LLM Architect (Chennai)

The Role The LLM Architect will own Droidal's large language model strategy and architecture for RCM AI agent development. You'll design the AI reasoning layers that allow Droidal's agents to understand payer rules, interpret EOBs and remittance advice, classify denial reasons, generate prior authorization narratives, and make workflow decisions all in a production healthcare setting where accuracy and auditability are non-negotiable. This is not a research role. You'll be building production LLM systems that process real claims, make real decisions, and directly impact provider revenue. What You'll Do Architecture & Design - Define Droidal's LLM system architecture: model selection, fine-tuning strategy, RAG pipelines, prompt engineering standards, and agentic reasoning frameworks - Design multi-agent LLM architectures where agents collaborate to complete multi-step RCM workflows (e.g., eligibility authorization submission denial handling) - Architect retrieval-augmented generation (RAG) systems over RCM-specific knowledge bases: payer policies, CPT/ICD coding rules, prior authorization requirements, and denial categorization logic - Design prompt engineering standards and guardrails that ensure consistent, auditable, and hallucination-resistant outputs in clinical and billing contexts Production AI Systems - Build and own the LLM inference and orchestration layer integrating with Droidal's AgentFlow platform and backend Python services - Establish evaluation frameworks: automated evals, human review pipelines, and regression testing for LLM-powered workflows - Implement observability, logging, and audit trails for all LLM decisions critical for HIPAA compliance and customer trust - Define latency, cost, and accuracy trade-off frameworks for model selection and serving strategy Voice AI - Architect the language understanding and generation components of Droidal's Voice AI agents real-time speech-to-text, intent classification, dialogue management, a .