Senior Advisor - AI Engineering

The Senior Advisor AI Engineering will be responsible for designing, developing, and deploying state-of-the-art generative AI solutions and pipelines across GCP, Azure, and AWS. This role requires expertise in prompt engineering, model fine-tuning, embeddings, and RAG pipelines. The ideal candidate will bring technical excellence, cloud expertise, and practical experience in production-grade AI deployments and delivery for product and business stakeholders.

• Design, develop, and deploy generative AI solutions using models such as Google Gemini, Azure OpenAI - GPT, or AWS Nova.  
• Build and maintain scalable AI pipelines including RAG pipelines, vector databases, and embedding models. 
• Conduct prompt engineering and implement best practices for model performance and usability. 
• Implement and optimize AI/ML workflows on cloud platforms: GCP (Vertex AI, Cloud Run, Pub/Sub, Observability), Azure, AWS. 
• Perform model fine-tuning, evaluations, and experimentation to improve generative AI outputs. 
• Collaborate with cross-functional teams to integrate AI solutions into applications and products. 
• Ensure technical excellence, scalability, and robustness in AI systems. 
• Stay up-to-date with emerging generative AI techniques and best practices.  

• Bachelor's or master's degree in computer science, Artificial Intelligence, Machine Learning, or related field. 
• 10+ years of professional experience in AI/ML with at least 2+ years focused on Generative AI. 
• Hands-on experience with cloud platforms: GCP - (Vertex AI, Cloud Run, Pub/Sub), Azure (OpenAI Service /Azure Foundry), or AWS Bedrock. 
• Expertise in prompt engineering, embeddings, RAG pipelines, and vector databases. 
• Strong Python programming skills and experience with ML frameworks (Hugging Face, PyTorch, TensorFlow). 
• Experience implementing AI pipelines, MLOps, and model lifecycle management in production environments. 
• Experience in model fine-tuning, optimization, evaluation, and deployment. 
• Strong understanding of machine learning concepts, data pipelines, and production-ready AI systems. 
• Proven ability to consult with business stakeholders to deliver effective, technically excellent, scalable AI solutions.  

• Familiarity with vector databases (Pinecone, Chroma) and RAG frameworks. 
• Familiarity with MLOps practices, CI/CD pipelines, and containerization (Docker/Kubernetes). 
• Strong presentation, communication, and stakeholder advisory skills. 
• Background in AI consulting, innovation labs, or R&D environments is a plus. 
• Experience in the healthcare domain.