Sigma Software
AdTech
SeniorBackendEngineer
Neural analysis suggests this role is
optimal for mid candidates.
“Senior Backend Engineer at Sigma Software. Skills: AI-powered backend systems, distributed data ingestion and ETL pipelines, LLM-powered workflows, AI agents and multi-agent orchestration, RAG-based architectures and semantic retrieval, graph-based knowledge representation and traceability analysis, distributed data processing using Apache Spark, scalable and high-performance APIs and backend services, cloud-native infrastructure and deployment workflows. Design and develop scalable AI-powered b”
What You'll Achieve.
transform how large-scale engineering organizations manage and analyze complex technical data; deliver impactful solutions; optimize advertising performance and audience targeting; enhance campaign effectiveness and deliver measurable business impact; improving traceability, identifying gaps, and enhancing decision-making in mission-critical projects
Industry & Context.
problem-solving and communication skills; Analytical mindset with problem-solving skills
Support deployments in secure, air-gapped, or classified environments when required, Adaptability to secure and classified environments
What They're Looking For.
Must Have
At least 5 years of commercial experience in software engineering, Data Engineering, or AI systems development, Experience with at least one statically typed programming language like Java, Rust, Scala or Go., 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, understanding of RAG architectures and semantic retrieval workflows, Hands-on experience with graph technologies, graph libraries, or graph databases, 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, problem-solving and communication skills, Upper-Intermediate level of English
Nice to Have
Background in Data Engineering, Experience with Apache Spark and distributed data processing, 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
What You'll 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
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
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
or classified environments when required
Create and maintain technical documentation and engineering best practices
How You'll Work.
Team & Collaboration
Collaborate with cross-functional engineering teams to integrate AI capabilities into platform services; Ability to work independently and in a distributed team; communication and collaboration abilities
Communication Scope
problem-solving and communication skills; communication and collaboration abilities
Full Job Description
Are you a Senior Backend Engineer passionate about building scalable AI-driven systems? Join us at Sigma Software 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. You will be part of an innovative team leveraging AI, semantic graphs, and distributed processing to deliver impactful solutions. At Sigma Software, we value expertise, creativity, and collaboration. Why join us? You will work with advanced technologies, contribute to mission-critical projects, and be part of a company recognized for excellence and innovation. CUSTOMER 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. PROJECT 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. * 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-ba
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