Software Engineer, GenAI Solutions

Why Keyrus, Why Now

Keyrus is an international group of 3,000 experts across 30 countries, built on a single conviction: AI does not transform businesses. Architected intelligence does.

For more than 30 years, we have been building the data foundations that make intelligent systems work, designing the Operating System of the intelligent enterprise, where intelligence is embedded into the core of business processes to create sustainable value: we operationalize intelligence.

As AI becomes part of everyday business operations, organizations need more than intelligent models. They need reliable applications, secure integrations, and production-ready software that connects AI capabilities with real business processes.

At Keyrus, you will help turn intelligent capabilities into scalable applications that people and organizations can use with confidence.

Technology amplifies. Keyrus culture differentiates. Industrial discipline connects the two.

What you'll architect

As a Software Engineer, AI Applications, you will design, develop, and maintain production-ready software applications that integrate AI capabilities into enterprise systems and business workflows.

Your primary focus will be software engineering, building reliable backend services, APIs, integrations, and application components that support AI-enabled solutions.

You will collaborate with AI Engineers, Data Engineers, Architects, and client teams to transform technical requirements into secure, scalable, and maintainable applications.

Your responsibilities

• Design, develop, test, and maintain production software applications, backend services, and APIs that support enterprise and AI-enabled solutions.
• Integrate AI services, LLM APIs, enterprise applications, databases, and external systems into reliable business workflows.
• Build secure and scalable application components, considering performance, authentication, error handling, and maintainability.
• Implement automated testing, CI/CD pipelines, monitoring, and software engineering practices to ensure production reliability.
• Troubleshoot application issues, optimize performance, and support deployment and ongoing improvements.
• Collaborate with AI Engineers, Data Engineers, and Architects to implement integrations and reusable software components.
• Work closely with clients to understand technical requirements, discuss implementation options, and deliver solutions aligned with business needs.

Who you are

You are a hands-on Software Engineer who enjoys building reliable applications and solving complex technical challenges.

You understand that integrating AI into business applications requires strong software engineering foundations, including secure APIs, reliable integrations, testing, and production operations.

You combine technical expertise with practical problem-solving and enjoy collaborating with multidisciplinary teams to deliver solutions that create real business value.

What you bring

Experience

• Strong hands-on experience developing, integrating, and maintaining production software applications, particularly backend services and APIs.
• Experience designing enterprise integrations and connecting applications with databases, cloud services, and external systems.
• Experience applying software engineering practices, including testing, version control, CI/CD, and production monitoring.
• Understanding of application security, scalability, performance, and maintainability in production environments.
• Strong communication skills, with the ability to explain technical concepts clearly, collaborate with stakeholders, and build relationships with clients and internal teams.

Technical skills

• Strong programming skills in at least one backend ecosystem, such as Java/Spring, Python/FastAPI, Node.js/TypeScript, .NET/C#, or Go.
• Experience designing and developing REST APIs, backend services, and enterprise application integrations.
• Hands-on experience with databases, data access patterns, and application-level data processing.
• Experience with at least one major cloud platform, such as AWS, Azure, or GCP.
• Knowledge of Git, automated testing, CI/CD, authentication, application security, and production software engineering practices.

Nice to have

• Experience integrating LLM APIs or AI services into enterprise applications, including OpenAI, Anthropic, Azure AI, or comparable technologies.
• Familiarity with RAG, AI agents, tool calling, and AI-enabled application workflows.
• Experience with Docker, Kubernetes, microservices, or distributed application architectures.
• Experience with event-driven systems, messaging plat