AI ENGINEER - ODIN - Global Markets IT

Job Title: AI Engineer
Department: ISPL Data Office, CIB IT Transversal
About Business Line/Function
Global Markets
The Global Markets business of BNP Paribas helps its corporate and institutional clients leverage capital markets across the globe for their financing, risk management and investment needs. This encompasses a wide range of financial products ranging from Foreign exchange to complex Equity Derivatives that are traded in financial markets across the globe 24/7. IT systems are integral to the business and are a key part of the value proposition to clients. These IT systems range from industry standard products for standard process automation to internally developed, often, market leading IT applications. The IT teams owning these IT systems are made up of functions that include Technical and Application production support, Business Analysis & Project Management, Development & Maintenance and Quality Control. BNP Paribas India Solutions is an equal partner in these IT functions along with colleagues in other locations including Paris, London, New York, Tokyo, Singapore & Hong Kong. This partnership ranges from sharing the IT work load, executing global strategy to owning global applications offshore. The technology and engineering landscape is wide, encompassing almost all techniques and platforms. It continues to evolve and transform with the market with the business continuing to invest in it.
Position Purpose
The AI Engineer will design, build and deploy production-grade data and AI solutions. The role combines strong Python and data engineering fundamentals (ETL, relational databases, REST APIs) with hands-on development of AI capabilities such as LLM-powered applications, Retrieval-Augmented Generation (RAG) pipelines and agentic workflows.
The position requires working in a virtual team and international environment and is multidisciplinary in nature. It involves coordination with other locations and divisions of BNP Paribas as necessary. The candidate should have strong engineering discipline, a problem-solving mindset and the ability to turn business requirements into reliable, secure and scalable solutions.
Responsibilities
Direct Responsibilities
Design, develop and maintain scalable Python applications and data pipelines using Pandas for data extraction, transformation and loading (ETL).
Build and expose secure, well-documented REST APIs using FastAPI, applying data validation (e.g. Pydantic) and API best practices.
Write efficient SQL and work with relational databases such as Oracle, PostgreSQL and MS SQL Server, including data modelling, query optimization and performance tuning.
Containerize applications using Docker and support deployment across development, test and production environments.
Develop Generative AI and Agentic AI solutions – LLM-based applications, RAG pipelines, and multi-agent workflows using frameworks such as LangChain, LangGraph or CrewAI.
Integrate Large Language Models through provider APIs (e.g. OpenAI / Azure OpenAI) and open-source models (e.g. Hugging Face), applying prompt engineering, structured outputs and function / tool calling.
Build natural-language interfaces to data (e.g. Text-to-SQL agents) that allow business users to query databases in plain English.
Automate business workflows by combining AI capabilities with APIs, scheduling / workflow tools (e.g. n8n) and messaging integrations.
Integrate AI solutions with enterprise data sources and tools, including vector databases and Model Context Protocol (MCP) based tool integrations.
Implement LLM observability, tracing and evaluation (e.g. Langfuse) to monitor quality, cost, latency and reliability of AI applications.
Develop, train and evaluate Machine Learning models where appropriate, using libraries such as Scikit-learn, TensorFlow and NumPy.
Follow sound engineering practices: version control with Git, code reviews, unit / integration testing and clear technical documentation.
Contribute to CI/CD pipelines (e.g. GitHub Actions / Jenkins) and support deployment of AI services on on-premise or cloud platforms (AWS / GCP / Azure).
Translate business requirements into technical designs and work closely with business users, data teams and other stakeholders throughout implementation and delivery.
Contributing Responsibilities
Contribute to the design of reusable components, frameworks and best practices for data engineering and AI development within the team.
Ensure solutions comply with the Group’s standards on data security, privacy, Responsible AI, risk and compliance.
Identify opportunities for automation and process improvement, and propose AI-driven solutions.
Participate in knowledge sharing, mentoring and cross-training to build AI capabilities within the team.
Stay up to date with the evolving AI / LLM ecosystem and assess new tools and techniques for adoption.
Technical & Behavioral Competencies
Strong programming skills in Python, with hands-on experience in data manipulation and analysis using Pandas.
Solid working knowledge of SQL and relational databases – Oracle / PostgreSQL / MS SQL Server.
Experience designing and building REST APIs, preferably with FastAPI.
Good understanding of ETL concepts, data pipelines, data quality and data integration.
Practical experience with Docker and Git based development workflows.
Exposure to LLM APIs (OpenAI / Azure OpenAI), Hugging Face models, prompt engineering, LLM application frameworks (LangChain, LangGraph, CrewAI), RAG pipelines, vector databases and LLM observability tools (e.g. Langfuse) is a strong plus.
Familiarity with ClickHouse, front-end frameworks (React / Angular), Machine Learning libraries (Scikit-learn, TensorFlow, NumPy), CI/CD and cloud platforms (AWS / GCP / Azure) is an added advantage.
Strong analytical and problem-solving skills with attention to detail; ability to communicate clearly with technical and non-technical stakeholders.
Specific Qualifications
Minimum 3 years of hands-on experience in Python development / data engineering, with Bachelor's Degree in Computer Science, Engineering, IT or a related field, or equivalent experience.
Hands-on experience building or contributing to AI / LLM based applications (Generative AI, RAG, Agentic AI) will be preferred.
Prior experience in the Banking / Financial Services domain is desirable.
Technical Skills
Skills Referential (Required knowledge, skills and abilities)
Must Have
Python
Pandas
Oracle / PostgreSQL / MS SQL Server
REST API
FastAPI
Docker
Git
ETL Concepts
Good to Have
ClickHouse
React / Angular
Agentic AI – LangGraph, CrewAI, LangChain
LLM APIs – OpenAI / Azure OpenAI; Prompt Engineering
Hugging Face (open-source LLMs, embeddings)
Text-to-SQL / Natural-language data querying agents
LLM Observability – Langfuse
Model Context Protocol (MCP)
RAG Pipelines and Vector Databases
Machine Learning – Scikit-learn, TensorFlow, NumPy
Pydantic
Workflow Automation – n8n
CI/CD – GitHub Actions / Jenkins
Cloud Platforms – AWS / GCP / Azure
Behavioral Skills
Communication skills – oral & written
Analytical Ability
Problem Solving / Critical Thinking
Team Player / Ability to collaborate
Ability to deliver / Results driven
Adaptability and continuous learning
Education Level: Bachelor Degree or equivalent (B.E. / B.Tech / MCA / M.Sc. in Computer Science, IT or related field)
Location: Mumbai
About BNP Paribas Group
BNP Paribas is the European Union’s leading bank and key player in international banking. It operates in 65 countries and has nearly 185,000 employees, including more than 145,000 in Europe. The Group has key positions in its three main fields of activity: Commercial, Personal Banking & Services for the Group’s commercial & personal banking and several specialized businesses including BNP Paribas Personal Finance and Arval; Investment & Protection Services for savings, investment, and protection solutions; and Corporate & Institutional Banking, focused on corporate and institutional clients. Based on its strong diversified and integrated model, the Group helps all its clients (individuals, community associations, entrepreneurs, SMEs, corporates and institutional clients) to realize their projects through solutions spanning financing, investment, savings and protection insurance. In Europe, BNP Paribas has four domestic markets: Belgium, France, Italy, and Luxembourg. The Group is rolling out its integrated commercial & personal banking model across several Mediterranean countries, Turkey, and Eastern Europe. As a key player in international banking, the Group has leading platforms and business lines in Europe, a strong presence in the Americas as well as a solid and fast-growing business in Asia-Pacific. BNP Paribas has implemented a Corporate Social Responsibility approach in all its activities, enabling it to contribute to the construction of a sustainable future, while ensuring the Group's performance and stability.
Abo

Work arrangement
Yes