Reckonsys Tech Labs - Python Developer - Generative AI

Key Responsibilities :

• Python Engineering
• Generative AI & RAG
• MCP (Model Context Protocol)
• Agent-to-Agent (A2A) Workflows
• Production & Observability

Required Skills & Qualifications :

37 years professional experience with Python (3.9+).

Strong knowledge of 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).

Add tracing, logging, and evaluation metrics (PromptFoo, LangSmith, Ragas).

Optimize for latency, cost, and accuracy in real-world deployments.

Deploy solutions using Docker, Kubernetes, and cloud platforms (AWS / GCP / Azure).

Design and implement multi-agent orchestration (e.g., AutoGen, CrewAI, LangGraph).

Build pipelines for agents to delegate tasks, exchange structured context, and collaborate.

Add observability, replay, and guardrails to A2A interactions.

Develop MCP servers to expose tools, resources, and APIs to LLMs.

Work with FastMCP SDK and design proper tool / resource decorators.

Ensure MCP servers follow best practices for discoverability, schema compliance, and security.

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).

Handle context-window optimization and fallback strategies for production workloads.

Build clean, modular, and scalable Python codebases using FastAPI / Django.

Implement APIs, microservices, and data pipelines to support AI use cases.

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.

What We Offer :

Opportunity to own core AI modules (MCP servers, RAG frameworks, A2A orchestration).

End-to-end involvement from architecture MVP production rollout.

A fast-moving, engineering-first culture where experimentation is encouraged.

Competitive compensation, flexible work setup, and strong career growth.

Location :

Bangalore (Hybrid) / Remote.

Experience Level :

3 7 years.

Compensation :

Competitive, based on expertise.

(ref : hirist.tech)