About this role
AI Software Engineer Practice by Numbers (PBN) | Gurugram, India S cope: AI / Conversational Products & Backend Services About Practice by Numbers Practice by Numbers is a dental practice management SaaS platform serving over 1,500 practices across North America — practice management software, VOIP, payment processing, and analytics. We're now expanding into AI-powered automation, building conversational AI products that change how practices interact with their patients. About the Role We’re looking for a Software Engineer with strong, hands-on experience in both backend product engineering and modern AI systems. The ideal candidate can design and build reliable, production-grade services while also developing, integrating, and deploying AI-powered capabilities. As this is a single opening on a small team, we need someone who can take end-to-end ownership across both areas and contribute independently throughout the product development lifecycle. You'll work on our AI Receptionist — a multi-channel conversational AI (voice, SMS, web chat) for dental practices — and the backend services, APIs, and integrations behind it. Hands-on IC role: you own features end to end, including their production behaviour. Real patient-facing traffic under HIPAA constraints, where correctness and latency both matter. Reports to: Lead Engineer — AI Location: Gurugram, India — this role is open in Gurugram only Work Mode: In-office Working Hours: Primarily IST (10 AM – 5 PM), with some evening overlap with US teams (until 9–11 PM IST) as needed What You'll Do Backend ● Build and maintain backend services and RESTful APIs in Python (FastAPI / Django) ● Design schemas and write efficient PostgreSQL queries; use Redis for caching and session state ● Work with async and event-driven patterns — queues, webhooks, WebSockets, background workers ● Own the operational side: logging, metrics, alerting, debugging production issues ● Write unit and integration tests for the business logic you ship AI & LLM ● Build and iterate on LLM-driven conversation flows: tool calling, multi-turn state, context handling ● Write and refine prompts for specific use cases, and measure the impact of changes ● Build guardrails for patient-facing interactions — no medical advice, no unverified data disclosure ● Work with RAG and knowledge-base retrieval for practice-specific questions ● Contribute to evaluation and regression testing so AI quality doesn't drift between releases ● Balance response quality, latency, and cost across LLM and voice vendors Integrations & Data ● Integrate with practice management systems (Dentrix, Open Dental, Eaglesoft) and internal PBN APIs ● Implement secure auth flows, including OTP-based patient verification ● Follow HIPAA-compliant practices across data handling, logging, and storage Collaboration ● Work with Product Management to turn requirements into working software, surfacing edge cases early ● Participate in sprint planning, standups, code reviews, and product reviews ● Document what you build; collaborate across time zones with US-based stakeholders Required Qualifications Experience ● 2–6 years of professional software development experience ● Hands-on experience building backend services and APIs that ran in production ● Practical experience with LLM-based applications (GPT-4/4o, Claude, or similar) — prompt design, tool calling, handling model output in real systems. Substantial personal or open-source work counts; tutorial-level does not. ● Experience debugging and improving a system after it shipped Technical Skills ● Strong Python — our primary language across AI and backend ● APIs: RESTful services, webhooks, third-party integrations; FastAPI or Django preferred ● Databases: PostgreSQL — schema design, indexing, query performance; Redis or similar ● Async Python (asyncio) and event-driven architectures ● Cloud: working knowledge of AWS (or GCP/Azure) — compute, storage, managed DBs, queues ● Version control, code review, and CI/CD as normal parts of your workflow AI Domain Understanding ● Clear view of what LLMs can and cannot do reliably, and how that shapes product design ● Prompt engineering and conversation design for multi-turn interactions ● Familiarity with RAG and agentic patterns — tool use, orchestration ● Some experience evaluating and monitoring LLM systems ● Awareness of token cost and latency trade-offs Soft Skills ● Comfort with ambiguity — you can make a reasonable call and explain it ● Clear communication with technical and non-technical stakeholders ● Able to drive your own work to completion without close supervision ● Comfortable with a fast pace and evolving requirements ● Willing to work in-office in Gurugram and overlap with US hours when needed Preferred Experience & Skills ● Conversational AI — chatbots, voice assistants, or IVR ● Voice/telephony (Twilio, Vonage) or STT/TTS APIs (Deepgram, ElevenLabs, AssemblyAI) ● LLM orchestration frameworks (LangChain, LlamaIndex) — or a considered view on skipping them ● Healthcare / HIPAA compliance knowledge ● Observability tools (Datadog, New Relic, Sentry, Papertrail) ● Celery or similar task queues; AWS SQS or equivalent ● SaaS or B2B product company background; multi-tenant architecture ● Open-source contributions