Senior Data Scientist

Overview

 

We are looking for a highly skilled Senior Data Scientist to design, develop, and industrialize enterprise-grade Conversational AI and GenAI solutions. The ideal candidate will have deep expertise in Large Language Models, Knowledge Graphs, advanced NLP, and scalable AI application development, along with strong experience in data engineering, cloud platforms, and modern AI system architecture.

This role involves working across the full lifecycle, from architecture to POC to production deployment, to build robust, scalable, and business-ready AI platforms.

Job Description

Key Responsibilities

Conversational AI & LLM Solutions

• Design, develop, and maintain enterprise-grade Conversational AI systems using modern architectural patterns.
• Build context-aware AI applications leveraging LLMs, vector databases, and multi-agent orchestration frameworks.
• Develop and optimize prompt engineering strategies for reliability, evaluation, and performance tuning.
• Implement LLM interaction workflows including RAG, tool usage, and agent-to-agent communication.

Knowledge Graphs & Graph Technologies

• Design and integrate Knowledge Graphs to enhance contextual intelligence and reasoning.
• Develop graph-based solutions using enterprise Neo4j with strong proficiency in Cypher query language and graph algorithms.
• Implement graph traversal, inference, and graph analytics for AI use cases.

AI Application Development

• Build modular, scalable, and maintainable Python-based AI applications.
• Develop high-performance REST APIs using Fast / Flask framework.
• Implement asynchronous processing and orchestration workflows.
• Ensure security, performance, and observability of AI services.

Data Engineering & Integration

• Develop and manage data ingestion and transformation pipelines using Azure Data Factory and Data bricks.
• Design and implement data lake architectures supporting multiple structured and unstructured data formats.
• Integrate large-scale enterprise data sources with AI platforms.
• Work with MongoDB for schema design, indexing strategies, and large-scale semi-structured data handling.

Distributed & Cloud Computing

• Develop distributed data processing solutions using Databricks and PySpark.
• Deploy and manage AI workloads on cloud platforms (preferably Microsoft Azure AI stack).

Architecture, POC & Industrialization

• Design scalable, highly available, and robust enterprise AI architectures.
• Lead rapid POC development and transition solutions to production-grade systems.
• Knowledge about CI/CD pipelines, containerization (Docker), and deployment automation.
• Define best practices for performance, scalability, and cost optimization.

Required Technical Skills

AI / GenAI

• Large Language Models (LLMs) & NLP
• RAG, agents, and multi-agent orchestration
• Prompt engineering & LLM evaluation frameworks
• Vector databases

Knowledge Graphs

• Neo4j
• Cypher query language
• Graph data modeling & graph algorithms

Programming & Frameworks

• Python (advanced proficiency)
• FastAPI / Flask
• Asynchronous & modular application design

Data & Databases

• Azure Data Factory
• Databricks & PySpark
• MongoDB (schema design, indexing, optimization)
• Data lake architectures

DevOps & Deployment

• CI/CD pipelines
• Docker & containerization
• Cloud deployment (Azure preferred)

Preferred Skills

• Experience with Microsoft AI ecosystem (Azure OpenAI, AI Search, Microsoft Foundry, etc.)
• Experience in enterprise-scale AI platform development
• Strong understanding of AI system evaluation, monitoring, and governance
• Exposure to security and responsible AI practices

Soft Skills

• Strong problem-solving and system design capabilities
• Ability to work in a fast-paced, innovation-driven environment
• Excellent communication and stakeholder collaboration
• Mentoring and technical leadership experience

Skills & Requirements

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