AI Architect - LLM Models

Description :

• Lead architecture, design, and implementation of LLM-based and agentic AI systems for clinical and operational use cases.
• Oversee the development of multi-agent orchestration frameworks (reasoning, planning, and task execution) using tools such as LangGraph, CrewAI, or Semantic Kernel.
• Build scalable RAG pipelines and retrieval systems using vector databases (Pinecone, FAISS, Weaviate, Vertex AI Matching Engine).
• Guide engineers on prompt design, model evaluation, multi-step orchestration, and hallucination control.
• Collaborate with product managers, data engineers, and designers to align AI architecture with business goals.
• Manage end-to-end AI lifecycle data ingestion, fine-tuning, evaluation, deployment, and monitoring on Vertex AI / AWS Bedrock / Azure OpenAI.
• Lead scrum ceremonies, sprint planning, and backlog prioritisation for the AI team.
• Work directly with external stakeholders and customer teams to understand requirements, gather feedback, and translate insights into scalable AI solutions.
• Ensure compliance with HIPAA, PHI safety, and responsible AI governance practices.
• Contribute to hiring, mentoring, and upskilling the AI engineering :
• Deep expertise in LLMs, RAG, and Agentic AI architectures, including multi-agent planning and task Hands-on experience with LangChain, LangGraph, CrewAI, or Semantic Kernel.
• Strong proficiency in Python, cloud-native systems, and microservice-based deployments.
• Proven track record of leading AI projects from concept to production, including performance optimisation and monitoring.
• Experience working with healthcare data models (FHIR, HL7 clinical notes) or similar regulated domains.
• Experience leading agile / scrum teams, with strong sprint planning and delivery discipline.
• Excellent communication and collaboration skills for customer-facing discussions, technical

presentations, and cross-team coordination.

(ref : hirist.tech)