Lead Software Engineer

Overview

Lead Software Engineer – Agentic AI (Healthcare SaaS | Dental Tech)

Compensation: 40–60+ LPA

Location: Gurugram, India

About the Company

Comprehensive dental practice management platform used by clinics to run operations end-to-end—scheduling, patient records, billing, reporting, and marketing automation.

Their mission is to help dental teams operate more efficiently and deliver better patient care through integrated workflows and data-driven insights.

The Opportunity

• Lead the build of greenfield conversational AI products—starting with a chatbot automating thousands of patient conversations daily.
• Own and scale additional agentic AI initiatives as the platform expands.

What You’ll Do

• Lead end-to-end development of patient-facing conversational AI (chat + voice), from build to production scale.
• Define architecture and technical strategy for LLM/agentic features across the platform.
• Build conversation orchestration (LangChain/LlamaIndex or custom), including multi-turn state, context retention, routing, and fallbacks.
• Optimize response quality, latency, and cost; implement evaluation, monitoring, and continuous improvement loops.
• Design guardrails and safety mechanisms for healthcare interactions (policy checks, escalation paths, safe prompting).
• Integrate with dental practice management systems (e.g., Dentrix, Open Dental, Eaglesoft) and internal services for real-time workflows.
• Ship secure, scalable services: APIs, authentication/verification (including MFA), data handling, observability, and reliability.
• Mentor engineers, conduct code reviews, raise engineering standards, and partner closely with Product and US stakeholders.

Must-Have

• 7+ years software engineering experience; 2+ years building and deploying AI/ML systems in production.
• Proven track record shipping products from concept → launch → scale.
• Hands-on experience building LLM applications in production (e.g., GPT-4/Claude or equivalent).
• Strong Python proficiency; experience with LLM frameworks (LangChain, LlamaIndex, or similar).
• Experience with conversational or real-time systems (chatbots, voice assistants, event-driven workflows).
• Strong backend fundamentals: REST APIs, webhooks, third-party integrations.
• Cloud experience (AWS/GCP/Azure) and common services (compute, storage, managed databases).
• Datastore experience for state/context (e.g., PostgreSQL, MongoDB) and session/state management patterns.
• Practical knowledge of RAG, prompt engineering, agentic patterns, and model evaluation/monitoring.
• Ability to work independently, drive execution in ambiguity, and communicate with technical/non-technical stakeholders.

Nice-to-Have

• Voice AI + telephony integrations (Twilio/Vonage) and/or STT/TTS providers (Deepgram/ElevenLabs/AssemblyAI).
• Exposure to healthcare compliance/security practices (HIPAA familiarity).
• Observability tooling (Datadog/New Relic/Sentry).
• SaaS/B2B experience, multi-tenant architecture, enterprise integrations.
• Open-source contributions or active involvement in the AI builder community.