Executive Director, Agentic Lab and Architecture Lead

Accountabilities: Define enterprise architecture, reference patterns, technical standards, and engineering guardrails for secure, scalable, and governed agentic AI capabilities.

Establish reusable architectural approaches covering agent orchestration, multi-agent systems, memory, RAG, tool and function calling, APIs, evaluation, observability, and enterprise integration.

Lead the Agentic Lab innovation roadmap, creating an environment for rapid experimentation, technical validation, and disciplined incubation of high-potential AI technologies.

Evaluate foundation models, agent frameworks, orchestration technologies, developer tools, and emerging approaches to determine their suitability for enterprise adoption.

Develop reusable proof-of-concepts, accelerators, architectural blueprints, and reference implementations that accelerate delivery and reduce duplicated effort across AI initiatives.

Drive adoption of shared technical assets and standards while establishing scalable patterns that support consistent implementation across enterprise AI solutions.

Partner with AI engineering, platform engineering, product, architecture, security, data, technology, and business teams to transition validated prototypes into production-ready capabilities.

Oversee the technical readiness and handoff of lab concepts into scaled implementations, including architecture reviews, documentation, risk assessments, and operating model transitions.

Embed Responsible AI, security, privacy, accessibility, data governance, regulatory, and quality requirements into architectures and experimentation practices from the outset.

Establish evaluation and monitoring standards covering agent reliability, explainability, performance, safety, human oversight, and measurable business value.

Lead, coach, and develop architects, engineers, and other technical talent, promoting disciplined experimentation, engineering excellence, reuse, and continuous learning.

Communicate architecture decisions, technical trade-offs, risks, investment requirements, progress, and strategic recommendations clearly to senior executives and cross-functional stakeholders.

Requirements

Bachelor’s or advanced degree in Computer Science, Artificial Intelligence, Engineering, or another relevant technical discipline.

12+ years of experience designing enterprise software platforms, AI architectures, data and AI products, or cloud-native engineering capabilities, including significant technical leadership experience.

Deep expertise in LLMs, agent frameworks, multi-agent orchestration, RAG, vector and graph databases, tool/function calling, memory, evaluation, observability, APIs, event-driven architectures, and cloud-native deployment.

Proven ability to establish enterprise reference architectures, reusable patterns, technical standards, guardrails, and validated blueprints for secure and scalable AI deployment.

Strong hands-on understanding of modern software engineering and AI delivery practices, including version control, CI/CD, testing, release readiness, model and prompt evaluation, telemetry, cost optimization, performance management, and operational support.

Demonstrated ability to evaluate emerging technologies through technical scouting, laboratory experimentation, architecture review, production-readiness assessment, and transition into engineering roadmaps.

Strong knowledge of Responsible AI, security, privacy, data governance, human oversight, access controls, prompt and model risks, auditability, and compliance requirements for enterprise AI.

Experience building enterprise agentic AI platforms, developer ecosystems, or AI architecture practices in a regulated industry such as pharmaceuticals, healthcare, financial services, or another highly governed environment is preferred.

Familiarity with technologies such as Microsoft Azure AI Foundry/OpenAI, Semantic Kernel, Copilot Studio, LangChain/LangGraph, MCP/A2A protocols, knowledge graphs, GraphRAG, and enterprise search architectures is advantageous.

Demonstrated ability to influence senior technology and business leaders on architecture trade-offs, investment decisions, platform reuse, operational risk, and enterprise scaling strategies.

Proven experience coaching principal engineers, architects, AI engineers, and product teams on reusable architecture patterns and disciplined innovation.

Strong executive communication, stakeholder engagement, strategic thinking, mentoring, curiosity, learning agility, and business-value orientation.

Ability to operate effectively in complex, fast-moving environments while balancing innovation with governance, reliability, security, and measurable outcomes.

Benefits

Annual salary range of $225,400–$418,600 , with final compensation determined by relevant skills, experience, and other applicable factors.

Performance-based cash incentive.

Potential eligibility for annual equity awards, depending on role level and applicable program criteria.

Comprehensive health benefits, including medical-related coverage.

Life and disability insurance benefits.

401(k) plan with company contributions and matching.

Generous paid time off, including vacation, personal days, holidays, and other eligible leaves.

Remote work opportunity available anywhere in the United States, subject to applicable legal-entity restrictions.

Approximately 10%+ travel may be required, including potential domestic and international travel.

Opportunity to lead enterprise-scale AI architecture and innovation initiatives with significant strategic visibility.

Inclusive environment focused on collaboration, innovation, professional growth, and technical leadership.

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