AI Engineer - Conversational Agents (LLM)

@ Diagnostic Robotics

About Diagnostic Robotics

At Diagnostic Robotics, we’re building AI-driven voice and chat agents to empower healthcare providers, payers, and value-based care teams. Our technology predicts adverse health events, enables early intervention, and automates routine administrative tasks, ultimately reducing costs, easing provider burden, and improving patient outcomes.

Our conversational agents leverage state-of-the-art LLMs to interact naturally with patients and care teams, delivering real value at scale.

The Role: AI Engineer - Conversational Agents

We’re seeking a hands-on AI Engineer with research expertise and engineering experience to lead the development of the AI core of our conversational agents. You will own the end-to-end AI lifecycle from design and KPI definition, through model development, fine-tuning, evaluation, deployment, and continuous optimization in production.

Working in a fast-moving startup environment, you will collaborate closely with our engineering team to integrate advanced AI capabilities into our product.

Key Responsibilities

• Research & Innovation: Stay updated with LLMs, generative AI, and multi-agent systems; experiment with new methods.
• Prompt Engineering: Design, test, and optimize prompts; develop libraries and testing frameworks.
• Model Development & Optimization: Adapt LLMs for specific use cases; optimize speed, accuracy, and cost.
• Performance Measurement: Define KPIs and build evaluation frameworks to monitor agent performance.
• Engineering & Deployment: Design, implement, and maintain production-ready AI pipelines in Python (and optionally Node); handle data ingestion and product integration.

Must-Have Qualifications

• Master’s or PhD in Computer Science, AI/ML, Mathematics, or related field.
• 4+ years professional development experience in Python (Node.js is a plus).
• Proven applied research experience in LLMs, NLP, or conversational AI.
• Strong track record of deploying AI models to production with iterative improvements.
• Expertise in prompt engineering and multi-agent systems.
• Solid understanding of performance metrics and evaluation methodologies for AI agents.
• Excellent communication skills and collaborative aptitude.

Nice-to-Have

• Experience in cloud environments (AWS, GCP, Azure).
• Background in healthcare technology and compliance (HIPAA, HL7/FHIR).

Job Impact

Your work directly influences patient care and healthcare efficiency, while leading innovation in LLM-based conversational AI.

Key skills/competency

AI, LLM, Conversational AI, Prompt Engineering, Python, NLP, Deployment, Model Optimization, Healthcare, Research