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.
Key Responsibilities
- 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
Essential Skills & Experience
3+ years of experience as an AI / ML Engineer or Software Engineer in AI-focused projectsStrong knowledge of LLMs, transformers, and conversational AIExperience with LangChain, LangGraph, or similar LLM orchestration toolsHands-on experience with FastAPI or equivalent Python frameworks for backend servicesFamiliarity with Prompt Engineering, RAG, and LLM evaluation techniquesDeep understanding of vector search, embeddings, and similarity-based retrievalWorking knowledge of Dialogflow CX or equivalent chatbot frameworksStrong software engineering foundation – Git, CI / CD, testing, REST APIsBonus Skills (Nice to Have)
Data Engineering experience : ETL, Airflow, dbt, BigQuery, or SnowflakeExperience building web crawlers, custom scrapers, or integrating external knowledge sourcesExperience setting up data lakes / warehouses and pipelinesFamiliarity with cloud infrastructure : GCP, AWS, or AzureFamiliarity with fine-tuning open-source LLMs (e.g., LLaMA, Mistral, etc.)Experience in evaluating LLM safety, reliability, and cost-performance tradeoffsExposure to frontend frameworks (React, Next.js) for chatbot UI integration#J-18808-Ljbffr