ENGINEERING JOBS / IT JOBS
Associate AI Engineers Full Time NEW
Full job description
Key Responsibilities:
- Assist in the development, testing, and deployment of AI chatbots using local and cloud-based LLMs.
- Support in building RAG (Retrieval-Augmented Generation) systems, including vector search and semantic retrieval.
- Work with Qdrant and embedding models to manage collections, vectors, and similarity search.
- Help develop FastAPI endpoints for AI services and WhatsApp/other messaging integrations.
- Participate in processing training data, embeddings, and conversation history pipelines.
- Implement and refine LLM-based intent detection, response ranking, and fallback systems.
- Collaborate on model optimization, prompt tuning, and improving response accuracy.
- Assist in deploying real-time AI systems for customer service automation.
- Contribute to knowledge base creation, FAQ structuring, and dynamic response generation.
- Write clean, maintainable, and well-documented code for AI modules.
- Stay updated on conversational AI, RAG methodologies, LLM improvements, and vector database innovations.
- Support integrating AI services into cloud environments and multi-tenant architectures.
Required Skills & Qualifications:
- Bachelor’s degree in Computer Science, AI, Data Science, or a related field.
- 0.5 – 2 years of experience working on AI/ML or chatbot projects.
- Hands-on experience with LLMs (OpenAI, Ollama, Hugging Face) and prompt engineering.
- Understanding of vector databases such as Qdrant, Pinecone, or ChromaDB.
- Experience working with embedding models, semantic search, or RAG pipelines.
- Proficiency in Python, especially FastAPI, async workflows, and API development.
- Familiarity with supervised/unsupervised ML concepts and evaluation techniques.
- Understanding of REST APIs, Git, and version control workflows.
- Good analytical, debugging, and problem-solving skills.
- Ability to work in a collaborative, fast-paced engineering environment.
- Exposure to cloud platforms (AWS/GCP/Azure) for deploying AI applications.
- Basic understanding of MLOps, retraining pipelines, or model monitoring.
Work Location: In person