
AI Engineer
3 days ago
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
- 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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