Intelligent Automation Engineer

Role : AI Engineer

Location : Pune (On-site)

Type : Full-Time

Experience : 3+ Years

Timings : 3 : 00 pm – 12 : 00 am

Job Title : AI Engineer

About the Role :

We’re hiring an AI Engineer with hands-on expertise in Large Language Models (LLMs) and Generative AI to build intelligent, automation-driven solutions such as chatbots, content generators, and lead engagement systems. The role involves end-to-end AI development, from prototype (POC) creation to production-grade deployment — leveraging frameworks like OpenAI, Hugging Face, LangChain, and vector databases.

You will collaborate with cross-functional teams to design smart, scalable AI systems that integrate seamlessly with web and backend applications. The ideal candidate is a creative problem-solver who can leverage both low-code tools and custom AI pipelines to deliver high-impact business solutions quickly.

Key Responsibilities

• Design, develop, and deploy LLM-based Generative AI applications such as chatbots, summarizers, and voice agents.
• Work with OpenAI, Hugging Face, Cohere, and other APIs for AI model integration.
• Apply prompt engineering, RAG pipelines, fine-tuning, and embeddings for business-specific AI use cases.
• Integrate AI models with web and mobile applications in collaboration with frontend and backend teams.
• Utilize LangChain, LlamaIndex, and vector databases (Pinecone, FAISS, Weaviate) for semantic search and LLM orchestration.
• Create Proof of Concepts (POCs) using tools such as N8n, Loveable, Vibe Code, Make (Integromat), Zapier, Retool, Bubble, and Flowise to rapidly design, test, and validate AI workflows, automation logic, and conversational experiences. These POCs help demonstrate business value and technical feasibility before scaling into full-fledged production applications integrated with the existing tech stack (React, Node.Js, MongoDB, and AWS infrastructure).
• Develop API integrations, data pipelines, and AI agents capable of connecting with CRMs, marketing platforms, and other enterprise systems.
• Deploy, monitor, and optimize AI solutions on AWS, GCP, or Azure, ensuring performance, scalability, and cost efficiency.
• Stay ahead of emerging trends in Generative AI, workflow automation, and LLM-powered applications to drive innovation within the organization.

Requirements