AI Platform Chief Architect

Jobtailor; California (MO); On-site; USD 140,000 - 210,000; Full time

Job summary

Jobtailor seeks a seasoned Enterprise Architect to shape the AI/ML platform strategy across hybrid cloud environments. You will define standards, drive architecture convergence, and partner with executives to deliver measurable business outcomes, ensuring security and governance across initiatives.

Own end‑to‑end architectural direction, establish guardrails, and mentor engineers while aligning portfolio roadmaps with risk, cost, and performance goals.

Qualifications

• Bachelor's degree or equivalent work experience.
• 10+ years of software engineering experience.
• 6+ years of experience leading multiple software engineering teams.
• Extensive experience leading enterprise/ platform architecture in complex organizations.
• Proven ability to set architectural vision, define standards, govern decisions, and influence strategy.
• Deep expertise in distributed systems, cloud-native architecture, data platforms, API/service integration, security architecture, and production operations.
• Strong understanding of AI/ML platform architecture, model integration patterns, responsible AI considerations, and data‑driven systems.
• Demonstrated success leading across engineering, product, data, security, risk, compliance, and operations teams without direct authority.
• Excellent executive communication skills, including explaining complex tradeoffs clearly.
• Experience establishing or maturing an enterprise architecture function or architecture review board.
• Experience with regulated, data‑sensitive, or highly governed environments.
• Familiarity with architecture frameworks, decision records, road mapping, and debt management.
• Experience shaping enterprise AI, GenAI, RAG, or intelligent automation strategies.
• Relevant architecture or cloud certifications such as TOGAF, AWS Certified Solutions Architect or Azure Solutions Architect.

Responsibilities

• Define and maintain enterprise architecture vision, principles, and reference architectures.
• Establish architecture standards to promote reuse, interoperability, and security.
• Drive architecture convergence across teams to reduce fragmentation and debt.
• Partner with senior leaders to align roadmaps with business outcomes.
• Own end-to-end architectural direction for AI/ML platform capabilities.
• Define production-grade patterns for observability and governance.
• Ensure platform supports secure onboarding across DEV/UAT/PROD with guardrails.
• Guide platform investments balancing innovation, risk, and cost.
• Lead architecture strategy across hybrid and multi-cloud ecosystems.
• Define patterns for secure data access, API management, and event-driven flows.
• Assess tech options and vendor choices balancing standards and cost.
• Ensure architectures meet security, compliance, resiliency, and performance.
• Lead architecture community of practice and governance forums.
• Provide technical stewardship across domains to resolve cross-platform deps.
• Coach architects and engineers to raise architectural maturity.
• Represent architecture in executive governance forums.
• Define architecture guardrails for privacy, governance, and data protection.
• Identify and manage architectural risk across platforms and operations.
• Translate complex choices into executive recommendations and tradeoffs.
• Influence stakeholders to align on priorities and roadmap sequencing.
• Advise leadership on platform strategy, modernization, and vendor decisions.
• Drive alignment between architecture strategy and delivery plans.

Skills

Architectural leadership

Distributed systems

Cloud-native

AI/ML architecture

Data governance

Security architecture

Stakeholder management

Executive communication

Roadmap governance

Technical debt

TOGAF certification

Cloud certifications

Education

Bachelor's degree or equivalent

Job description

Responsibilities

• Define and maintain the enterprise architecture vision, principles, reference architectures, and decision frameworks for AI/ML platforms and adjacent technology domains.
• Establish architecture standards that promote reuse, interoperability, resiliency, security, and speed‑to‑market across products, platforms, and shared services.
• Drive architecture convergence across teams to reduce fragmentation, duplicate capabilities, technical debt, and long‑term operational cost.
• Partner with senior technology and business leaders to ensure architecture roadmaps directly support strategic priorities and measurable business outcomes.
• Own the end‑to‑end architectural direction for enterprise AI/ML platform capabilities, including model integration, inference services, retrieval patterns, orchestration, and automation.
• Define production‑grade patterns for observability, scalability, model/data traceability, policy enforcement, and responsible AI controls.
• Ensure platform capabilities can support secure onboarding of AI/ML use cases across DEV, UAT, and PROD environments with clear guardrails and repeatable patterns.
• Guide platform investment decisions by balancing innovation, risk, cost, operational complexity, and business value.
• Lead enterprise architecture strategy across hybrid and multi‑cloud ecosystems, including Azure, AWS, on‑premises services, data platforms, integration layers, and shared platform capabilities.
• Define architectural patterns for secure data access, service integration, API management, event‑driven flows, workload placement, and cost‑aware scaling.
• Assess technology options and vendor/platform choices, making recommendations that balance enterprise standards, delivery velocity, security posture, and total cost of ownership.
• Ensure solution architectures align to enterprise security, compliance, resiliency, performance, and operational support requirements.
• Lead the architecture community of practice, establishing forums, review mechanisms, and decision processes that improve consistency without slowing delivery.
• Provide senior technical stewardship across domains, resolving complex cross‑platform dependencies and ensuring end‑to‑end solution integrity.
• Coach and mentor architects, senior engineers, and technical leaders to raise architectural maturity and systems‑thinking capability across the organization.
• Represent architecture in executive, risk, compliance, product, and engineering governance forums.
• Define architecture guardrails for security, privacy, compliance, data protection, model governance, auditability, and responsible AI.
• Identify and manage architectural risk across platforms, integrations, dependencies, and production operations.
• Ensure risk decisions are clearly documented, communicated, and aligned with enterprise control expectations.
• Translate complex architecture choices into clear executive‑level recommendations, tradeoffs, risk implications, and investment options.
• Influence senior stakeholders across business, product, technology, security, and operations to align on enterprise architecture priorities and roadmap sequencing.
• Serve as a trusted advisor to technology leadership on platform strategy, modernization, vendor decisions, emerging technologies, and long‑term capability planning.
• Drive alignment between architecture strategy, portfolio funding, delivery execution, and measurable business outcomes.
• Establish architecture‑led operating mechanisms that improve transparency, dependency management, delivery predictability, and production readiness.
• Partner with engineering and platform leaders to ensure architectural decisions are reflected in backlogs, roadmaps, delivery plans, and operational support models.
• Promote disciplined use of Agile practices, Jira hygiene, architecture decision records, structured status reporting, and issue escalation paths.
• Hold teams accountable for solution quality, resiliency, performance, lifecycle ownership, and timely resolution of architectural risks.

Requirements

• Bachelor's degree, or equivalent work experience
• 10 or more years of relevant software engineering experience
• Six or more years of experience leading multiple software engineering teams
• Extensive experience leading enterprise architecture, platform architecture, or large‑scale technology transformation in complex organizations.
• Proven ability to set architectural vision, define standards, govern technical decisions, and influence executive‑level strategy.
• Deep expertise in distributed systems, cloud‑native architecture, data platforms, API/service integration, security architecture, and production operations.
• Strong understanding of AI/ML platform architecture, model integration patterns, responsible AI considerations, and data‑driven systems.
• Demonstrated success leading across engineering, product, data, security, risk, compliance, and operations teams without relying solely on direct authority.
• Excellent executive communication skills, including the ability to explain complex technical tradeoffs, risks, and investment choices clearly.
• Experience establishing or maturing an enterprise architecture function, architecture review board, or architecture community of practice.
• Experience with regulated, data‑sensitive, or highly governed environments.
• Familiarity with architecture frameworks, decision records, technology road mapping, portfolio governance, and technical debt management.
• Experience shaping enterprise AI, GenAI, agentic AI, RAG, or intelligent automation strategies.
• Relevant architecture or cloud certifications such as TOGAF, AWS Certified Solutions Architect, Azure Solutions Architect, or equivalent experience.