Python Developer

Role Objective

We are looking for a heavy-hitting Backend Developer to architect the next generation of our AI ecosystem. You won't just be "using" LLMs; you will be building the infrastructure that allows them to communicate, use tools, and interact with enterprise data using the

Model Context Protocol (MCP)

and

Multi-Agent Orchestration

.

Key Responsibilities

• Architect MCP Infrastructure:

Design and implement production-ready

MCP Servers and

Clients to standardize how our AI models interact with secure data sources and local tools.

• High-Performance Backend:

Build and optimize asynchronous APIs using

Python (3.11+)

and

FastAPI

, ensuring sub-100ms latency for real-time agentic workflows.

• Agentic Orchestration:

Develop intelligent routing systems, tool-calling logic, and "Agent-to-Agent" (A2A) communication patterns using frameworks like

LangGraph or

CrewAI

.

• Production MLOps:

Deploy scalable AI services on

AWS (EKS/Lambda)

using

Docker and

Kubernetes

, ensuring robust

CI/CD pipelines and monitoring.

• Data Strategy:

Implement Advanced

RAG (Retrieval-Augmented Generation)

pipelines involving hybrid search, semantic chunking, and vector databases (Qdrant/Pinecone/Milvus).

Technical Skill Set

• Core Backend:

Expert-level

Python

(AsyncIO, Type Hinting, Pydantic) and

FastAPI

.

• AI Standards:

Hands-on experience with

Model Context Protocol (MCP)

and

LLM Orchestration

.

• Cloud & DevOps:

Strong proficiency in

AWS services,

Docker

,

Kubernetes

, and

Terraform/Ansible

.

• Database & Search:

Experience with

PostgreSQL

,

Redis

, and

Vector Databases

.

• Messaging:

Familiarity with event-driven architectures using

Kafka

,

RabbitMQ

, or

Celery

.

Preferred Qualifications

• Contributed to open-source AI projects or built custom MCP servers.
• Deep understanding of

LLM Evaluation

(DeepEval/Ragas) and observability.

• Experience in high-compliance domains (Fintech/Healthcare) is a plus.