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Niche LLM specialization reduces pool, but Bangalore metro increases applicant density.
Requires specialized LLM, vector DB, and MLOps experience, limiting transferability across industries.
Multiple explicit years requirements and many mandatory LLM, backend, and MLOps technologies.
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Design, build, and maintain scalable backend systems and APIs using FastAPI, Python, and async programming.
Integrate and orchestrate LLM workflows and observability tools (Azure OpenAI GPT-4, LangChain, LangGraph, Langfuse).
Implement multi-tenant architectures with data isolation, prompt management, and troubleshoot using structured logging and tracing.
7+ years strong Python development experience with advanced async/await, type hints, Pydantic, and SOLID principles.
2+ years hands-on in machine learning and production Large Language Model (LLM) systems including LangChain and Azure OpenAI integration.
3+ years building backend APIs using FastAPI, async patterns, rate limiting, and SQLAlchemy.
Bachelor’s or Master’s degree in Computer Science or related field.
Experienced in designing extensible and maintainable backend systems using dependency injection, layered architectures, and abstract base classes.
Practical expertise in RAG architectures, vector databases (e.g., Pinecone, Weaviate), and NLP/Computer Vision domains including document understanding and OCR.
Capable of managing ML workflows, MLOps tools (MLflow, model versioning, A/B testing), and integrating cloud services with multi-tenant secure architectures.