits include medical, dental and vision insurance, paid time off and company holidays, 401(k) retirement plan with company-match, and an annual incentive program.

Job Summary:

As a Principal Generative AI (GenAI) Engineer, you will be at the forefront of developing and deploying advanced Generative AI solutions that drive innovation and business value. Your role will involve designing, optimizing, and implementing cutting-edge AI models and techniques, including Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG). You will work closely with cross-functional teams to integrate these technologies into our products and services, ensuring they meet both performance and business requirements. Your deep understanding of AI, coupled with your ability to stay current with the latest advancements, will be critical in shaping the future of our AI capabilities.  

Responsibilities

Duties/Responsibilities:

• Actively design, develop, and deploy advanced Generative AI applications, utilizing techniques such as prompt engineering and Retrieval-Augmented Generation (RAG).
• Collaborate closely with data scientists, ML engineers, and product teams to translate business requirements into scalable, production-ready GenAI applications.
• Experiment with and rigorously evaluate new Generative AI techniques and models, including LLMs and RAG, ensuring they meet high standards for performance, scalability, and ethical integrity.
• Explore and implement agentic frameworks and techniques, to develop AI systems capable of autonomous decision-making and task execution, pushing the boundaries of what's possible with GenAI.
• Stay at the forefront of Generative AI research, continuously integrating the latest advancements in LLMs, RAG, and related fields to enhance and evolve existing solutions.
• Optimize GenAI models for real-world deployment, balancing computational efficiency with high performance and accuracy.
• Seamlessly integrate GenAI models into production environments, ensuring robust operation, effective monitoring, and ongoing maintenance.
• Contribute to the development and refinement of best practices, coding standards, and guidelines specific to Generative AI technologies, with a focus on practical implementation, including prompt engineering.
• Participate in continuous learning and professional development to maintain expertise in AI/ML technologies and emerging trends.
• Contribute to innovation through patent filings, publications, and other forms of intellectual property generation related to Generative AI advancements

Qualifications

Required Skills/Abilities: 

• Deep understanding of machine learning algorithms, neural networks, and natural language processing (NLP).
• Expertise in working with state-of-the-art Generative AI models, including model fine-tuning, optimization, and deployment.
• Proficiency in prompt engineering to design and optimize prompts for Generative AI models, ensuring they produce high-quality and relevant outputs.
• Strong experience with Retrieval-Augmented Generation (RAG) techniques to enhance the capabilities of LLMs by integrating external knowledge sources.
• Proficiency in programming languages such as Python, TensorFlow, PyTorch, and other relevant AI/ML frameworks.
• Experience with data pre-processing, data augmentation, and handling large datasets.
• Familiarity with ethical considerations and bias mitigation strategies in AI model development.
• Strong software engineering skills, including experience with version control (Git), CI/CD pipelines, and cloud platforms (AWS, Azure, Google Cloud).
• Ability to build, deploy, and maintain scalable AI/ML pipelines that integrate Generative AI models and techniques like RAG.
• Experience with APIs and microservices architecture for integrating AI solutions into existing systems.
• Strong problem-solving skills, creativity, and a passion for innovation in the AI space.
• Excellent communication skills, with the ability to articulate complex technical concepts to both technical and non-technical stakeholders.
• Ability to mentor and guide junior engineers, fostering a culture of continuous learning and innovation.
• Proven track record of developing and deploying production-level AI/ML solutions.

Education and Experience:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field preferred.
• D. in AI, Machine Learning, or a related discipline preferred.
• 8 years of experience in software engineering, with at least 4 years focused on AI/ML strongly preferred
• Experience working specifically with Generative AI technologies and models.
• Experience working with Large Language Models (LLMs), including transformer-based architectures like GPT and BERT strongly preferred.

NOTE: The above Job Description is intended to communicate the general function of the mentioned position and by no means should be considered an exhaustive or complete outline of the specific tasks and functions that will be required.  Additionally, specific tasks and duties of the position are subject to change as the Company, the department and circumstances change.  All employees are expected to perform their duties within their ability as required by the job and/or as requested by management.