Junior AI Engineer developing agentic systems for AI fintech solutions in healthcare. Collaborating in agile team to create impactful and innovative AI applications.
About the role
- Intermediate AI Developer at Nuclear Promise X designing AI solutions. Focused on Microsoft Azure and enhancing efficiency in the nuclear sector's workflows.
Responsibilities
- Design and develop AI-powered solutions using Microsoft Azure services, including OpenAI, Cognitive Search, Vision, Document Intelligence, and Cosmos DB for vector storage.
- Build and iterate on retrieval-augmented generation (RAG) pipelines and knowledge-grounded architectures, including GraphRAG and emerging techniques like OmniRAG.
- Rapidly prototype AI applications tailored to specific client needs, such as document digitization, data vectorization, and content generation workflows.
- Contribute to the architecture and implementation of advanced AI systems, including agent-based orchestration and integration with modern APIs and platforms.
- Prepare and structure training data, including labeled inputs for both text and image-based models, with a focus on production readiness and model performance.
- Evaluate and adopt new tools and frameworks based on AI/ML advancements, ensuring that implementations are stable and scalable.
- Collaborate across teams to deliver high-impact, cloud-native applications using Python (especially Azure's AI SDK). Exposure to JavaScript/TypeScript or Node.js is considered an asset.
Requirements
- 8–15 years of relevant experience in software or AI/ML development.
- Strong hands-on experience with Microsoft Azure AI services, including OpenAI, AI Search, Vision, Document Intelligence, and Cosmos DB.
- Proven ability to develop and deploy retrieval-based AI solutions using RAG pipelines, knowledge graphs, and related architectures.
- Demonstrated skill in rapidly building and iterating AI prototypes based on client requirements.
- Strong Python development skills, with experience using Azure’s AI SDK.
- Experience designing and implementing AI solution architectures, including agent-based systems and orchestration tools.
- Awareness of current and emerging AI/ML research, with the ability to assess production readiness.
- Exposure to front-end or full-stack development (JavaScript/TypeScript, Node.js) is an asset.
- Familiarity with engineering or technical documentation (e.g., schematics, diagrams) is considered an asset.
- Ability to independently structure and label data for AI training pipelines.
Benefits
- Tools and support for mental wellness, professional growth, and financial security.
- Health coverage, a spending account, and the freedom to rest and recharge.
- Meaningful work, alignment with your values, and time to refresh with flexible time off.
- Competitive pay and recognition for the impact you make.
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