Application AI Engineer

Description

The company is a global team across 40 locations building AI agents, intelligent tools, and the cloud infrastructure to scale them.

The e-invoicing localization team sits within the company's Globalization AI unit and is in an active build phase. Its current work applies AI to coding, research, automation, and software design to speed up compliant solutions for markets worldwide.

Learning, coaching, and knowledge sharing are central to how the team works. The company has built enterprise applications for over 50 years.

Responsibilities

• Build and run AI-powered backend services, APIs, and agent tools in Python, designed for reliability, scalability, and observability.
• Create RAG systems and agentic workflows that draw on trusted enterprise knowledge, and improve prompts, retrieval quality, output handling, and user experience.
• Connect AI capabilities to the company's AI assistant, ServiceNow, its cloud platform services, and other enterprise systems.
• Write and maintain automated tests, evaluation pipelines, and benchmarks that measure the quality and performance of AI systems.
• Turn validated experiments and proofs of concept into production-ready capabilities, and keep up with new models, frameworks, and protocols.
• Own features and modules from start to finish, working with product managers, engineers, and domain specialists, and share technical knowledge so other teams can adopt AI-assisted engineering.

Requirements

• Fluency in English is required.
• A degree in computer science, engineering, or a related field, or equivalent practical experience.
• Hands-on Python and backend work, including APIs and async programming, plus a solid grasp of REST, distributed systems, and data modelling.
• Hands-on work with LLM applications, RAG, tool calling, or agentic workflows, or clear self-directed learning in these areas, with exposure to frameworks such as FastAPI or LangGraph.
• Experience building and operating cloud-based applications or microservices, including Docker, Kubernetes, CI/CD, automated testing, and secure service integration.
• Solid communication skills, a collaborative style, and the creative thinking and learning agility to adapt as the role changes.
• A genuine interest in building AI-powered products, and a record of following AI's fast progress and using AI-assisted tools and context engineering, shown through delivered projects, prototypes, research, or open-source contributions.
• A practical, accountable approach to AI: use AI-assisted tools, context engineering, and automation to build better solutions, and take responsibility for the quality, safety, and alignment of AI-generated output.

Conditions

Successful candidates may be required to pass a background verification carried out by an external vendor.

The company's guidelines on ethical AI use in recruitment apply, and violating them may lead to disqualification from the hiring process.

The company is committed to equal employment opportunity and offers accommodations to applicants with physical or mental disabilities.

Benefits

• Under the company's referral policy, the employee referral program covers permanent roles only.