AI Software Engineer in Gurugram, Haryāna at Practice By Numbers

Practice by Numbers (PBN) | Gurugram, India S

cope: AI / Conversational Products & Backend Services

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.

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

● 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

● 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

● 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

● 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

● 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

● 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

● 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

● 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