Fullstack Engineer- WIth AI

Cummins; Pune District; Hybrid; INR 1,800,000 - 3,200,000; Full time

Job summary

Cummins is seeking a hands-on Full Stack AI Engineer to design, develop, and deploy enterprise-grade AI applications and reusable Agentic AI frameworks. The role combines full-stack development, AI engineering, framework development, and cloud-native architecture to build scalable AI solutions and enterprise AI platform capabilities.

The candidate will design end-to-end AI applications using React/Next.js, Python/Node.js, APIs and databases, and build agentic AI solutions with LLMs, RAG,

Qualifications

• 8–10 years of hands-on full-stack AI engineering experience.
• Experience designing and deploying enterprise-grade AI apps.
• Proficiency with cloud-native architectures.
• Strong React/Next.js, Python/Node.js, and databases skills.

Responsibilities

• Design and develop end-to-end AI applications using React/Next.js, Python/Node.js, APIs, and databases.
• Build agentic AI solutions using LLMs, RAG, multi-agent orchestration, tool calling, memory, and MCP.
• Design and develop reusable Agentic AI frameworks, SDKs, orchestration components, and developer accelerators.
• Build extensible agent architectures, reusable tools, connectors, integration adapters, and workflow templates.
• Implement framework-level capabilities including agent lifecycle management, state management, context handling, guardrails, evaluation, and observability.
• Develop secure enterprise integrations and scalable backend services.
• Implement cloud-native deployment, CI/CD, monitoring, and performance optimization on AWS/Azure.
• Drive solutions from PoC to production while ensuring reusability, maintainability, and enterprise standards.
• Collaborate with architects, developers, and stakeholders to establish AI engineering best practices.

Skills

React

Next.js

TypeScript

JavaScript

Python

Node.js

REST APIs

SQL/NoSQL databases

CI/CD

AWS/Azure

Docker

Git

Tools

LangChain

LangGraph

CrewAI

AutoGen

Strands Agents

OpenAI API

Azure OpenAI

Amazon Bedrock

Kubernetes

Job description

Experience: 8 to 10 Years

Role Summary

We are looking for a hands-on Full Stack AI Engineer to design, develop, and deploy enterprise-grade AI applications and reusable Agentic AI frameworks. The role combines full-stack development, AI engineering, framework development, and cloud-native architecture to build scalable AI solutions and enterprise AI platform capabilities.

Key Responsibilities

• Design and develop end-to-end AI applications using React/Next.js, Python/Node.js, APIs, and databases.
• Build agentic AI solutions using LLMs, RAG, multi-agent orchestration, tool calling, memory, and MCP.
• Design and develop reusable Agentic AI frameworks, SDKs, orchestration components, and developer accelerators.
• Build extensible agent architectures, reusable tools, connectors, integration adapters, and workflow templates.
• Implement framework-level capabilities including agent lifecycle management, state management, context handling, guardrails, evaluation, and observability.
• Develop secure enterprise integrations and scalable backend services.
• Implement cloud-native deployment, CI/CD, monitoring, and performance optimization on AWS/Azure.
• Drive solutions from PoC to production while ensuring reusability, maintainability, and enterprise standards.
• Collaborate with architects, developers, and stakeholders to establish AI engineering best practices.

Required Technical Skills

Full Stack Engineering

• Strong experience with React, Next.js, TypeScript/JavaScript, HTML, and CSS.
• Proficiency in Python and/or Node.js.
• Experience with REST APIs, authentication, authorization, and SQL/NoSQL databases.

Agentic AI Engineering

• Hands-on experience with LLM APIs (OpenAI, Azure OpenAI, Amazon Bedrock, or equivalent).
• Experience with LangChain, LangGraph, CrewAI, AutoGen, Strands Agents, or similar frameworks.
• Strong understanding of RAG, embeddings, vector databases, tool calling, MCP, and multi-agent orchestration.

AI Framework & Platform Engineering

• Experience designing reusable software frameworks, libraries, SDKs, and modular architectures.
• Understanding of agent orchestration patterns, workflow engines, state management, and agent-to-agent communication.
• Ability to build extensible plugin architectures, reusable connectors, tool registries, and configuration-driven components.
• Knowledge of AI guardrails, evaluation frameworks, tracing, observability, and governance.
• Experience designing scalable, secure, and maintainable platform components with well-defined interfaces and APIs.

Cloud & DevOps

• Experience with AWS or Azure, Docker, Git, and CI/CD pipelines.
• Understanding of cloud-native architectures, application security, monitoring, and performance optimization.

Preferred Skills

• Experience building internal developer platforms, AI frameworks, or enterprise AI accelerators.
• Exposure to MCP servers, A2A protocols, agent registries, and multi-agent runtime architectures.
• Knowledge of Kubernetes, infrastructure as code, and distributed systems.
• Experience with AI gateways, model routing, cost optimization, and LLM evaluation.
• Familiarity with enterprise integrations such as SAP, ServiceNow, Jira, or SharePoint.

Soft Skills

• Strong analytical, problem-solving, and software design skills.
• Ability to independently design and deliver reusable technical components.
• Strong collaboration, communication, and stakeholder management.
• Ownership mindset with a focus on engineering quality and innovation.