We are seeking aย Senior AI/ML Engineerย to design, develop, and deploy production-grade AI and machine learning solutions for financial services use cases. This is a hands-on role for an experienced professional with strong expertise inย Python, Machine Learning, Generative AI, LLMs, RAG, Agentic AI, and Data Engineering.
The ideal candidate will be comfortable transforming complex business and financial requirements into scalable AI-powered applications. You will work closely with finance, quantitative, technology, and business teams to develop practical solutions across areas such as risk, credit, compliance, treasury, markets, and financial reporting.
Key Responsibilities
Design, develop, and deploy AI/ML and Generative AI solutions for financial services use cases.
Buildย LLM applications, RAG pipelines, AI agents, document intelligence solutions, and workflow automation tools.
Develop scalable Python-based APIs, model services, dashboards, and data pipelines.
Work with financial datasets, including transaction data, credit data, market data, financial statements, and unstructured documents.
Support AI solutions across risk management, credit, treasury, compliance, markets, corporate banking, and management reporting.
Prototype innovative AI solutions rapidly and transform successful prototypes into production-grade applications.
Design and implement solutions using technologies such asย Python, pandas, NumPy, scikit-learn, PyTorch, TensorFlow, FastAPI, Flask, Streamlit, LangChain, LangGraph, LlamaIndex, vector databases, embeddings, and RAG.
Build and integrate cloud-native solutions usingย Azure, AWS, or GCP, along with Docker, Kubernetes, Git, and CI/CD practices.
Collaborate with finance and quantitative teams to translate complex methodologies into practical software solutions.
Implement appropriate testing, logging, monitoring, security, and basic MLOps practices.
Work with cross-functional teams to understand business requirements and deliver scalable solutions.
Mentor junior engineers, developers, and analysts on coding standards, modelling practices, testing, and deployment.
What Makes You a Great Fit
7+ years of experience inย AI/ML Engineering, Data Science, Software Engineering, or Analytics Engineering.
Strong hands-on expertise inย Pythonย and modern machine learning frameworks.
Proven experience building and deploying real-world AI/ML applications rather than working exclusively with notebooks or prototypes.
Experience developing APIs, data pipelines, dashboards, and production-grade model services.
Familiarity with SQL, structured databases, cloud platforms, containers, CI/CD, testing, and deployment practices.
Strong problem-solving and analytical skills with the ability to work through ambiguous business challenges.
Ability to communicate effectively with both technical teams and finance/business stakeholders.
Exposure toย banking, fintech, payments, insurance, asset management, consulting, or capital marketsย is highly valuable.
Knowledge of financial use cases such as credit risk, fraud, KYC, treasury, trading, portfolio analytics, regulatory reporting, or financial document processing is an advantage.
A practical, delivery-focused mindset with the ability to build solutions quickly and continuously improve them for production use.
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