Senior Level AI Data Engineer Jobs
Senior level ai data engineer jobs place experienced professionals in charge of data platform architecture, end-to-end pipeline ownership, and the engineering teams that deliver production AI systems. Openings are concentrated across on-site, remote, and hybrid settings in Technology & Software, Banking & Financial Services, and Consulting & Professional Services, with employers like Apple, CVS Health, and JPMorganChase hiring at this level now.
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Showing 5 of 74+ Senior Level AI Data Engineer jobs
Position: Sr Data & AI Architect
Location: Auburn Hills, MI - 48326 (3-Days Onsite)
Duration: 4+ Months Contract
Note: Only Locals
Job Description:
Senior Data & AI Solutions Architect
• Define end-to-end architecture for AI-powered data solutions, including intelligent agents, automation workflows, and multi-agent ecosystems across enterprise platforms.
• Define collaboration frameworks supporting sequential, parallel, event-driven, conditional, and human-in-the-loop interactions.
• Translate business requirements and operational workflows into scalable data and AI solutions, integration, security, deployment, and operational architectures.
• Provide technical leadership across Architecture, Engineering, Security, Data, and Operations teams, establishing standards, governance frameworks, and reusable patterns.
• Define security architecture — authentication, authorization, identity propagation, and governance controls across all interaction layers.
• Establish responsible AI guardrails covering data privacy, prompt security, model safety, compliance, and human approval workflows.
• Define enterprise data architecture, integration strategies, canonical data models, API standards, and knowledge management frameworks.
• Define RAG or comparable approaches enabling secure access to structured and unstructured enterprise data.
• Drive data privacy, integration, and management practices for seamless, governed accessibility across platforms.
Technical Experience
• 10+ years in Solution, Enterprise, Cloud, or Data Integration Architecture.
• Strong cloud architecture experience (AWS/Azure/GCP) and experience integrating enterprise platforms (CRM, ERP, ITSM, or similar).
• Experience with data structures, enterprise tools, cloud hyperscalers and platforms leveraging AI for data management and governance.
• Strong understanding of Agentic AI, Conversational AI, Generative AI, and multi-agent architectures.
• Deep knowledge of APIs, event-driven architecture, identity protocols, canonical data models, security, and observability.
• Ability to translate business objectives into scalable technical architecture and implementation roadmaps.
• Strong stakeholder management, documentation, and executive communication skills.
• Experience in Effective Application Development Project Implementation / Deployment strategies with a customer base distributed throughout the world.
• Experience in highly parallel work environments with projects utilizing iterative, agile, and waterfall approaches to achieve their objectives.
• Experience in both business transformation and information technology projects is required.
Unique Skills
• Technical knowledge with hands-on experience, managing application development
• Strong verbal and written communications skills, with an ability to express complex technical concepts in business terms
• Strong analytical, problem-solving, and conceptual skills
• Strong interpersonal skills; ability to communicate and persuade at all management levels and thrive in a cross-functional environment
Position: Sr Data & AI Architect
Location: Auburn Hills, MI - 48326 (3-Days Onsite)
Duration: 4+ Months Contract
Note: Only Locals
Job Description:
Senior Data & AI Solutions Architect
• Define end-to-end architecture for AI-powered data solutions, including intelligent agents, automation workflows, and multi-agent ecosystems across enterprise platforms.
• Define collaboration frameworks supporting sequential, parallel, event-driven, conditional, and human-in-the-loop interactions.
• Translate business requirements and operational workflows into scalable data and AI solutions, integration, security, deployment, and operational architectures.
• Provide technical leadership across Architecture, Engineering, Security, Data, and Operations teams, establishing standards, governance frameworks, and reusable patterns.
• Define security architecture — authentication, authorization, identity propagation, and governance controls across all interaction layers.
• Establish responsible AI guardrails covering data privacy, prompt security, model safety, compliance, and human approval workflows.
• Define enterprise data architecture, integration strategies, canonical data models, API standards, and knowledge management frameworks.
• Define RAG or comparable approaches enabling secure access to structured and unstructured enterprise data.
• Drive data privacy, integration, and management practices for seamless, governed accessibility across platforms.
Technical Experience
• 10+ years in Solution, Enterprise, Cloud, or Data Integration Architecture.
• Strong cloud architecture experience (AWS/Azure/GCP) and experience integrating enterprise platforms (CRM, ERP, ITSM, or similar).
• Experience with data structures, enterprise tools, cloud hyperscalers and platforms leveraging AI for data management and governance.
• Strong understanding of Agentic AI, Conversational AI, Generative AI, and multi-agent architectures.
• Deep knowledge of APIs, event-driven architecture, identity protocols, canonical data models, security, and observability.
• Ability to translate business objectives into scalable technical architecture and implementation roadmaps.
• Strong stakeholder management, documentation, and executive communication skills.
• Experience in Effective Application Development Project Implementation / Deployment strategies with a customer base distributed throughout the world.
• Experience in highly parallel work environments with projects utilizing iterative, agile, and waterfall approaches to achieve their objectives.
• Experience in both business transformation and information technology projects is required.
Unique Skills
• Technical knowledge with hands-on experience, managing application development
• Strong verbal and written communications skills, with an ability to express complex technical concepts in business terms
• Strong analytical, problem-solving, and conceptual skills
• Strong interpersonal skills; ability to communicate and persuade at all management levels and thrive in a cross-functional environment
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Who's Hiring
Top Industries Hiring
- Technology & Software32
- Banking & Financial Services8
- Consulting & Professional Services7
- Insurance6
- Healthcare & Medical Services4
Senior Level AI Data Engineer Jobs: Frequently Asked Questions
How do I get a senior level ai data engineer job?
Employers at this level expect candidates who have owned data infrastructure decisions, not just contributed to them. Demonstrating that you have led the design of scalable pipelines, evaluated and selected tooling, mentored junior engineers, and delivered AI-ready data systems in production will set you apart. Strong communication with cross-functional stakeholders is equally important, since senior roles carry organizational accountability alongside technical depth.
Which companies hire senior level ai data engineers?
Companies hiring senior level ai data engineers right now include Apple, CVS Health, and JPMorganChase, based on current listings on Migrate Mate as of September 2026. Hiring at this level comes from a broad mix of enterprise technology firms, fast-scaling startups with mature data functions, and large organizations building or expanding their AI capabilities.
Are there remote senior level ai data engineer jobs?
Yes, remote and hybrid work is well established at this level. About 48% of senior level ai data engineer openings are remote or hybrid as of September 2026, reflecting how many organizations treat experienced data engineers as distributed contributors who can lead teams and architecture decisions without being on-site full time.
What makes a ai data engineer role senior level?
Senior roles are defined by ownership rather than execution. A senior ai data engineer sets the architectural direction for data platforms, makes independent decisions on tooling and design tradeoffs, and is accountable for the reliability and scalability of production systems. They also mentor and guide less experienced engineers, contribute to technical strategy, and are expected to operate with limited oversight across complex, ambiguous problems.
Which industries hire the most senior level ai data engineers?
Senior Level ai data engineer roles concentrate in Technology & Software, Banking & Financial Services, and Consulting & Professional Services, based on current listings on Migrate Mate as of September 2026. These sectors drive hiring because they operate at the intersection of large-scale data infrastructure and applied AI, where the cost of poor data architecture is highest and the demand for experienced technical leadership is most acute.