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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in architecting and designing AI solutions, integrating cloud and on-premises data architectures, and optimizing AI/ML workflows. Proficient in collaborating with stakeholders to translate business needs into scalable, secure, and compliant technical solutions.
Highest-signal resume keywords
Artificial Intelligence (AI)Machine Learning (ML)Cloud ArchitectureData GovernanceAI Solution Design
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data ArchitectureAI Model DevelopmentData VisualizationMLOpsGenerative AIDeep LearningWorkflow OrchestrationSemantic ModelingAPI IntegrationEvent-Driven Architecture
Soft Skills
CommunicationCollaborationStakeholder EngagementTechnical GuidanceProblem Solving
Tools & Technologies
ML PlatformsVector DatabasesOrchestration PlatformsData Cataloging ToolsDecision-Support Tools
Industry Keywords
Supply ChainLogisticsAerospaceOperational EnvironmentsData Security
Tech Stack
Tools & technologiesCloud
About the role
Key responsibilities & impact- Lead the architecture and design of end-to-end AI solutions supporting Boeing Global Services business needs
- Define solution architectures integrating on-premises and cloud-based data, analytics, and AI capabilities into scalable enterprise patterns
- Translate business requirements into technical designs for AI-enabled solutions
- Architect the full solution lifecycle from raw data and governed data products through data modeling, ontology, AI model development, orchestration, and visualization
- Design solutions using machine learning, generative AI, Agentic AI, deep learning, optimization, and other advanced AI techniques
- Partner with business stakeholders to identify high-value use cases and shape feasible technical solutions
- Collaborate with data engineers, data scientists, software engineers, platform architects, and product teams
- Define patterns for data ingestion, transformation, semantic modeling, ontology design, AI model integration, workflow orchestration, and user experience delivery
- Ensure solutions are scalable, maintainable, secure, and aligned with Boeing architecture, cyber, governance, and compliance standards
- Evaluate technical tradeoffs across cloud, hybrid, and on-premises environments and recommend best-fit architectures
- Provide architectural guidance throughout design, build, testing, deployment, monitoring, and enhancement phases
- Support reusable frameworks, reference architectures, and patterns for AI solutions
- Work with front-end and product teams to deliver insights and AI outputs through interfaces, dashboards, copilots, or decision-support tools
- Help define ontology and semantic-layer approaches for supply chain data
- Participate in technical governance, design reviews, and architecture decision forums
- Support production readiness, performance tuning, observability, and operational support for deployed AI solutions
- Stay current on emerging AI technologies and recommend innovations that improve performance and business value
Requirements
What you’ll need- 10+ years of experience with Artificial Intelligence (AI) and Machine Learning (ML) technologies, including integrating AI-driven insights into data architecture and analytics processes
- 10+ years of experience with Information Technology architecture, including cloud and data architecture in large-scale hybrid cloud and on-premises environments
- 10+ years of experience communicating with technical experts and explaining difficult technical concepts to non-technical business users
- 10+ years of experience working across organizations and interfacing with key stakeholders, including senior leaders
- 5+ years of experience designing, developing, and optimizing AI/ML solutions, data science workflows, and analytics methodologies
- 5+ years of experience with AI/ML and generative AI lifecycle concepts, including model development, evaluation, deployment, monitoring, change management, documentation, and data governance
- Experience architecting AI solutions for supply chain, logistics, inventory, planning, sourcing, or parts domains
- Experience with ML platforms, MLOps, LLM orchestration, vector databases, retrieval-augmented generation, and model lifecycle management
- Experience designing semantic layers, ontologies, knowledge graphs, or enterprise data models
- Experience with Agentic AI, workflow automation, or AI-based decision support solutions
- Experience with data visualization tools, orchestration platforms, and front-end delivery patterns
- Experience with enterprise data governance, cataloging, lineage, and security frameworks
- Experience with event-driven architecture, API-based integration, and scalable cloud-native design
- Strong understanding of data architecture, APIs, integration patterns, and production engineering concepts
- Experience supporting industrial, aerospace, or similarly complex operational environments
- U.S. Person required to meet U.S. export control compliance requirements
- Employer will not sponsor applicants for employment visa status
- Successful candidates must satisfy the Company’s Conflict of Interest (COI) assessment process
- Post-offer applicants and employees may be subject to drug and alcohol testing when policy criteria are met
Benefits
Comp & perks- Competitive base pay
- Variable compensation opportunities
- Health insurance
- Flexible spending accounts
- Health savings accounts
- Retirement savings plans
- Life insurance programs
- Disability insurance programs
- Paid time away from work
- Unpaid time away from work
- Relocation based on candidate eligibility