Teams at eka.care

Own the vision and roadmap for AI products embedded in clinical workflows. Partner with data scientists, AI engineers, and designers on model selection, prompting, retrieval, speech, tools, and agent orchestration. Define product quality evaluations, safety guardrails, and trust metrics. Translate clinical problems into product behaviors, lead enterprise and government deployments, and manage client engagements. The role requires AI product management experience, technical API and SDK fluency, and strong judgment around healthcare AI safety.

Develop and post-train large language models for safe, instruction-following clinical applications across Indian languages. Responsibilities include designing SFT and preference-optimization datasets, training reward models, building physician-guided reinforcement-learning loops, creating healthcare tool-use data, and conducting evaluations, error analysis, ablations, and red-teaming. Requires production experience with open-weight models, post-training frameworks, Python, distributed training, and strong empirical practices.

Build scalable backend systems, microservices, APIs, and data pipelines while integrating LLM-powered features and agentic workflows. Develop RAG systems using vector databases and embeddings, implement tool-calling and agent memory, and create evaluation frameworks for model quality, cost, and latency. The role also involves system optimization, testing, experimentation, and collaboration with product and frontend teams.