Job Title: AI Solutions Developer for Cybersecurity

Department: ITG CDF

About Business line/Function: The AI department within the CDF teams aims to upskill the teams in charge of Cyber and Fraud Detection with new AI tools to improve tools and increase productivity. The objective is to achieve AI empowerment within CDF.

Position Purpose: The AI Solution Developer will be responsible for developing AI-based solutions to enhance the capabilities of the Cyber and Fraud Detection teams. This role involves working closely with subject matter experts to adapt tools and continuously improve them based on user feedback. The developer will leverage Python and associated libraries to build and deploy machine learning models and user interfaces.

Responsibilities

Direct Responsibilities

• End-to-End Solution Ownership:
  Own the complete project lifecycle—interacting with business stakeholders, translating requirements, architecting solutions, developing, deploying, and supporting AI-powered cyber and fraud detection tools.

• Advanced Model Development:
  Design, train, finetune, and evaluate machine learning and deep learning models, especially transformer-based architectures and Large Language Models (LLMs), using PyTorch, TensorFlow, or JAX.

• GenAI/Agentic Systems:

   Research, build, and implement GenAI solutions using LLMs, small language models (SLMs), and agentic frameworks such as LangGraph, LangChain, or similar.

• Prompt Engineering:

   Craft advanced prompts, context chains, and input/output pipelines to optimize LLM performance and specialize solutions for security/fraud use cases.

• Data Engineering:

   Develop and maintain secure ETL pipelines. Handle large, sensitive, and structured/unstructured datasets for model training, inference, and monitoring.

• User Interface Development (Optional, Plus):

   Design simple, functional, and business-friendly UIs using Streamlit, Gradio, Flask, or other modern frameworks to allow teams to interact with AI solutions seamlessly.

• Contributing and Collaboration Responsibilities

  Collaborate with subject matter experts and business users to identify opportunities for GenAI/agentic solutions.

• Stay updated with the latest research and developments in LLMs, SLMs, and AI for cybersecurity, and proactively bring those advancements into the organization.

• Contribute to AI upskilling and best practices for CDF teams.

• Document solutions, design decisions, and deliver technical guidance/training to colleagues and stakeholders.

Technical & Behavioral Competencies

• Core AI/ML

  • Deep expertise in machine learning and deep learning, especially transformer-based models (BERT, GPT, Llama, Mistral, etc.).

     

  • Hands-on experience with LLMs (including open-source SLMs), their architectures, pre-training, instruction tuning, supervised/reinforcement finetuning, quantization, and model evaluation.

     

  • Strong foundations in GenAI, NLP, and prompt engineering.

     

  • Familiarity with best practices for secure and robust AI deployment (preferably in regulated environments).

• Agentic and Orchestration Frameworks

  • Experience developing agentic workflows/applications with LangGraph, LangChain, or similar is strongly preferred.

• Programming & Data Engineering

  • Proficient in Python, including ML/data libraries (PyTorch/TensorFlow, pandas, scikit-learn).

  • Solid understanding of ETL processes, data wrangling, and building/maintaining production pipelines.

• UI (Plus/Optional)

  • Experience with at least one interface tool: Streamlit, Gradio, Flask, etc.

• DevOps & Deployment

  • Experience deploying and maintaining production-grade AI models. Familiarity with Docker, REST APIs, or cloud ML platforms (GCP, Azure, AWS) is a plus.

• Solution Ownership

  • Demonstrated ability to take a project from ideation to business user engagement, POC, MVP, and production.

Specific Qualifications:

• 4+ years hands-on with machine learning / deep learning in production environments (cybersecurity domain experience is a plus.
• Portfolio, GitHub, or case studies of relevant GenAI, LLM, agentic solution projects are a plus 

Skills Referential (Required knowledge, skills and abilities)

Technical Skills:

• Skill 1
• Skill 2
• Skill 3
• Skill 4
• <Insert more skills as necessary>

Behavioral Skills: 

• • Innovation and creative problem-solving in dynamic security/fraud environments

  • Curiosity and self-driven research on new AI techniques for business value

• Transversal Skills

  • Excellent oral and written communication (technical and non-technical)

  • Stakeholder management and requirements gathering

  • Team player with collaborative and mentoring mindset

  • Rigor, attention to detail, adaptability, and resilience

Education Level: Bachelor’s/Master’s degree in Computer Science, Data Science, AI, Machine Learning, or related field

Location: Chennai

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.

About BNP Paribas India Solutions:

Established in 2005, BNP Paribas India Solutions is a wholly owned subsidiary of BNP Paribas SA, European Union’s leading bank with an international reach. With delivery centers located in Bengaluru, Chennai and Mumbai, we are a 24x7 global delivery center. India Solutions services three business lines: Corporate and Institutional Banking, Investment Solutions and Retail Banking for BNP Paribas across the Group. Driving innovation and growth, we are harnessing the potential of over 10000 employees, to provide support and develop best-in-class solutions.

Commitment to Diversity and Inclusion

At BNP Paribas, we passionately embrace diversity and are committed to fostering an inclusive workplace where all employees are valued, respected and can bring their authentic selves to work. We prohibit Discrimination and Harassment of any kind and our policies promote equal employment opportunity for all employees and applicants, irrespective of, but not limited to their gender, gender identity, sex, sexual orientation, ethnicity, race, colour, national origin, age, religion, social status, mental or physical disabilities, veteran status etc. As a global Bank, we truly believe that inclusion and diversity of our teams is key to our success in serving our clients and the communities we operate in. As a global Bank, we truly believe that inclusion and diversity of our teams is key to our success in serving our clients and the communities we operate in.