AI Application Engineer

Job Title:- AI Application EngineerExperience:- 5+ yearLocation:- RemoteTiming:- 3pm - 12amAbout the roleWe’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 ship features end-to-end: Django-based backends, real-time agent infra (Live Kit + Deep gram), and LLM integrations (API and self-hosted). Great for someone with solid Python fundamentals plus side projects in AI/agents.What you’ll doBuild backend services in Python/Django (REST/WebSocket endpoints, auth, RBAC).Implement agent flows that combine Live Kit (real-time media), Deep gram (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 (or similar): blue-green deploys, background workers, cron jobs, service health checks, environment variables/secrets.Write tests, logs, and metrics; add basic observability(Prometheus/Open Telemetry, Sentry).Document endpoints, flows, and runbooks.Nice to have (you’ll learn here if you don’t know all yet)Lang Chain/Llama Index, 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 (build C start commands, service dependencies, health checks, persistent disks).Security hygiene: OAuth2, JWT, signed webhooks, PII handling, rate limits. Minimum qualifications~5 year experience with Python and Django/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 herePython 3.11+, Django/DRF, FastAPI (selective), Celery, Redis, Postgres, Web Sockets, Live Kit, Deep gram, LLMs (OpenAI/Anthropic/Mistral/Azure), self-hosted (Ollama/vLLM), vector DB (pgvector/Qdrant), LangChain/Llama Index, Kafka (nice), , Docker, GitHub Actions, 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—Live Kit + Deep gram + 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.

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