Principal Software Engineer – AI

Principal Software Engineer – AI

Requirements

• 12+ years of experience in software development.
• Expertise in Python, Java, SQL, and AI/ML frameworks (PyTorch, TensorFlow, Keras, Scikit-learn).
• Proven experience fine-tuning LLMs, developing RAG systems, and working with Generative AI.
• 8+ years of hands-on experience deploying ML models in production using AWS SageMaker, Bedrock, or similar cloud AI platforms.
• Strong background in task automation, workflow optimization, and real-time AI applications.
• Deep expertise in cloud computing (AWS) and MLOps best practices.
• Strong problem-solving skills with a strategic mindset for AI adoption and innovation.

Responsibilities

• Develop and execute a strategic roadmap for AI-driven lab operations optimization.
• Identify and implement Generative AI and deep learning models for automating and enhancing lab workflows.
• Lead research and prototyping efforts in Retrieval-Augmented Generation (RAG), prompt engineering, and fine-tuning LLMs (Large Language Models).
• Guide AI-driven solutions for task list generation, workflow guidance, and intelligent lab automation.
• Stay at the forefront of AI advancements, assessing emerging technologies for their practical application in lab operations.
• Architect and optimize Generative AI solutions leveraging AWS Bedrock, SageMaker, and ML frameworks (PyTorch, TensorFlow, Scikit-learn).
• Develop and fine-tune custom LLMs to enhance workflow automation and decision support.
• Build real-time AI-powered applications to provide contextual recommendations and predictive insights in lab environments.
• Ensure scalability, security, and efficiency of AI/ML models for high-throughput lab operations.
• Implement MLOps best practices, including automated model training, validation, and deployment pipelines.
• Design full-stack AI-driven applications that integrate workflow automation, task management, and decision support.
• Develop interactive dashboards and AI-driven user interfaces that enhance lab efficiency.
• Implement AI-powered guidance tools that assist lab personnel in navigating complex workflows.
• Work on backend AI services and front-end applications to deliver seamless AI-driven experiences.
• Work closely with data scientists, software engineers, and lab personnel to define and execute AI solutions.
• Lead internal and external teams in the development and deployment of Generative AI applications.
• Educate technical and business leaders on AI/ML capabilities and strategic applications.
• Advocate for and implement responsible AI practices, ensuring compliance with regulatory requirements.

Preferred Qualifications

• Experience with custom LIMS/LES development and AI-driven lab automation.
• Familiarity with regulatory compliance and security standards in healthcare and life sciences.