Senior AI Backend Software Engineer

Our customer operates in the AdTech 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.

You will join an international cross-functional team of engineers, AI specialists, and product experts collaborating across multiple locations to build scalable, high-impact solutions for complex engineering environments.

• Interview process that respects people and their time
• Professional and open IT community
• Internal meet-ups and resources for knowledge sharing
• Time for recovery and relaxation
• Bright online and offline events
• Opportunity to become part of our internal volunteer community

• 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 pipeline
• 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

• 5+ years of commercial experience in software engineering, backend development, data engineering, or AI systems development

• Strong hands-on experience with Python

• Practical experience building or integrating LLM-based applications

• Hands-on experience with graph technologies, graph libraries, and graph databases

• Good understanding of RAG architectures, semantic retrieval, embeddings, and vector search

• Experience with AI agents, agentic workflows, tool-calling, or multi-step AI orchestration

• Experience building backend services, APIs, integrations, or platform components

• Understanding of data ingestion, ETL/ELT workflows, and large-scale data processing concepts

• Experience with SQL and relational databases

• Good understanding of distributed systems and scalable architecture

• Experience working with cloud environments such as AWS, GCP, or Azure

• Strong engineering mindset: clean code, ownership, reliability, and maintainability

• Willingness to work with Go and/or Scala as part of the production ecosystem

• Strong problem-solving and communication skills

• Upper-Intermediate English or higher

  WILL BE A PLUS

• 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

  Personal Profile

• Analytical mindset with strong problem-solving skills

• Ability to work independently and in a distributed team

• Adaptability to secure and classified environments

• Strong communication and collaboration abilities

• Passion for AI-driven engineering solutions