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

- Robust 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.

📌 Fullstack Engineer- WIth AI (Pune)
🏢 Cummins
📍 Pune