Senior Developer

2 weeks ago

Hubli, Karnataka, India beBeeBackend Full time ₹ 1,50,00,000 - ₹ 2,50,00,000

At Reckonsys Tech Labs, we are crafting innovative AI backends that combine Python engineering discipline with GenAI capabilities like tool orchestration, retrieval pipelines, and observability.

">Job Title

Generative AI Backend Engineer

Reckonsys is seeking a highly skilled and experienced Generative AI Backend Engineer to join our team. As a key member of our backend team, you will be responsible for architecting, implementing, and optimizing production-grade AI systems that work reliably in real-world environments.

The ideal candidate will have hands-on experience with Generative AI (GenAI), Model Context Protocol (MCP), Agent-to-Agent (A2A) workflows, and Retrieval-Augmented Generation (RAG). You will design and develop MCP servers to expose tools, resources, and APIs to Large Language Models (LLMs).

We are looking for someone who can implement RAG pipelines: text preprocessing, embeddings, chunking strategies, retrieval, re-ranking, and evaluation. Experience with integrating LLM APIs (OpenAI, Anthropic, Gemini, Mistral) and open-source models (Llama, MPT, Falcon) is also required.

Key Responsibilities:
  • Architect and implement AI backends using Python engineering principles.
  • Design and develop MCP servers to expose tools, resources, and APIs to Large Language Models (LLMs).
  • Implement RAG pipelines: text preprocessing, embeddings, chunking strategies, retrieval, re-ranking, and evaluation.
  • Integrate with LLM APIs (OpenAI, Anthropic, Gemini, Mistral) and open-source models (Llama, MPT, Falcon).
  • Optimize for latency, cost, and accuracy in real-world deployments.
Requirements:
  • 3–7 years professional experience with Python (3.9+).
  • Strong knowledge of Object-Oriented Programming (OOP), async programming, and REST API design.
  • Proven hands-on experience with RAG implementations and vector databases (Pinecone, Weaviate, FAISS, Qdrant, Milvus).
  • Familiarity with MCP (Model Context Protocol) concepts and hands-on experience with MCP server implementations.
  • Understanding of multi-agent workflows and orchestration libraries (LangGraph, AutoGen, CrewAI).
  • Proficiency with FastAPI/Django for backend development.
  • Comfort with Docker, GitHub Actions, CI/CD pipelines.
  • Practical experience with cloud infrastructure (AWS/GCP/Azure).
Nice-to-Have:
  • Exposure to AI observability & evaluation (LangSmith, PromptFoo, Ragas).
  • Contributions to open-source AI/ML or MCP projects.
  • Understanding of compliance/security frameworks (SOC-2, GDPR, HIPAA).
  • Prior work with custom embeddings, fine-tuning, or LLMOps stacks.

 

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