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
Experience
Required Qualifications
- 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
