Client: Our client is a Europe based organization and one of the world’s most established stock exchanges.
Position overview: We are looking for a Junior AI Developer to join a growing team building AI-driven solutions within a governed enterprise AI platform for the financial services industry. In this role, you will support the design of intelligent agents, develop reusable AI components, and integrate large language models (LLMs) with enterprise systems and data platforms, working closely with senior engineers and business stakeholders.
Technology stack: Python, LLMs (OpenAI, Anthropic, Azure OpenAI Service), RAG and AI agent frameworks, Azure cloud services (Azure AI Studio, Azure Machine Learning, Azure Functions, Azure Service Bus), SQL/Postgres and enterprise data platforms, REST APIs and microservices architecture, Docker and containerization, Jira, Confluence, Git repositories.
- Responsibilities: Contribute to the development of AI agents that automate workflows and support business decision-making.
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Build reusable, deterministic AI components and services under the guidance of senior engineers.
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Support integration with enterprise systems including databases, APIs, Jira, Confluence, and knowledge bases.
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Assist in implementing RAG-based solutions to produce accurate, grounded, and auditable outputs. Follow governance, security, permissioning, and audit standards as defined by the platform team.
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Collaborate with technical and business teams on solution design and contribute to architecture discussions.
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Participate in testing, optimization, and performance tuning of AI solutions. Contribute to secure and maintainable AI workflows and integrations.
- Requirements: Backend development experience with Python, including exposure to building or consuming APIs.
- Foundational knowledge of LLMs, AI agents, RAG systems, or ML-driven applications, including hands-on project or coursework experience.
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Familiarity with cloud platforms, preferably Azure.
- Basic understanding of data security, governance, and reliability principles.
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Ability to write clean, maintainable code and collaborate within a team environment.
- Good communication skills and a willingness to learn in a fast-moving technical domain.
- Nice to have: Exposure to financial services, enterprise data, or data-heavy domains is a plus.
- Interest in semantic data modeling or knowledge graphs. Any experience with workflow automation tools or rules engines.
- Awareness of enterprise AI governance and compliance considerations.
