AI engineer in industrial transformation

As a Senior AI Engineer, you will design, build, deploy, and continuously improve enterprise-grade AI applications that support critical business processes within the Transformation of Industry division.

• Design, develop, test, and deploy scalable, secure, and maintainable AI applications using Generative AI, Large Language Models, and Retrieval-Augmented Generation frameworks.
• Engineer production-ready AI services and reusable components using Python, REST APIs, FastAPI, and microservice-based architectures.
• Design end-to-end solution architectures that integrate AI capabilities with enterprise applications, data platforms, identity services, and business workflows.
• Develop cloud-native AI solutions across Microsoft Azure and Amazon Web Services, selecting appropriate services based on scalability, security, performance, operational, and cost requirements.
• Build and manage CI/CD pipelines for AI applications, model components, infrastructure, testing, and production releases.
• Apply software engineering practices such as modular design, automated testing, code reviews, observability, version control, secure coding, and technical documentation.
• Manage the full lifecycle of AI applications, from data ingestion and preprocessing through orchestration, API integration, deployment, monitoring, and ongoing optimization.
• Maintain, troubleshoot, and enhance existing AI solutions to ensure reliability, availability, performance, and business continuity.
• Implement appropriate guardrails, access controls, evaluation mechanisms, logging, and monitoring for enterprise AI applications.
• Collaborate with product managers, architects, data engineers, application teams, cybersecurity teams, and business stakeholders to translate business requirements into robust technical solutions.
• Lead technical design discussions, evaluate alternative architectures, and communicate engineering decisions, dependencies, risks, and trade-offs clearly.
• Mentor junior AI developers through technical coaching, pair programming, design guidance, code reviews, and structured knowledge sharing.
• Promote engineering standards and reusable patterns across AI development, MLOps, DevOps, cloud architecture, and secure software delivery.
• Research and assess emerging AI technologies, frameworks, and engineering approaches, and recommend their adoption where they provide measurable business or technical value.

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
• 8+ years of software engineering experience, with proven delivery of production-grade applications.
• 5+ years of hands-on experience designing, developing, and deploying AI/ML solutions, including Generative AI and Retrieval-Augmented Generation (RAG) architectures.
• Strong Python engineering skills and experience building scalable REST APIs and microservices using FastAPI or similar frameworks.
• Hands-on experience with both Microsoft Azure and Amazon Web Services (AWS), including AI, application, and cloud-native services.
• Experience with Docker, Kubernetes, CI/CD pipelines, and DevOps practices for deploying and operating enterprise applications.
• Good understanding of MLOps, AI observability, security, and operationalization of AI solutions.
• Experience working with Snowflake, SQL, APIs, data integration, vector databases, and enterprise application architectures.
• Ability to design scalable, secure, and maintainable software solutions with strong software engineering fundamentals.
• Proven experience mentoring junior engineers, conducting code reviews, and driving engineering best practices.
• Strong analytical, problem-solving, communication, documentation, and stakeholder-management skills.
• Ability to work within a globally distributed, cross-functional engineering environment.
• Будет плюсом: Experience with OpenShift and Terraform is a strong advantage

• Flexible and hybrid working environment
• Opportunities for continuous professional and personal development
• Collaborative and inclusive international work environment
• Access to learning, training, and knowledge-sharing opportunities
• Competitive local benefits
• Opportunities to work with innovative technologies and contribute to impactful projects