Generative AI Engineer

Primary Responsibilities:

Apply advanced Generative AI techniques to build AI workflows

Design and implement scalable data pipelines and data transformation workflows to support AI/ML model development and deployment

Participate actively in the full AI lifecycle: contributing to brainstorming and conceptualization, rapid prototyping, experimentation, and writing high-quality, robust production code

Develop, fine-tune, and optimize Large Language Models (LLMs) for domain-specific use cases, including prompt engineering, few-shot learning, and model evaluation

Collaborate closely with product managers, designers, and other engineers to understand requirements, refine technical approaches, and deliver scalable, impactful AI solutions

Stay current with the latest advancements in AI/ML, LLMs, and Data Engineering, evaluate new technologies, and propose innovative ways to tackle healthcare challenges

Troubleshoot complex technical issues, identify root causes, and implement effective solutions in both development and production environments

Required Qualifications:

LLM Proficiency: Hands-on experience working with Large Language Models (e.g., GPT, LLaMA, Mistral), including prompt engineering, fine-tuning, and building RAG pipelines for enterprise-scale applications

Data Engineering Skills: Practical experience in designing and managing data pipelines, ETL/ELT workflows, and working with large-scale structured and unstructured datasets using tools such as Apache Spark, Databricks, Apache Airflow, or Azure Data Factory

Generative AI Frameworks: Demonstrated expertise in working with advanced Generative AI frameworks, LLMs, and RAG pipelines