Overview

We are looking for a hands-on Generative AI Engineer to build production-ready AI applications using LLMs, RAG, Agentic AI, Python and modern AI technologies.

Responsibilities

• Design and develop production-ready Generative AI applications using Python, LLMs and modern AI technologies.
• Build Retrieval-Augmented Generation (RAG) pipelines for document understanding, enterprise knowledge retrieval and context-aware responses.
• Develop Agentic AI workflows using tool calling, function calling, structured outputs and multi-step reasoning.
• Build and maintain backend AI services and REST APIs using Python and frameworks such as FastAPI or Flask.
• Integrate LLM platforms including OpenAI, Hugging Face and other hosted or local AI models.
• Work with embeddings and vector databases such as pgvector, FAISS, ChromaDB or similar technologies.
• Develop conversational AI and Voice AI solutions using Speech-to-Text, Text-to-Speech and real-time audio technologies.
• Integrate AI capabilities with web, mobile and enterprise applications.
• Design AI workflows capable of interpreting user commands and securely interacting with application functions and external tools.
• Implement prompt engineering, context management, structured prompting and model-response validation.
• Improve AI response quality, retrieval accuracy, latency, reliability and overall application performance.
• Evaluate model outputs and implement techniques to reduce hallucinations and improve answer relevance.
• Implement chunking, metadata filtering, retrieval, reranking and other RAG optimisation techniques.
• Work with relational, NoSQL and vector databases as required by the application.
• Containerize and deploy AI services using Docker and modern deployment environments.
• Debug issues across AI models, APIs, databases, integrations and production services.
• Participate in architecture discussions, code reviews, testing and technical documentation.
• Research and evaluate emerging LLM, Agentic AI, Voice AI and Generative AI technologies.
• Collaborate with frontend, backend, QA and product teams to deliver complete AI-powered products.

Qualifications

• Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Information Technology or a related technical field, or equivalent practical experience.
• 1–3 years of hands-on experience in software engineering, AI engineering, Generative AI or a related field.
• Strong programming skills in Python.
• Practical experience working with LLMs and Generative AI applications.
• Hands-on experience integrating AI models or third-party AI APIs into applications.
• Good understanding of Machine Learning, NLP and Generative AI fundamentals.
• Understanding of prompt engineering, context management and structured LLM outputs.
• Understanding of embeddings, semantic search and vector databases.
• Understanding of AI Agents, tool calling, function calling and multi-step AI workflows.
• Working knowledge of databases such as PostgreSQL, MongoDB, MySQL or similar technologies.
• Strong debugging, analytical and problem-solving skills.
• Ability to explain projects personally designed or developed, including architecture, implementation decisions and individual contribution.
• Familiarity with MCP or similar AI tool-integration architectures is an advantage.
• Knowledge of JavaScript/TypeScript, React.js or Node.js is an advantage but not mandatory.