Data Scientist

Role Overview:
This role is ideal for an AI professional who thrives in designing LLM-driven pipelines, orchestrating multi-agent architectures, and optimizing models for deployment on enterprise platforms. You will work with cross-functional teams to automate business processes and deliver
insights at scale.

Key Responsibilities:
● Architect and implement Retrieval-Augmented Generation (RAG) pipelines using tools like LangChain, LlamaIndex, and Azure AI Search.
● Design and coordinate agent-based LLM systems using frameworks like AutoGen, TaskWeaver, and CrewAI for complex document analysis and process automation.
● Integrate Azure Cognitive Services (OCR, layout analysis, document intelligence) for structured data extraction and real-time insight generation.
● Develop secure and scalable FastAPI backends, containerized via Docker and orchestrated on Azure Kubernetes Service (AKS).
● Collaborate with business experts to fine-tune prompts, build chatbots with contextual memory, and deploy solutions that meet compliance and audit standards.
● Build low-code applications using Power Apps and Power Automate to streamline enterprise workflows like workforce planning and financial tracking.
● Monitor model performance using Azure Application Insights, iterate on user feedback, and maintain operational excellence with CI/CD pipelines.
● Contribute to AI research and publications and stay updated with the latest trends in ethical AI and edge deployment strategies.

Required Skills:

● 2–4 years of experience in Data Science, AI/ML, and Deep Learning, preferably in enterprise settings.
● Strong experience with Python, TensorFlow/Keras, Scikit-learn, and NLP frameworks such as SpaCy, HuggingFace, and NLTK.
● Proven expertise in Generative AI systems, including RAG architecture, vector-based search, and prompt engineering.
● Solid hands-on experience with Azure Cloud Platform, including services like Azure OpenAI, Cosmos DB, Key Vault, Blob Storage, Function Apps, etc.
● Proficiency with FastAPI, Flask, and RESTful API design.
● Experience deploying models and services using Docker, Kubernetes, and Azure DevOps.
● Familiarity with Power Platform (Power BI, Power Apps, Power Automate) and SharePoint integration.

Preferred Qualifications:
● Microsoft certifications such as Azure AI Engineer Associate (AI-102).
● Experience in developing enterprise tools for due diligence, finance, or workforce planning.
● Exposure to edge computing and model optimization for constrained environments.
● Demonstrated research output through peer-reviewed publications.