Senior AI Engineer

About the Position

Senior AI Engineer

Join Sigma Software as a Senior AI Engineer to work on a cutting-edge platform that transforms how large-scale engineering organizations manage and analyze complex technical data. This is a remote position with flexible locations across Europe, Ukraine, and LATAM.

At Sigma Software, we value expertise, creativity, and collaboration. You will work with advanced technologies, contribute to mission-critical projects, and be part of a company recognized for excellence and innovation.

Responsibilities

• 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

Requirements

• 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

We Offer

• Flexible locations across Europe, Ukraine, and LATAM
• Remote work options
• Opportunity to work with cutting-edge technologies
• Be part of a recognized company for excellence and innovation
• Competitive salary (details not provided)
• Professional development opportunities
• Flexible work schedule
• Remote work
• Stylish and comfortable office (option to choose work location)
• Sports events and communities

About the Company

Our customer operates in the EdTech industry, delivering advanced technology solutions that optimize advertising performance and audience targeting. While the name is confidential, the organization is known for leveraging cutting-edge AI and data-driven strategies to enhance campaign effectiveness and deliver measurable business impact.

We are developing a next-generation AI-powered Knowledge Base and Gap Analysis platform for SysML-based engineering environments. The system enables large-scale engineering organizations to ingest, structure, analyze, and reason over complex MBSE artifacts and technical documentation. It supports both cloud and secure classified environments, improving traceability, identifying gaps, and enhancing decision-making in mission-critical projects.