Senior Machine Learning Engineer I (Finance)

About this role

The Senior Machine Learning Engineer I sits in the Finance Transformation team in IT at CP Axtra, building and operating AI/LLM-powered features that automate and augment finance processes across Makro and Lotus's. The role requires strong engineering fundamentals, hands-on experience deploying AI features into production, and the ability to work with Finance and cross-functional teams. It does not focus on developing custom ML models, but deep technical proficiency and system-level thinking are essential.

Responsibilities

• AI and LLM Evaluation
• •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.
• System and Backend Development
• •Build and maintain backend services and APIs that integrate LLMs or AI workflows with finance systems such as Oracle Fusion.
• •Architect scalable systems supporting chat interfaces, retrieval pipelines, classification tools, or finance workflow automation.
• •Implement solid software engineering practices: testing, versioning, error handling, observability, and performance optimization.
• •Ensure robust integration with internal systems, data services, and production infrastructure.
• AI Application Engineering
• •Work on features powered by LLMs such as RAG systems, finance copilots, document intelligence for invoices/contracts, and intelligent automation.
• •Implement embeddings, document retrieval layers, vector search, caching, and fallback logic.
• •Collaborate with platform teams on deployment, API management, and resource optimization.
• Operations and Reliability
• •Monitor AI features in production and proactively address model drift, latency issues, and failure patterns.
• •Maintain evaluation logs, experiment results, and version control for AI workflows.
• •Work with DevOps to manage CI/CD pipelines, container deployment, and runtime environments.
• Collaboration and Delivery
• •Partner 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.
• •Produce clear documentation on workflows, system design, evaluation methods, and application behavior.

Requirements

• 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.
• Hands-on experience with vector databases, embeddings, or retrieval-based architectures.
• Strong problem-solving skills and the ability to evaluate AI model behavior systematically.
• Experience with Docker, Kubernetes, CI/CD pipelines, and cloud environments.
• Preferred
• Experience building or maintaining RAG systems, chat systems, or AI automation workflows.
• Familiarity with observability tools (logging, tracing, monitoring) in production environments.
• Experience working with Airflow, Prefect, or orchestration frameworks.
• Knowledge of data pipelines, ETL workflows, or integration with ERP systems such as Oracle Fusion.
• Domain knowledge in finance, retail, loyalty, process automation, or enterprise systems.

Benefits

• International workplace
• Opportunities for growth in e-commerce, wholesales, and retail industry

- Competitive benefits

• Fast-paced, dynamic, and supportive environment