AI Engineer

Job Summary

We are seeking an AI Engineer with hands-on experience in large language models (LLMs), generative AI systems, and applied natural language processing (NLP) specifically for healthcare use cases. This role will focus on building, integrating, optimizing, and evaluating AI models and pipelines, ensuring accuracy, scalability, and compliance in regulated healthcare environments.

Responsibilities

• AI Model Development & Optimization: Design, build, and optimize LLM/SLM-powered AI systems for healthcare applications, developing and refining model interaction layers (prompting, orchestration, retrieval, and reasoning pipelines).
• LLM Training, Fine-Tuning & Customization: Collaborate with Machine Learning (ML) and NLP teams to fine-tune and adapt LLMs and SLMs for domain-specific healthcare tasks, assisting in data curation, augmentation, preprocessing, and evaluation to enhance model performance.
• Generative & Conversational AI Systems: Build AI-driven workflows for healthcare conversations, summarization, decision support, and automation while ensuring conversational outputs meet clinical relevance, compliance, and safety standards.
• Evaluation, Monitoring & Continuous Improvement: Define and implement evaluation metrics and testing frameworks to measure AI system performance, conducting A/B testing and monitoring for iterative improvement based on real-world usage.
• Collaboration & Research: Work closely with healthcare professionals, product teams, data engineers, and software engineers, staying updated with advancements in LLMs, generative AI, NLP, and applied AI research, while translating insights into scalable, production-ready AI solutions.

Qualifications

• Bachelor's or Master's degree in Computer Science, AI, NLP, Data Science, or a related field.
• 2+ years of experience in AI engineering, NLP, generative AI, or LLM-based systems.
• Experience working with AI solutions in regulated industries (healthcare preferred).
• Strong portfolio of AI-driven projects demonstrating real-world impact.
• Relevant certifications (AWS/GCP AI, ML, or Generative AI) are a plus.
• Hands-on experience with generative AI & LLMs, particularly with GPT models, LLaMA, or other open/closed-source LLM architectures.
• Proficiency in Python, with experience using frameworks such as LangChain and Transformers.
• Strong understanding of NLP concepts such as semantic search, intent recognition, contextual AI, and Retrieval-Augmented Generation (RAG).