AI Applications Engineer

Position: AI Applications Engineer

Experience: 4+Years

Timings: 3PM-12AM IST

Location: Remote

About the role

We’re building agentic AI apps for real business use—voice/chat agents that orchestrate workflows across CRMs/ERPs and internal tools. You’ll help us shipfeatures end-to- end: Django-based backends, real-time agent infra (LiveKit + Deepgram), and LLM integrations (API and self-hosted). Great for someone with solid Python fundamentals plus side projects in AI/agents.

What you’ll do

• Build backend services in

  Python/Django

  (REST/WebSocket endpoints, auth, RBAC).
• Implement agent flows that combine

  LiveKit

  (real-time media),

  Deepgram

  (ASR/TTS), and

  LLM APIs

  (OpenAI/Anthropic/Mistral/Azure).
• Integrate tools and data:

  PostgreSQL

  ,

  Redis

  , external SaaS (e.g., Salesforce/HubSpot/Zendesk) via APIs.
• Add job orchestration C background work:

  Celery/RQ

  , scheduled tasks, retries.
• Support

  self-hosted LLMs

  (Docker/Kubernetes) and vector search (e.g.,

  pgvector

  ,

  Qdrant

  , or

  FAISS

  ).
• Deploy and operate services on

  Render.com

  (or similar): blue-green deploys, background workers, cron jobs, service health checks, environment variables/secrets.
• Write tests, logs, and metrics; add basic

  observability

  (Prometheus/OpenTelemetry, Sentry).
• Document endpoints, flows, and runbooks.

Nice to have (you’ll learn here if you don’t know all yet)

• LangChain/LlamaIndex

  , function/tool calling, multi-step “agents”.
• Real-time comms basics:

  WebRTC

  , TURN/STUN, audio pipelines.
• Prompt engineering,

  RAG

  patterns, evals C guardrails (prompt libraries, regex/JSON schema validation).
• Frontend basics (React) to debug agent UIs.
• CI/CD on Render.com (build C start commands, service dependencies, health checks, persistent disks).
• Security hygiene: OAuth2, JWT, signed webhooks, PII handling, rate limits.

Minimum qualifications

• ~3 year experience (internships or personal projects count) with

  Python

  andDjango/FastAPI.
• You’ve shipped at least one project using an

  LLM

  (API or local) or a

  speech

  API.
• Comfortable with

  Git

  ,

  Docker

  ,

  PostgreSQL

  ,

  Redis

  , and basic

  Linux

  .
• Can read API docs and wire up third-party integrations quickly.
• Clear written communication; habit of small, tested PRs.

Tech stack you’ll touch here

Python 3.11+, Django/DRF, FastAPI (selective), Celery, Redis, Postgres, WebSockets, LiveKit, Deepgram, LLMs (OpenAI/Anthropic/Mistral/Azure), self-hosted (Ollama/vLLM), vectorDB (pgvector/Qdrant),LangChain/LlamaIndex, Kafka (nice), Render.com, Docker, GitHubActions, Sentry/OTel.

Example problems you might work on

• “Voice agent” that answers calls, verifies a customer, pulls order status from Django models, and schedules a return—

  LiveKit + Deepgram + tool-using LLM

  .

• RAG

  : ingest PDFs/emails from a shared inbox, chunk/embed, store in pgvector, expose a search+answer endpoint.

• Workflow

  : Celery pipeline to reconcile invoices nightly; retries with idempotency keys and alerting.