Cloud Engineer: Gen AI

We are seeking a highly skilled and experienced Data Scientist with a minimum of 3+
years of experience in Data Science and Machine Learning, preferably with experience in LLMs, Generative AI and Agentic AI. The candidate should have strong Python programming skilla, a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. Ideally, you’ll also have:

Core Logic: Strong proficiency in Python (Pandas, NumPy) and API frameworks (FastAPI or Flask). GenAI Stack: Experience with orchestration frameworks like LangChain or LlamaIndex LLMs: Deep understanding of open-source models (Hugging Face). Database: Experience with Vector Databases for semantic search and SQL/NoSQL for structured data. Engineering: Familiarity with Docker, Git, and CI/CD pipelines. Experience building "Agentic" workflows (Autogen, LangGraph). Knowledge of model quantization and local inference (Ollama, vLLM). Experience engaging with stakeholders to translate business needs into AI solutions. Experience with cloud platforms such as GCP or AWS. Utilize tools such as Docker and Git to build and manage AI pipelines.

Roles & Responsibilities

Working across backend and full-stack teams to develop and architect Generative AI solutions using ML and GenAI. Architect & Build: Design and develop scalable GenAI solutions (Chatbots, Agents, Copilots) using Python and FastAPI. Agentic AI: Build autonomous agents capable of tool calling, reasoning, and executing complex workflows. RAG Pipelines: Implement advanced Retrieval Augmented Generation (RAG) systems, optimizing for context retrieval using Vector Databases (e.g., Pinecone, Weaviate, ChromaDB).

Model Optimization: Perform fine-tuning of open-source models (Llama 3, Mistral) and
optimize prompt engineering for cost, latency, and accuracy. Deployment: Containerize applications using Docker and collaborate with DevOps to deploy models on cloud platforms (AWS/GCP). Evaluation: Implement evaluation frameworks (e.g., Ragas, TruLens) to monitor model hallucination and performance. Implement monitoring and logging tools to ensure AI model performance and reliability. Collaborating with software engineers and operations teams to ensure seamless integration and deployment of AI models. Track record of driving innovation and staying updated with the latest AI research and advancements.

Education:
Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Work exp: 3+ years of total experience in Data Science or Software Engineering. 1-2 years of hands-on experience specifically with LLMs and Generative AI.