Junior AI Engineer (Freshgrad welcomed)

Who we are

Crédit Agricole Corporate and Investment Banking (CA-CIB) is the CIB arm of Crédit Agricole Group, world’s 11th largest bank by total assets.

Our Singapore center is the 2nd largest IT setup (after Paris Head Office) for Crédit Agricole CIB's worldwide business. We work daily with international branches located in 30 markets by:

• Envisioning and preparing the Bank’s futures information systems
• Partnering and supporting core banking flagships and transverse areas in their large scale development projects
• Providing premium In-house Banking applications

This unique positioning empowers us to bring our core banking business a sustainable competitive advantage on the market

We seek innovative and agile people sharing our mindset to support ambitious and forthcoming technological challenges.

Position

The Junior AI Engineer plays a hands-on delivery role within the AI & Data Science team, contributing to the design, development, and deployment of AI-powered solutions across the Bank's business lines and support functions. This role sits at the intersection of technology and business — requiring both the technical capability to build working AI systems and communication & presentation skills to engage directly with business stakeholders to understand their needs.

The incumbent will work alongside senior engineers on production-grade AI initiatives spanning natural language processing, retrieval-augmented generation (RAG), and agentic workflow automation. A core expectation of this role is the ability to translate ambiguous, real-world business problems into executable technical specifications, and eventually into deployed AI solutions. The Junior AI Engineer will develop in contact with senior practitioners and is expected to grow rapidly in both technical depth and business fluency.

All Junior Engineers at GIT are onboarded on multi-functional software engineering teams, developing their skills through on-the-job training and practical project work.

Main responsibilities

• Work with seniors, team lead, other stakeholders to understand project requirements and translate business needs into technical solutions
• Develop AI applications using LLMs, RAG systems, and AI agents with Python and AI coding assistants (GitHub Copilot, Cursor, etc.)
• Build backend services and APIs to support ML applications and connect AI tools to existing bank systems
• Support the packaging and deployment of machine learning models into production environments
• Design and develop data pipelines for ingestion, transformation, and delivery to support AI workflows
• Write clean, modular, testable code and participate in code reviews
• Test, monitor, and debug solutions after deployment, implementing fixes under guidance
• Automate data validation, quality checks, and pipeline monitoring
• Work with cloud platforms (AWS, Azure, or GCP) and container technologies (Docker, Kubernetes)
• Collaborate with data scientists, engineers, DevOps teams, and business stakeholders across cultures and time zones
• Follow best practices for versioning, logging, and CI/CD
• Document your work for team knowledge sharing and stay updated on latest AI developments

Qualifications and Profile

Education

• Bachelor's or Master's degree in Computer Science, Data Science, Information Systems or a related engineering quantitative discipline.

Experience

• Fresher to 2 years of professional experience; fresh graduates are strongly encouraged to apply.
• Hands-on exposure to AI/ML concepts through academic projects, internships, personal projects, or hackathons.
• Demonstrable familiarity with LLM APIs, prompt engineering, or RAG concepts — formal work experience is not required; evidence of self-directed learning is valued equally.
• Practical experience with Python and at least one cloud platform (AWS, Azure, or GCP).
• Use of AI-assisted development tools: GitHub Copilot or equivalent (e.g., Cursor, Antigravity etc)
• Understanding of RESTful APIs and basic software development principles
• Knowledge of version control (Git/GitHub)
• Exposure to ETL tools, data pipelines, or containerization (Docker/Kubernetes) is a plus
• ReactJS experience is a bonus

Other Professional Skills and Mind-set

• AI-native development mindset – treats AI coding assistants (GitHub Copilot or equivalent) as a major development instrument; instinctively uses AI tools to compress cycle time from specification to working prototype, and continuously looks for ways to amplify personal output through intelligent tool use.
• Strong analytical and problem-solving skills applied to complex, ambiguous business challenges.
• Proactive communication - comfortable asking clarifying questions and surfacing issues early.
• Genuine curiosity about AI developments and a track record of self-directed learning.
• Team player with the ability to work independently when required, in a multicultural and geographically distributed environment.
• Basic understanding of financial services or banking concepts, or a strong willingness to develop this knowledge rapidly.