AI Engineer

     Design, develop and deploy Generative AI solutions (AI assistants, code generation tools, intelligent automation) that increase IT staff productivity

·       Collaborate with IT teams across the domain to identify high-impact use cases where AI can streamline development, testing, documentation or operations

·       Build AI agent architectures tailored to IT workflows, including agent orchestration and inter-agent communication protocols (e.g. Model Context Protocol – MCP)

·       Develop full-stack components supporting AI solutions: backend services (Python – mandatory), frontend interfaces (React or Angular – optional), and API layers

·       Work closely with the Product Owner and domain experts to translate IT pain points and requirements into technical specifications and actionable user stories

·       Leverage the GenAI Platform squad's shared services, APIs and components to build solutions efficiently while providing feedback for platform improvements

·       Implement and maintain CI/CD pipelines for AI solution deployment, ensuring quality, reproducibility and traceability

·       Design and manage containerized environments (Kubernetes/Docker) for AI workloads in the bank's private cloud infrastructure

·       Ensure all solutions comply with the bank's security, data privacy and governance standards, particularly around sensitive data handling and regulatory constraints

·       Conduct proof-of-concepts (PoCs) and prototyping to evaluate emerging AI tools and frameworks for potential adoption in IT use cases

Contributing Responsibilities

·       Provide feedback to the GenAI Platform squad on shared services, APIs and components to drive platform improvements

·       Participate in knowledge sharing, internal tech talks and communities of practice around GenAI, IT automation and emerging technologies

·       Contribute to the technical evaluation of third-party AI tools and vendor solutions, providing recommendations to the Division Head

·       Mentor and support junior team members on AI engineering best practices and coding standards

·       Collaborate with other IT squads to identify cross-domain AI use cases and integration opportunities

·       Support the preparation of governance documentation (Technical Design Documents, Architecture Decision Records) required for solution deployment

·       Support the squad Scrum Master and Product Owner in backlog refinement, effort estimation and sprint planning from a technical perspective

Technical & Behavioral Competencies

The ideal candidate is a hands-on engineer with strong software development fundamentals and a solid understanding of Generative AI concepts and tooling. They should demonstrate genuine curiosity and passion for AI and new technologies, staying up to date with the rapidly evolving GenAI landscape. We value engineers who can bridge the gap between innovation and enterprise-grade delivery — someone comfortable working with cutting-edge AI frameworks while respecting the governance and security constraints of a global banking institution. Experience in deploying AI solutions in a corporate or enterprise environment is highly valued but not mandatory.

Specific Qualifications:

·       5+ years of overall software engineering experience

·       At least 1 hands-on experience building or integrating a GenAI / AI-powered application in a professional context

·       Strong proficiency in Python (mandatory) for backend development and AI solution implementation

·       Working knowledge of RESTful API design, data modelling and system integration patterns

·       Familiarity with Generative AI concepts: LLMs, prompt engineering, RAG (Retrieval-Augmented Generation), fine-tuning, embeddings

·       Understanding of AI agent architectures and inter-agent communication protocols (e.g. MCP – Model Context Protocol)

·       Knowledge of containerization (Docker, Kubernetes) and CI/CD pipelines

·    &nb