We are looking for a GenAI Developer to design, build, and deploy intelligent applications using Large Language Models . You will bridge the gap between core AI research and practical software products by building robust RAG pipelines, managing vector databases, and optimizing model performance. Your goal is to turn state-of-the-art models into scalable, production-ready solutions that solve complex business problems.
Responsibilities
Design and implement end-to-end Generative AI applications and agents.
Build and optimize RAG (Retrieval-Augmented Generation) pipelines for data grounding.
Write complex prompts and implement prompt engineering best practices.
Integrate LLMs with external APIs, tools, and enterprise data sources.
Develop and maintain backend services using Python frameworks like FastAPI or Flask.
Manage vector databases such as Pinecone, Milvus, or Weaviate.
Fine-tune open-source models (like Llama or Mistral) for specific domain tasks.
Monitor AI performance, mitigate hallucinations, and ensure high-quality outputs.
Collaborate with product teams to identify high-impact AI opportunities.
Requirements
Strong proficiency in Python and modern software development practices.
Hands-on experience with orchestration frameworks like LangChain, LlamaIndex, or Haystack.
Deep understanding of LLM architectures, tokenization, and embedding models.
Experience working with major AI providers like OpenAI, Anthropic, or Google Gemini.
Familiarity with vector storage and semantic search techniques.
Knowledge of CI/CD pipelines and cloud platforms like AWS, GCP, or Azure.
Ability to evaluate and benchmark model outputs using frameworks like RAGAS or TruLens.
Portfolio of AI-driven projects or a strong background in NLP and Machine Learning.
Preferred Qualifications
Experience with model quantization and local deployment (Ollama, vLLM).
Knowledge of frontend frameworks like React for building AI interfaces.
Contributions to open-source AI projects or libraries.
Advanced degree in Computer Science, Data Science, or a related technical field.