AI Software Engineer
Practice by Numbers
Description
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
About Practice by Numbers
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