Senior Director, Enterprise AI & Architecture
$200,000–$250,000 year
HybridBoston, Massachusetts, United States
Job Summary
Define and own the Enterprise AI strategy, roadmap, and operating model while leading a team spanning architecture, AI engineering, platform, governance, and security. Establish architecture patterns for AI-First applications, copilots, intelligent workflows, and reusable components, then oversee a risk-tiered governance and architecture review process. Partner with applications, engineering, infrastructure, operations, and security teams to pilot, refine, and scale AI-enabled practices across the SDLC. Embed security, privacy, and responsible AI principles into platforms and business use cases, creating governance models that support experimentation while protecting enterprise data. Lead the development of AI capabilities such as decision support, workflow automation, and productivity tools, driving adoption of a centralized AI platform including LLM gateways and model registries. Build and lead a high-performing organization, developing talent and fostering a culture of disciplined experimentation and measurable outcomes.
Required Qualifications
- 15+ years of progressive technology leadership experience
- senior responsibility for engineering, architecture, platforms, data, infrastructure, automation, AI, digital transformation, or enterprise technology delivery
- 5+ years managing multi-disciplinary engineering or architecture teams
- Experience at large Enterprise, enabling enterprise adoption of AI productivity tools such as Gemini, ChatGPT, Claude, or similar platforms
- Significant hands-on leadership experience with AI, machine learning, Generative AI, automation, advanced analytics, intelligent platforms, developer productivity tools, or emerging technology capabilities, at a large Enterprise Organization
- Strong understanding of Generative AI concepts and implementation patterns, including LLMs, RAG pipelines, agentic AI frameworks, enterprise ML deployment patterns, SLMs, embeddings, prompt engineering, retrieval-augmented generation, vector databases, semantic search, evaluation frameworks, and enterprise knowledge integration
- Experience with Agentic AI patterns, including autonomous or semi-autonomous agents, tool/function calling, workflow orchestration, human-in-the-loop controls, guardrails, monitoring, and safe deployment practices
- Familiarity with Model Context Protocol (MCP) or similar approaches for connecting AI systems to enterprise tools, data sources, APIs, and workflow actions in a secure and governed manner
- Understanding of AI/ML model lifecycle practices, including model selection, experimentation, validation controls, performance monitoring, drift detection, feedback loops, auditability, and responsible production deployment
- Familiarity with enterprise AI platform capabilities such as model access gateways, model catalogs, AI orchestration layers, policy enforcement, prompt and response controls, observability, cost monitoring, and usage governance
- Strong technical fluency across cloud platforms, APIs, microservices, data platforms, observability, automation, cybersecurity, identity, privacy, and modern engineering practices
- Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or related field required
- Proven experience leading Enterprise-scale technology transformation; preferably in a regulated environment, such as financial services, or another highly governed industry
- Track record of partnering with executive stakeholders and translating technology strategy into business outcomes
- Experienced at defining and influencing organizational strategy, inclusive of board and executive level communications (written and verbal)
- Demonstrated success building or leading an enterprise AI, platform engineering, or architecture function at scale
- Proven ability to lead internal teams, contractors, vendors, and system integration partners in a fast-paced, high-accountability environment
- Strong command of compliance requirements relevant to payments (PCI-DSS, SOX)
- Experience with FinOps practices and cloud cost governance for AI/ML workloads
- Must be available for weekend shifts
- #LI-Hybrid
Desired Qualifications
- Experience at a global payments, fintech, or healthcare technology company
- Familiarity with federated delivery models and domain-led architecture teams
- Background in responsible AI, AI ethics frameworks, or model explainability
- MBA or advanced degree in Computer Science, Engineering, or related field
Hiring someone like this?
Get your role in front of qualified candidates on Sorce.