Assistant Manager

Job Summary

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.