Overview :

We're looking for an experienced GenAI Engineer to join our Fraud Innovation Lab, contributing to the development of scalable, reliable AI agents that support advanced fraud detection and risk management capabilities. The role focuses on developing AI agents and refining machine learning models to support experimentation, prototyping, and transition to production-grade solutions.

This role is ideal for GenAI engineer with strong software fundamentals who enjoys working in fast-paced, problem-driven environments.

Role & Responsibilities :

- End-to-End Development including design, code, and deploying functional prototypes.

- Build fully functional AI agents capable of autonomous investigation, decision making, and workflow execution.

- Apply strong foundations in mathematics and statistics to develop and optimise algorithms for analytical and AI-driven components.

- Train, evaluate, and optimize machine-learning models for fraud detection, risk scoring, and behavioural analysis.

- Develop APIs and microservices to integrate fraud capabilities with internal platforms and external systems.

- Own technical direction and architecture decisions by defining architecture, selecting tools, and managing the full lifecycle - data ingestion, model logic, APIs, and deployment.

- Design and test components like risk scoring models, anomaly detectors, signal ingestors, and real-time rule engines.

- Apply GenAI/LLMs, basic ML, or hybrid rule+AI techniques.

What We're Looking For :

- Bachelor's or Master's degree in Computer Science, Data Science, Information Technology, Engineering, or a related field.

- 3 to 5 years of experience in software engineering / ML engineering/ Data Science /Gen AI engineer.

- Knowledge of modern Agentic frameworks, GenAI model capabilities, and agentic coding principles (tool use, planning, memory, and execution loops).

- Familiarity with a wide range of prompting techniques, including few-shot, chain of-thought, tool-augmented, retrieval-augmented, and multi-agent prompting

- Strong hands-on experience in Python or similar backend programming languages.

- Solid understanding of data structures, algorithms, and object-oriented design principles.

- Experience building and consuming RESTful APIs and microservice-based architectures.

- Hands-on experience with databases (SQL and/or NoSQL) and data processing workflows.

- Ability to work effectively in agile development environments with evolving requirements.