Associate - Data Science / Applied AI ML

Associate - Data Science / Applied AI ML

Job Responsibilities

• Develop AI-powered applications leveraging LLMs, Generative AI, Agentic AI, and advanced analytics.
• Build and enhance AI agents that interact with enterprise tools, data sources, APIs, and business workflows.
• Develop orchestration workflows using frameworks such as LangGraph, Semantic Kernel, LangChain, or similar technologies.
• Implement MCP (Model Context Protocol) integrations to securely connect AI applications with enterprise systems, knowledge sources, and services.
• Build and support Retrieval-Augmented Generation (RAG), GraphRAG, and Knowledge Graph solutions.
• Develop scalable Python-based applications, APIs, and services to support AI and analytics use cases.
• Integrate enterprise LLM platforms and GenAI services into business workflows and operational processes.
• Perform data exploration, experimentation, testing, and performance optimization across structured and unstructured datasets.
• Create dashboards, reporting solutions, and user-facing applications that translate AI outputs into actionable insights.
• Collaborate with Compliance, Technology, and Business stakeholders to understand requirements and deliver high-quality solutions.
• Contribute to reusable frameworks, engineering standards, testing practices, and AI governance requirements.

Required Qualifications and Skills

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related quantitative discipline.
• 5+ years of experience developing software, automation, analytics, or AI solutions.
• Strong programming skills in Python and SQL.
• Experience working with LLMs, Generative AI platforms, prompt engineering, and AI application development.
• Experience building solutions using orchestration frameworks such as LangGraph, LangChain or similar technologies.
• Understanding of Agentic AI concepts, tool calling, workflow automation, memory management, and multi-step reasoning.
• Experience implementing MCP (Model Context Protocol) integrations or similar enterprise integration patterns.
• Familiarity with RAG, embeddings, vector databases, semantic search, and knowledge retrieval techniques.
• Experience working with REST APIs, JSON, and enterprise system integrations.
• Strong problem-solving, analytical, and communication skills.
• Ability to work independently and collaboratively in a fast-paced environment.

Preferred Qualifications

• Experience with Neo4j, Knowledge Graphs, or GraphRAG architectures.
• Experience with AI observability, evaluation frameworks, and LLM testing methodologies.
• Experience with cloud-based AI platforms and enterprise AI ecosystems.
• Familiarity with compliance, risk management, or financial services domains.
• Experience building AI copilots, assistants, workflow automation solutions, or multi-agent systems.