AI Engineer with Python

We are looking for an experienced AI Engineer with strong Python expertise to join our banking technology team. The ideal candidate will design, develop, and deploy AI/ML solutions for banking and financial-services use cases, with a strong focus on Generative AI, Large Language Models (LLMs), machine learning, NLP, and production-grade Python applications.

The candidate will work closely with data scientists, software engineers, product teams, and banking stakeholders to build secure, scalable, and compliant AI solutions., * Design, develop, and deploy AI/ML solutions using Python for banking and financial-services use cases.

• Develop applications using Generative AI, LLMs, NLP, RAG, prompt engineering, and AI agents.
• Build and maintain production-quality Python services, APIs, and AI pipelines.
• Develop Retrieval-Augmented Generation (RAG) solutions using vector databases and enterprise knowledge repositories.
• Integrate LLMs and AI services with existing banking applications and data platforms.
• Develop and optimize machine-learning models for use cases such as:
• Fraud detection
• Credit risk and underwriting
• Customer segmentation
• Transaction monitoring
• Document intelligence
• Customer service automation
• Financial document analysis
• Regulatory/compliance use cases
• Implement model evaluation, monitoring, versioning, and continuous improvement.
• Work with structured and unstructured banking data while maintaining high standards for security, privacy, governance, and regulatory compliance.
• Build REST APIs and microservices using frameworks such as FastAPI or Flask.
• Collaborate with DevOps/MLOps teams to deploy AI solutions on cloud platforms.
• Optimize AI applications for performance, scalability, reliability, and cost.
• Participate in code reviews, architecture discussions, testing, and technical documentation.

Programming

• Strong hands-on experience with Python
• Object-oriented programming and software engineering principles
• REST APIs and microservices
• FastAPI / Flask
• Git and CI/CD

AI / Machine Learning

• Machine learning fundamentals and model development
• NLP and deep learning
• Generative AI and LLMs
• Prompt engineering
• RAG architecture
• Embeddings and vector search
• Experience with LLM frameworks such as LangChain, LlamaIndex, or similar
• Familiarity with model evaluation and observability

Cloud & Data

• Experience with AWS, Azure, or Google Cloud Platform
• SQL and relational databases
• NoSQL databases
• Experience with vector databases such as Pinecone, FAISS, Weaviate, Milvus, or Azure AI Search
• Docker and Kubernetes is a plus