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)

Minimum qualifications

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