Design and develop a developer-first Agent SDK (libraries, templates, reference implementations).

Implement the platforms MCP (Model Context Protocol).

Build reusable MCP servers or MCP-compatible connectors.

Develop platform-grade RAG components.

Build an evaluation and reliability framework covering offline evaluations, regression testing for prompts and tools, quality metrics, and drift detection.

Collaborate with backend and platform engineering teams to integrate agent services into broader platform pillars such as APIs, integration frameworks, audit frameworks, and security controls.

Solid hands-on expertise in Python, which is the primary language for agent and LLM development.

Experience building microservices and APIs, authentication mechanisms, and integration services.

Practical understanding of MCP concepts, including exposing tools and resources via MCP servers and consuming them from agent runtimes. Retrieval, RAG, and Data

Experience building microservices and APIs, authentication mechanisms, and integration services.

Experience designing and implementing RAG pipelines with vector databases, embeddings, retrieval strategies, and grounding techniques. Cloud, DevOps, and Platform

📌 Agentic AI + Gen AI+AI/ML Expert (Bengaluru)
🏢 ARCIS e Services
📍 Bengaluru