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Job Description
The Role
Build scalable AI-powered backend systems that form the backbone of our client solutions.
You’ll architect robust APIs, integrate multiple AI providers with intelligent fallback strategies,
and optimize real-time workflows that handle AI processing at scale.
What You’ll Do
● Integrate and manage multiple AI providers (LLMs, image/video generation) with smart
fallback and cost optimization
● Design and optimize prompt engineering strategies for consistent, high-quality AI outputs
● Build high-performance REST/GraphQL APIs using Django and FastAPI with async
processing
● Develop real-time features using SSE, WebSockets, and background task processing
(Celery)
● Architect scalable microservices with robust error handling, rate limiting, and monitoring
● Optimize database queries, implement caching strategies, and design efficient data
models
● Implement RAG pipelines and vector embeddings for context-aware AI responses
● Write comprehensive tests, maintain CI/CD pipelines, and conduct code reviews
Job Requirements
Requirements:
- 5+ Years of Experience.
- Python & Frameworks: Django and/or FastAPI in production, async Python (asyncio,
async/await) - AI Integration: LLM APIs (OpenAI, Gemini, etc.), prompt engineering, token/cost
optimization - Databases: PostgreSQL (query optimization, indexing), Redis (caching, queuing)
Async Processing: Celery or equivalent, message brokers (RabbitMQ, Redis, SQS) - DevOps: Docker, Git, cloud platforms (AWS/GCP), CI/CD pipelines
- API Design: RESTful principles, authentication, rate limiting, error handling.
Tech Stack
Python 3.10+ | Django, FastAPI | PostgreSQL, Redis, MongoDB | OpenAI, Gemini | Celery |
Docker | AWS/GCP
Nice-to-Have
- Server-Sent Events (SSE) or WebSocket implementation
- Vector databases (Pinecone, Weaviate, pgvector) and RAG architectures
- MongoDB or NoSQL experience
- Multi-provider AI abstractions and failover strategies
- GraphQL, workflow orchestration (Temporal, Airflow), Kubernetes
- Observability tools (Datadog, Sentry, ELK)
- LangChain, LlamaIndex, or similar frameworks
