AI & Python Developer

Core Responsibilities
Agentic AI Development: Design, build, and optimize autonomous agent systems using frameworks like LangGraph, AutoGen, and Haystack Agents.
Generative AI Implementation: Build and refine Large Language Models (LLM) and Retrieval-Augmented Generation (RAG) systems, primarily within the Microsoft Azure cloud environment.
Stakeholder Collaboration: Partner with risk and business stakeholders to identify workflows suitable for AI-driven productivity improvements.
Operational Excellence: Implement MLOps and LLMOps best practices for continuous integration, deployment, and monitoring of AI solutions.
Prompt Engineering: Develop and optimize prompts for LLMs to ensure accurate, context-aware outputs for complex financial business cases.echnical Requirements
Experience: Typically requires 5–10 years in AI/ML development, depending on the seniority (Senior vs. Junior roles).
Programming: Advanced proficiency in Python and standard libraries (NumPy, Pandas, scikit-learn).
AI Frameworks: Hands-on experience with PyTorch, TensorFlow, and orchestration tools like LangChain or LlamaIndex.
Cloud Infrastructure: Deep knowledge of Azure AI services, including Azure Machine Learning, Cognitive Services, and Copilot Studio.
Education: A Bachelor's or Master’s degree in Computer Science, Engineering, or a related quantitative field is standard