Senior Machine Learning Engineer I (Finance)

The Senior Machine Learning Engineer I works within the Finance Transformation team at CP Axtra. The role involves building and operating AI and LLM-powered features to automate and augment finance processes across Makro and Lotus's. Key duties include evaluating large language models for accuracy and reliability, designing evaluation frameworks, and implementing quality guardrails for sensitive financial data. The engineer will also build backend services and APIs that integrate LLMs with finance systems like Oracle Fusion, architect scalable systems for chat interfaces and retrieval pipelines, and monitor AI features in production to address model drift and latency issues. The position requires strong engineering fundamentals, experience deploying AI features into production, and the ability to collaborate with Finance and cross-functional teams.

Evaluate large language models and AI services for accuracy, reliability, safety, latency, and business suitability on finance use cases.

Design structured evaluation frameworks, test cases, and benchmarking methodologies.

Conduct prompt testing, retrieval validation, and failure-mode analysis.

Implement quality guardrails, safety filters, and monitoring for LLM applications handling sensitive financial data.

Build and maintain backend services and APIs that integrate LLMs or AI workflows with finance systems such as Oracle Fusion.

5 to 8 years of experience in software engineering, ML engineering, or AI engineering.

Strong proficiency in Python and experience designing production-grade backend services.

Proven experience deploying AI or LLM-based applications into production environments.

Solid understanding of system design, distributed systems, APIs, and microservices.

Experience with LLM tooling such as Azure OpenAI, ChatGPT, or similar platforms.

Collaborate with product owners, Finance teams, and engineering teams to convert requirements into reliable AI solutions. Provide technical guidance on feasibility, architecture choices, and operational trade-offs.