Job Description :

- Design, develop, and deploy production-grade AI applications using Python and modern AI engineering frameworks.

- Build Retrieval-Augmented Generation (RAG) solutions using vector databases and enterprise knowledge sources.

- Develop AI agents and multi-agent workflows using frameworks such as LangChain, LangGraph, n8n, OpenAI Agents SDK, or similar orchestration frameworks.

- Integrate AI solutions with enterprise applications, cloud services, APIs, databases, and internal business systems.

- Collaborate with business stakeholders, product teams, and engineering teams to translate business requirements into AI-powered solutions.

- Build secure, scalable, and reliable AI applications on AWS cloud infrastructure.

- Optimize LLM performance, prompt engineering, retrieval quality, latency, scalability, and operational cost.

- Develop reusable AI components, frameworks, templates, and engineering best practices for the ERPAI AI platform.

- Own AI initiatives throughout the complete software lifecycle from ideation and prototyping through production deployment and ongoing improvements.

Required Skills & Experience :

- 5 - 12 years of professional experience in Software Engineering, Machine Learning Engineering, or AI Engineering.

- Strong software engineering experience with Python.

- Hands-on experience building applications using Large Language Models (LLMs).

- Practical experience designing and implementing Retrieval-Augmented Generation (RAG) solutions.

- Experience working with vector databases and embedding models.

- Experience with AI orchestration frameworks such as LangChain, LangGraph, n8n, OpenAI Agents SDK, or similar multi-agent frameworks.

- Experience developing cloud-native applications on AWS.

- Strong understanding of REST APIs, backend services, databases, data pipelines, and enterprise application integration.

- Experience building production-grade AI applications rather than proof-of-concept implementations.

- Strong analytical, debugging, and problem-solving skills.

- Ability to work independently, take ownership, and deliver high-quality solutions with minimal supervision.

- A startup mindset with a strong focus on execution, learning, and continuous improvement.