AI Engineer (Generative AI)-Contractor

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Experience : 3+ years

Employment Type : Full-time Contractor

Team : Data & AI Team

About the Role

We are seeking a passionate and hands-on AI Engineer to join our growing Data & AI team. In this role, you will design, develop, and deploy cutting-edge LLM-powered chatbot and search solutions for enterprise use cases. You will work on projects involving Google Cloud Dialogflow CX, Retrieval-Augmented Generation (RAG), LangChain, LangGraph, and vector databases, delivering high-impact applications that enable intelligent conversational interfaces and smart search experiences.

This is a highly technical and client-facing role, ideal for someone who enjoys solving real-world problems using state-of-the-art AI tools and frameworks.

• Design, develop, and optimize AI chatbots using LLMs (e.g., Gemini, LLaMA, Claude, etc.)
• Build semantic and enterprise search systems with RAG pipelines
• Integrate LLM orchestration frameworks such as LangChain and LangGraph
• Work with vector databases (e.g., FAISS, Weaviate, Pinecone, Milvus) for efficient retrieval
• Develop and deploy APIs using FastAPI or other Python-based backend frameworks
• Implement prompt engineering, tuning, and evaluation techniques for various use cases
• Fine-tune foundation models using domain-specific datasets when required
• Work with GCP services including Dialogflow CX, Vertex AI, BigQuery, Cloud Functions
• Contribute to best practices, documentation, code repositories, and DevOps pipelines
• 3+ years of experience as an AI / ML Engineer or Software Engineer in AI-focused projects
• Strong knowledge of LLMs, transformers, and conversational AI
• Experience with LangChain, LangGraph, or similar LLM orchestration tools
• Hands-on experience with FastAPI or equivalent Python frameworks for backend services
• Familiarity with Prompt Engineering, RAG, and LLM evaluation techniques
• Deep understanding of vector search, embeddings, and similarity-based retrieval
• Working knowledge of Dialogflow CX or equivalent chatbot frameworks
• Strong software engineering foundation – Git, CI / CD, testing, REST APIs
• Data Engineering experience : ETL, Airflow, dbt, BigQuery, or Snowflake
• Experience building web crawlers, custom scrapers, or integrating external knowledge sources
• Experience setting up data lakes / warehouses and pipelines
• Familiarity with cloud infrastructure : GCP, AWS, or Azure
• Familiarity with fine-tuning open-source LLMs (e.g., LLaMA, Mistral, etc.)
• Experience in evaluating LLM safety, reliability, and cost-performance tradeoffs
• Exposure to frontend frameworks (React, Next.js) for chatbot UI integration

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