Senior Software Engineer, AI

Practice by Numbers; Gurugram District; On-site; INR 1,800,000 - 2,400,000; Full time

Job summary

Practice by Numbers is seeking a Senior Software Engineer to own backend services and AI components for the AI Receptionist, working on multi-channel interfaces with HIPAA constraints. Location is Gurugram, India, with in-office work and occasional overlap with US teams.

You will design APIs with Python (FastAPI/Django), leverage PostgreSQL, Redis, and integrate with practice management systems. A focus on reliability and end-to-end ownership is essential.

Qualifications

• 4+ years of professional software development experience.
• Hands-on experience building backend services and APIs in production.
• Experience with LLM-based applications and prompt design.
• Debugging and improving a system after shipping.

Responsibilities

• Build and maintain backend services and RESTful APIs using Python.
• Design schemas; optimize PostgreSQL queries and caching with Redis.
• Work with async patterns and event-driven architectures.
• Own operational aspects: logging, metrics, alerts, production debugging.
• Develop AI features for the conversational AI receptionist and integrations.
• Collaborate with Product Management and US stakeholders; write docs.

Skills

Python

APIs & Backend

LLM / AI systems

Debugging production systems

Tools

FastAPI

Django

PostgreSQL

Redis

Webhooks

AWS

Job description

Practice by Numbers (PBN) | Gurugram, India Scope: 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.

About The Role

We're looking for a Senior 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

• Own the conversation layer for real‑time voice — turn‑taking, barge‑in, and recovery when the agent talks over a caller or stalls mid‑turn
• Debug non‑deterministic failures in production: fabricated confirmations, invented practice policies, dropped context across turns
• Own patient identity resolution over the phone — misheard and misspelled names, shared phone numbers, multi‑algorithm phonetic matching
• Version prompts and tool schemas like code: canary changes, measure impact, roll back regressions
• Own the eval and regression suite — golden conversation sets, replay of production calls, CI gating on prompt and model changes
• Design guardrails for patient‑facing interactions: no medical advice, no unverified data disclosure, tool‑call authorization, PHI excluded from logs and traces, escalation to a human when the agent should stop
• Own the model and voice vendor abstraction so a provider change is configuration, not a rewrite
• Keep voice, SMS, and web chat consistent — shared state and knowledge base, channel‑appropriate behaviour

Integrations & Data

• Integrate with practice management systems (Dentrix, Open Dental, Eaglesoft) and internal PBN APIs
• Implement secure auth flows, including OTP‑based patient verification
• Define SLOs for conversation success and turn latency; own incident response and postmortems for this surface

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

• 4+ 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

• Shipped an LLM system to real users and debugged it in production; can describe a failure mode you found and fixed
• Specific view of what current models are unreliable at, and how that shapes what runs unsupervised versus behind a tool call or human review
• Multi‑turn conversation design — state that survives interruptions, topic switches, and mid‑call corrections
• Experience measuring LLM systems: offline evals, judge model calibration, or production quality metrics
• Working knowledge of token cost and latency trade‑offs, including where streaming helps and where it adds complexity

Soft Skills

• Frame the problem, not just solve it; write down architectural decisions and the tradeoffs you rejected
• 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 skippingthem
• Healthcare / HIPAA compliance knowledge
• SaaS or B2B product company background; multi‑tenant architecture