Junior Backend Developer; Python

Job Overview

We are looking for a highly capable Python & AI/ML with deep expertise in backend engineering, LLM-based applications, RAG architectures, and AI agent frameworks. You will lead the design, development, and deployment of production-grade AI systems built on Python, modern LLM tooling, retrieval engines, embeddings, and vector databases. This is a hands‑on leadership role focused on building scalable and intelligent AI products.

• Lead the architecture and development of LLM-driven applications, AI agents, and RAG-based systems.
• Provide technical guidance, conduct code reviews, and mentor junior team members.
• Drive best practices in Python backend engineering, API development, and AI system design.

• Build and maintain backend services using FastAPI or Flask.
• Develop scalable API endpoints for AI applications, embeddings, and retrieval systems.
• Ensure backend code quality, modularity, performance, and maintainability.

• Build AI applications using:
  Lang Chain, Lang Graph, Semantic Kernel, Haystack, Llama Index, Auto Gen.
• Develop autonomous or semi‑autonomous AI agents with tool calling and workflow graphs.
• Implement Retrieval‑Augmented Generation (RAG) pipelines, embedding pipelines, chunking strategies, reranking, and grounding techniques.
• Work with OpenAI SDK and other LLM providers (Anthropic, Azure OpenAI, Cohere, etc.).
• Manage prompt engineering, prompt routing, safety guardrails, and evaluation metrics.

• Build data pipelines for indexing, embeddings, and retrieval workflows.
• Work with SQL databases (PostgreSQL, MySQL, etc.) for metadata and application storage.

• Bachelor's/Master's degree in Computer Science, AI/ML, Data Science, or related fields.
• 8 to 10 years of experience in Python backend development.
• Strong proficiency in FastAPI or Flask.
• Strong working knowledge of SQL databases (Postgres, MySQL, etc.).
• Hands‑on expertise with vector databases:
  Redis, Postgres/pgvector, Elasticsearch, or Neo4j.
• Practical experience with FAISS for similarity search.
• Hands‑on experience with modern LLM frameworks:
  Lang Chain, Lang Graph, Semantic Kernel, Haystack, Llama Index, Auto Gen.
• Strong understanding of embeddings & vector search, RAG pipelines, retrieval optimization, chunking strategies, document loaders & indexing.
• Experience building AI apps using OpenAI SDK or similar.
• Experience deploying APIs/services using Docker and cloud environments.
• Leadership experience: guiding teams, conducting reviews, driving architecture decisions.

For applications and inquiries, contact: