Senior Python Engineer

Key ResponsibilitiesBackend & API Development

• Design and develop high-performance backend systems using Python.
• Build scalable RESTful and GraphQL APIs (FastAPI preferred).
• Develop microservices and event-driven architectures to support high throughput.
• Implement asynchronous and concurrent processing systems using asyncio and Celery.

AI/ML Integration

• Integrate ML models into production environments via optimized pipelines.
• Build and maintain LLM-based applications, specifically focusing on RAG (Retrieval-Augmented Generation), embeddings, and prompt engineering.
• Work with LangChain, LlamaIndex, and OpenAI/Hugging Face APIs.
• Collaborate with AI/ML engineers to deploy and optimize automation engines and chatbots.

Data Engineering & System Design

• Design ETL pipelines for large-scale data processing of structured and unstructured datasets.
• Manage distributed systems handling millions of records daily, ensuring fault tolerance and scalability.
• Implement efficient caching (Redis), queuing (RabbitMQ/Kafka), and load-balancing strategies.
• Optimize database performance across PostgreSQL, MongoDB, and Vector Databases (Pinecone, Weaviate).

Required Skills & Experience

• Core Python: 3–4 years of experience with deep proficiency in OOP, data structures, and design patterns.
• Backend Frameworks: Hands-on experience with FastAPI, Django, or Flask.
• Modern AI Stack: Familiarity with TensorFlow/PyTorch and a strong grasp of the LLM ecosystem (RAG, Vector search).
• Cloud & Infrastructure: Proficiency in AWS (EC2, Lambda, S3, RDS) or similar cloud providers (Azure/GCP).
• Observability & Security: Experience with Prometheus/Grafana and securing APIs using OAuth2/JWT.
• Testing: Commitment to code quality using pytest, SonarQube, and pre-commit hooks.

Technical Environment

• Databases: PostgreSQL, MySQL, Redis, MongoDB, FAISS.
• Messaging: RabbitMQ, Kafka (Pub/Sub systems).
• DevOps: Docker, CI/CD, OpenTelemetry for tracing.

Work Location: In person