AI Engineer – AI Agents (Healthcare)

Build, curate, and maintain agentic workflows along with datasets for training and evaluation. Run systematic LLM evaluations, track regressions, and ensure models meet quality bars. Define and implement LLM performance metrics(e.g., correctness, latency, hallucination control, safety). Work closely with Product and Customer-facing teams, experiment with prompting techniques, fine-tuning datasets, retrieval strategies, and model configurations and ensure agent behaviour aligns with user expectations. Develop internal tooling to speed up evaluation, annotation, and iteration cycles. Build automated pipelines for regression checks and model monitoring. Create mechanisms that turn real user interactions into actionable model improvements. Ensure agents behave consistently across large-scale production scenarios. Debug complex system behaviours spanning prompts, tools, APIs, and model responses. To understand real-world use cases and failure modes. Translate customer insights into model needs, data requirements, and product improvements. Tune latency, turn-taking, and conversational naturalness for voice AI systems. Write clean, reliable code in Python or JS for model pipelines, tools, and integrations. Think in systems: from data ingestion to model outputs to user-facing behaviour.