Senior AI Engineer

About the Role

Day-to-day, the Senior AI Engineer will work closely with cross-functional engineering teams to integrate AI capabilities into platform services, focusing on scalability, high-performance, and reliability. The role demands a strong understanding of RAG architectures, semantic retrieval workflows, and experience with cloud-native infrastructure.

As part of the team, the Senior AI Engineer will participate in architecture discussions, technical decision-making processes, and contribute to cloud-native infrastructure and deployment workflows. This includes supporting deployments in secure, air-gapped, or classified environments when required.

What You Will Do

• Design and develop scalable AI-powered backend systems for SysML-based engineering environments.
• Build and maintain distributed data ingestion and ETL pipelines for large-scale engineering artifacts and technical documentation.
• Develop and optimize LLM-powered workflows for metadata extraction, semantic analysis, and entity resolution.
• Implement AI agents and multi-agent orchestration workflows.
• Design and improve RAG-based architectures and semantic retrieval pipelines.
• Develop graph-based knowledge representation and traceability analysis solutions.
• Work with graph databases, graph processing libraries, and semantic relationship modeling.
• Build and optimize distributed data processing workflows using Apache Spark.
• Collaborate with cross-functional engineering teams to integrate AI capabilities into platform services.
• Design scalable and high-performance APIs and backend services.
• Improve system reliability, scalability, observability, and performance across distributed environments.
• Participate in architecture discussions and technical decision-making processes.
• Contribute to cloud-native infrastructure and deployment workflows.
• Support deployments in secure, air-gapped, or classified environments when required.
• Create and maintain technical documentation and engineering best practices.

What We Are Looking For

• At least 5 years of commercial experience in software engineering, Data Engineering, or AI systems development.
• Experience with Golang.
• Hands-on experience building distributed and scalable systems.
• Practical experience with LLM-based applications and AI integrations.
• Experience building AI agents and multi-agent systems.
• Strong understanding of RAG architectures and semantic retrieval workflows.
• Strong understanding of ETL pipelines and large-scale data ingestion workflows.
• Experience with cloud-native infrastructure and distributed environments.
• Practical experience with backend platform development and API integrations.
• Good understanding of semantic search, entity resolution, and metadata extraction.
• Experience working with highly scalable and high-performance systems.
• Strong problem-solving and communication skills.
• Upper-Intermediate level of English.

Nice to Have

• Background in Data Engineering.
• Experience with distributed data processing, Apache Spark, or Apache Beam.
• Experience with Knowledge Graphs and graph-based semantic modeling.
• Familiarity with MBSE or SysML environments.
• Experience supporting air-gapped or classified environments.
• Experience with vector databases and embedding pipelines.
• Experience with Kubernetes and cloud platforms such as AWS, GCP, or Azure.

Benefits and Perks

• Competitive salary package.
• Opportunity to work on cutting-edge AI-driven projects.
• Collaboration with a talented team of professionals.
• Flexible remote work arrangements across Europe, Ukraine, and LATAM.
• Professional development and growth opportunities.
• Access to the latest technologies and tools.
• Recognition and reward for outstanding performance.
• Comprehensive health insurance package.
• Generous paid time off policy.
• Remote work stipend to support your home office setup.

• Ensure your portfolio highlights specific examples of designing and developing scalable AI-powered backend systems, especially those related to SysML-based engineering environments.
• Familiarize yourself with the latest trends in AI, machine learning, and data engineering to stand out in your application and during interviews.
• Prepare to discuss your experience with distributed data processing, Apache Spark, and cloud-native infrastructure, as these are key to the role.
• Demonstrate strong problem-solving skills and the ability to communicate complex technical ideas clearly, as these are crucial for success in this position.
• Be ready to discuss your approach to building and maintaining distributed data ingestion and ETL pipelines, and how you optimize LLM-powered workflows.
• Show enthusiasm for working in a collaborative environment and contributing to the development of innovative AI-driven solutions.