As a Lead Software Engineer, you champion the technical vision for AI-powered products that transform patient interactions in dental practices. You architect and deliver greenfield conversational AI solutions, starting with a chatbot that automates thousands of healthcare conversations each day. As the platform grows, you own additional AI initiatives and shape the future of automation in dental practice management.
Responsibilities:
- Lead the technical development of conversational AI chatbots from the current phase through production scale.
- Own additional AI products and initiatives as they emerge in the product roadmap.
- Define technical strategy and architecture for AI-powered features across the platform.
- Drive innovation in AI applications for healthcare and practice management.
- Design and implement scalable AI conversation systems for voice and chat across multiple channels.
- Architect LLM integration strategies that balance response quality, latency, and cost.
- Build robust conversation orchestration using frameworks such as LangChain or custom solutions.
- Ensure system reliability, observability, and performance monitoring at scale.
- Design multi-turn conversation flows with state management and context retention.
- Implement prompt-engineering strategies for diverse business use cases.
- Fine-tune LLM behavior for healthcare-specific applications.
- Build guardrails and safety mechanisms for patient-facing interactions.
- Integrate with practice management systems (e. g., Dentrix, Open Dental, Eaglesoft) for real-time data sync.
- Implement secure authentication systems, including multi-factor verification.
- Build RESTful APIs for dashboards and system integrations.
- Ensure HIPAA compliance across all data handling and storage.
- Provide technical mentorship to junior developers and conduct code reviews.
- Work closely with product management to translate requirements into technical specifications.
- Participate in sprint planning, daily stand-ups, and product reviews.
- Contribute to technical documentation and drive engineering best practices.
- Collaborate effectively across time zones with US-based stakeholders.
Requirements:
- 7+ years of software development experience with progressive responsibility.
- 2+ years building and deploying AI/ML systems in production.
- Track record of shipping products that reached the market and scaled to significant user bases.
- Hands‑on experience with LLM‑based applications (e. g., GPT‑4 and Claude) in production.
- Background in real‑time systems or conversational AI (chatbots or voice assistants).
- Experience leading technical initiatives or mentoring development teams.
- Strong proficiency in Python for AI system development.
- Experience with LLM frameworks such as LangChain or LlamaIndex.
- API development skills: RESTful services, webhooks, and third‑party integrations.
- Experience with cloud platforms (AWS, GCP, or Azure) and services like Lambda, S3 and RDS.
- Database experience with PostgreSQL, MongoDB, or similar for conversation state management.
- Voice processing experience with STT/TTS APIs (Deepgram, ElevenLabs, AssemblyAI) or similar.
- Understanding of async programming, event‑driven architectures, and real‑time systems.
- Deep understanding of LLM capabilities and limitations.
- Practical experience with prompt engineering, agentic architecture, and conversation design.
- Knowledge of RAG (Retrieval‑Augmented Generation) patterns.
- Familiarity with model evaluation, testing, and monitoring.
- Ability to optimize costs for LLM‑based systems.
- Proven ability to lead projects from conception to production.
- Strong problem‑solving and analytical skills.
- Excellent communication with technical and non‑technical stakeholders.
- Ability to work independently and drive projects to completion.
- Comfortable in a fast‑paced startup environment with evolving requirements.
- Experience collaborating across time zones (US‑India preferred).
Nice to Have:
- Experience building voice AI systems or telephony integrations (Twilio, Vonage).
- Knowledge of healthcare/HIPAA compliance requirements.
- Background in NLP or speech recognition technologies.
- Familiarity with monitoring and observability tools (Datadog, New Relic, Sentry).
- Previous experience in SaaS or B2B product companies.
- Contributions to open‑source AI projects or an active presence in the AI community.
- Experience with multi‑tenant architecture and enterprise integrations.
- Track record of scaling products from early stage to growth.
- Bachelor's or master's degree from top‑rated institutions (IITs/IIMs or equivalent).
- Relevant certifications in AI or related fields.