Senior AI Engineer

Design and develop scalable AI-powered backend systems for SysML-based engineering environmentsBuild and maintain distributed data ingestion and ETL pipelines for large-scale engineering artifacts and technical documentationDevelop and optimize LLM-powered workflows for metadata extraction, semantic analysis, and entity resolutionImplement AI agents and multi-agent orchestration workflowsDesign and improve RAG-based architectures and semantic retrieval pipelinesDevelop graph-based knowledge representation and traceability analysis solutionsWork with graph databases, graph processing libraries, and semantic relationship modelingBuild and optimize distributed data processing workflows using Apache SparkCollaborate with cross-functional engineering teams to integrate AI capabilities into platform servicesDesign scalable and high-performance APIs and backend servicesImprove system reliability, scalability, observability, and performance across distributed environmentsParticipate in architecture discussions and technical decision-making processesContribute to cloud-native infrastructure and deployment workflowsSupport deployments in secure, air-gapped, or classified environments when requiredCreate and maintain technical documentation and engineering best practicesAt least 5 years of commercial experience in software engineering, Data Engineering, or AI systems developmentExperience with GolangHands-on experience building distributed and scalable systemsPractical experience with LLM-based applications and AI integrationsExperience building AI agents and multi-agent systemsStrong understanding of RAG architectures and semantic retrieval workflowsStrong understanding of ETL pipelines and large-scale data ingestion workflowsExperience with cloud-native infrastructure and distributed environmentsPractical experience with backend platform development and API integrationsGood understanding of semantic search, entity resolution, and metadata extractionExperience working with highly scalable and high-performance systemsStrong problem-solving and communication skillsUpper-Intermediate level of EnglishWILL BE A PLUSBackground in Data EngineeringExperience with distributed data processing, Apache Spark, or Apache BeamExperience with Knowledge Graphs and graph-based semantic modelingFamiliarity with MBSE or SysML environmentsExperience supporting air-gapped or classified environmentsExperience with vector databases and embedding pipelinesExperience with Kubernetes and cloud platforms such as AWS, GCP, or AzurePERSONAL PROFILEAnalytical mindset with strong problem-solving skillsAbility to work independently and in a distributed teamAdaptability to secure and classified environmentsStrong communication and collaboration abilitiesPassion for AI-driven engineering solutionsAre you a Senior AI 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.CUSTOMEROur 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.PROJECTWe 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.Originally posted on Himalayas