6 infrastructure engineer jobs found

Basic Qualifications Requires a Bachelor’s degree in Software Engineering, or a related Science, Engineering, Technology or Mathematics field. Also requires 8+ years of job-related experience, or a Master's degree plus 6 years of job-related experience. Agile experience preferred.     CLEARANCE REQUIREMENTS: : Department of Defense Secret security clearance is required at time of hire. Applicants selected will be subject to a U.S. Government security investigation and must meet eligibility requirements for access to classified information. Due to the nature of work performed within our facilities, U.S. citizenship is required. Responsibilities for this Position ROLE AND POSITION OBJECTIVES: Intelligent Data Management: Use AI tools to analyze, map, and automate the data migration from the existing workflows and systems Design modern, flexible data architectures, not locked to legacy patterns Leverage AI to detect...

Basic Qualifications Bachelor's degree in Software Engineering, or related Science, Technology, Engineering or Mathematics field, plus a minimum of 8 years of relevant experience; or Master's degree, plus 6 years relevant experience. Responsibilities for this Position What You'll Own Production AI services. Build and deploy agentic workflows, RAG pipelines, and LLM-integrated applications using Python, LangChain/LangGraph, and commercial foundation models (Claude, Codex, Gemini, open source). Data-to-insight pipelines. Implement document ingestion workflows that transform unstructured enterprise data into structured models for AI reasoning — embeddings, vectorization, knowledge graphs. API integration. Design and build secure API interfaces that connect AI services to internal tools, enterprise platforms (Oracle, IFS, Snowflake, PLM, MES, CRM), and data sources. Deployment and reliability. Containerize and deploy AI services...

Basic Qualifications Bachelor's degree in Software Engineering, or related Science, Technology, Engineering or Mathematics field, plus a minimum of 8 years of relevant experience; or Master's degree, plus 6 years relevant experience. Responsibilities for this Position What You'll Own SLOs and reliability metrics. Define service level objectives for every AI service that goes to production. Establish error budgets and use them to drive engineering decisions — not just measure uptime. Monitoring and observability. Build and maintain monitoring, logging, and alerting infrastructure for AI services. You will know when something is degrading before users do. Incident response. Establish incident management procedures, lead post-incident reviews, and drive corrective actions. When something breaks, you coordinate the response and ensure it doesn't break the same way again. Operational readiness reviews. Before any AI service goes...

Basic Qualifications Bachelor's degree in Systems Engineering, or a related Science, Engineering or Mathematics field, plus a minimum of 8 years of relevant experience; or Master's degree, plus a minimum of 6 years of relevant experience. Responsibilities for this Position What You'll Own Enterprise knowledge architecture. Define and maintain the overarching structure that connects domain-specific ontologies across pods. Manage the relationships between business vocabularies, taxonomies, and data models at the enterprise level. Cross-domain consistency. Ensure that business concepts defined in one pod are compatible with concepts in other pods. Resolve naming conflicts, semantic overlaps, and definitional inconsistencies before they become integration problems. Metadata and tagging standards. Establish enterprise-wide standards for metadata, tagging, classification, and search structures. Build the knowledge infrastructure...

Basic Qualifications Bachelor's degree in Software Engineering, or related Science, Technology, Engineering or Mathematics field, plus a minimum of 8 years of relevant experience; or Master's degree, plus 6 years relevant experience. Responsibilities for this Position What You'll Own Production AI services. Build and deploy agentic workflows, RAG pipelines, and LLM-integrated applications using Python, LangChain/LangGraph, and commercial foundation models (Claude, Codex, Gemini, open source). Data-to-insight pipelines. Implement document ingestion workflows that transform unstructured enterprise data into structured models for AI reasoning — embeddings, vectorization, knowledge graphs. API integration. Design and build secure API interfaces that connect AI services to internal tools, enterprise platforms (Oracle, IFS, Snowflake, PLM, MES, CRM), and data sources. Deployment and reliability. Containerize and deploy AI...

Basic Qualifications Requires a Bachelor’s degree in Software Engineering, or a related Science, Engineering, Technology or Mathematics field. Also requires 5+ years of job-related experience, or a Master's degree plus 3 years of job-related experience. Agile experience preferred.     Due to the nature of work performed within our facilities, U.S. citizenship is required. Responsibilities for this Position What You'll Do: - Conduct code reviews across the platform codebase. You will review pull requests thoroughly, provide clear and constructive feedback, and help maintain code quality standards. - Build and maintain integrations with enterprise systems including SharePoint (via Microsoft Graph API), GitLab, EPDM, and internal Hub services. - Develop and maintain LLM API integrations across multiple providers. - Build and maintain RAG pipelines: document ingestion, parsing, chunking, embedding generation, vector database...