Assistant Manager

Darwinbox Digital Solutions Pvt. Ltd.; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Darwinbox Digital Solutions Pvt. Ltd. seeks an experienced AI Architect to lead the architecture, development, and scaling of enterprise-grade agentic AI solutions.

The role focuses on robust multi-agent systems using RAG, LangGraph, and MCP, integrated with enterprise apps for production readiness. You will mentor AI engineers, drive engineering best practices across the lifecycle, and collaborate with product and enterprise teams to ensure security, reliability, and observability while

Qualifications

• Experienced in architecting production-grade AI agents and multi-agent systems.
• Hands-on with RAG architectures, tool/calling, agent orchestration, APIs, and enterprise integrations.
• Cloud-native, secure, scalable, observable distributed systems.
• Experience leading technical teams, architecture/code reviews, and engineering best practices.

Responsibilities

• Architect and design enterprise-level agentic AI frameworks using RAG, LangGraph, MCP.
• Oversee end-to-end development of production-grade AI agents using Python for backend and React/Node.js for frontend.
• Integrate AI agents with enterprise systems, APIs and data platforms.
• Define and enforce best practices for AI development, CI/CD, DevOps, testing and deployment.
• Lead, mentor and upskill a team of AI professionals.
• Design for scalability, security, reliability, observability and performance.
• Establish governance and monitoring frameworks for AI agents.
• Stay current with Agentic AI developments and adoption opportunities.

Skills

Agentic AI Design

LLM/RAG Engineering

LangGraph

MCP

Python

React

Node.js

Enterprise Systems Integration

Cloud Architecture

CI/CD

DevOps

AI Evaluation & Monitoring

AI Governance

Job description

Lead the architecture, development, and scaling of enterprise-grade Agentic AI solutions. The primary focus is to design robust multi-agent systems using RAG, LangGraph, and MCP, integrated with enterprise applications and built for scalability, security, reliability, and production readiness. The role also involves leading and mentoring AI professionals while driving engineering best practices across the AI development lifecycle.

Roles and Responsibilities

• AI Architecture: Architect and design enterprise-level agentic AI frameworks using RAG, LangGraph, MCP (Model Context Protocol), and LLM-based technologies.
• Agent Development: Oversee the end-to-end development of production-grade AI agents using Python for backend services and React/Node.js for frontend applications.
• Enterprise Integration: Collaborate with Product, Engineering, and other cross-functional teams to integrate AI agents with enterprise systems, applications, APIs, and data platforms.
• Engineering & DevOps: Define and enforce best practices for AI development, including CI/CD, DevOps, testing, code reviews, deployment automation, and production readiness.
• Leadership & Mentoring: Lead, mentor, and upskill a team of AI professionals. Conduct technical design and code reviews while maintaining high engineering standards.
• Scalability, Security & Reliability: Design AI solutions that meet enterprise requirements for scalability, security, reliability, observability, and performance.
• AI Governance & Monitoring: Establish frameworks for AI agent evaluation, monitoring, performance measurement, governance, and continuous improvement.
• Innovation: Stay current with emerging developments in Agentic AI, LLMs, RAG, AI orchestration frameworks, and enterprise AI architecture, and identify opportunities to adopt relevant technologies.

Required Skills

• Agentic AI System Design, LLM/RAG Engineering, LangGraph, MCP, Python, React, Node.js, Enterprise Systems Integration, Cloud Architecture, CI/CD, DevOps, AI Evaluation & Monitoring, and AI Governance.
• Strong experience designing and building production-grade AI agents and multi-agent systems using modern LLM frameworks.
• Hands-on experience with RAG architectures, tool/function calling, agent orchestration, APIs, enterprise integrations, and LLM application development.
• Strong understanding of cloud-native architecture, security, scalability, observability, and distributed systems.
• Experience leading technical teams, conducting architecture/code reviews, and establishing engineering best practices is highly preferred.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status.