Senior Python Engineer with Azure and LLM Expertise

About the Job: We are seeking a skilled developer with expertise in Java, LLM Application Frameworks, and Data Science on Azure to join our team in Dubai, United Arab Emirates. The ideal candidate will possess a strong knowledge base in bank-related technologies and demonstrate a robust understanding of software architecture and design patterns, especially within the realm of enterprise AI solutions.

Must Have Skills:

• Java (Expert)
• LLM Application Frameworks (Strong)
• Data science on Azure (Strong)

Good To Have Skills:

• Azure DevOps suite (Expert)

Knowledge & Experience:

• 5+ years of hands-on development experience, with a minimum of 3 years in advanced Python engineering.
• Proven expertise in LangChain, LangGraph, or equivalent LLM orchestration frameworks.
• Familiarity with Azure AI Services, including Azure OpenAI, AI Studio, and Cognitive APIs.
• Strong background in serverless architecture, particularly Azure Functions or AWS Lambda.
• Solid understanding of LLM application design, prompt engineering, embeddings, and vector database integrations.
• Experience with Java-based microservices and REST API integration.
• Strong grasp of software architecture, design patterns, and distributed system concepts.
• Experience in developing modular, testable, and maintainable Python codebases.
• Knowledge of LLM lifecycle management (training, fine-tuning, evaluation).
• Experience with Azure DevOps pipelines, Docker, and Kubernetes (EKS/AKS).
• Prior work on enterprise AI solutions, such as chatbots, assistants, document intelligence, and RAG pipelines.

Domain & Functional Expertise:

• Strong functional and technical understanding of the Banking domain, especially Corporate & Investment Banking.
• Ability to interpret business requirements and assess system impacts, integrations, and dependencies.

Technical Skills:

• Programming: Expert-level Python (data structures, algorithms, async I/O, typing, and packaging).
• Frameworks: LangChain, LangGraph, FastAPI, Flask.
• Cloud: Azure AI Services, Azure Functions, Azure Storage, Cosmos DB (or similar).
• Serverless: Function Apps, Event-driven design, API Gateway integrations.
• DevOps: CI/CD, Docker, Git, Unit testing, Code reviews.
• Data & AI: Embeddings, Vector stores, RAG, OpenAI APIs.
• Integration: REST, GraphQL, gRPC, message queues (Kafka/SQS/Event Hub).
• Exposure to Java: Microservices, Spring Boot integration.