Staff Enterprise Architect

DoubleVerify•New York, NY

22h•Hybrid

About The Position

DoubleVerify is hiring a Staff Enterprise Architect to help shape how our business domains, systems, and data work together at enterprise scale. This is a hands-on individual contributor role for someone who can connect business strategy, operating models, data flows, and technical implementation. You will help define how core business domains should interoperate, where ownership should live, how systems should interface, and what sequence of changes will simplify operations, improve control, and accelerate delivery across both enterprise business platforms and proprietary internal systems. In the near to mid-term, this role will likely spend significant time on priority journeys such as Quote-to-Cash (Q2C), adjacent revenue and billing workflows, and the interfaces between enterprise business systems and proprietary operational platforms, but the mandate is enterprise-wide. This is not a pure governance role and not a people-management role. Success comes through systems thinking, technical credibility, strong judgment, and the ability to align and influence stakeholders from senior leadership through individual teams. The ideal candidate has a strong operator instinct: someone who sees systems end to end, identifies where ownership and boundaries should sit, understands how data should move, and can turn an architectural vision into practical change. You should be comfortable moving between strategy and execution: facilitating alignment with senior stakeholders, producing clear architecture artifacts, and getting hands-on with code, integrations, prototypes, and technical validation when needed.

Requirements

10+ years of experience in enterprise architecture, principal architecture, business systems transformation, or a comparable role with cross-functional enterprise scope.
Proven ability to define a vision and translate it into execution, with measurable outcomes rather than only proposals or documentation.
Strong systems thinking across business processes, data architecture, application architecture, and integrations.
Hands-on technical depth, including the ability to write code, build prototypes, and work directly with APIs, automation, and data systems.
Strong understanding of modern enterprise platforms and patterns, including systems of record, workflow automation, integration architecture, and data movement across domains.
Experience working across both large enterprise third-party applications and proprietary internal systems, with sound judgment about where process logic, data ownership, and controls should live.
Excellent written and verbal communication; able to create clear architecture artifacts and present complex ideas convincingly to both executives and practitioners.
Strong interpersonal skills and high judgment; able to align stakeholders, influence without authority, and handle disagreement constructively.
Strong execution mindset, including proactive escalation, risk management, and follow-through on ambiguous cross-functional work.
Good understanding of the latest progress in AI/LLM systems, with the ability to distinguish real enterprise value from hype and apply these technologies thoughtfully.

Nice To Haves

Experience with large-scale enterprise platforms such as CRM, CPQ, billing, ERP, finance, BI/analytics, or adjacent business-process systems.
Familiarity with adtech, martech, or adjacent digital-media environments, including concepts such as account hierarchies, campaign structures, DSP data, measurement, and revenue workflows.
Experience with domain-driven design, capability modeling, operating-model design, or pragmatic enterprise architecture frameworks.
Experience in organizations undergoing process simplification, automation, operating-model redesign, or systems consolidation.
Experience shipping AI/LLM-enabled internal platforms, workflow automation, knowledge tools, search/RAG systems, or evaluation and monitoring workflows.
Background in operations, RevOps, COO-style transformation work, or other roles that required turning fragmented processes into clear operating systems.

Responsibilities

Define and communicate a clear target-state architecture for key enterprise business domains across process, data, applications, and integrations.
Translate business strategy into phased roadmaps, decision frameworks, and measurable outcomes such as cycle-time reduction, risk reduction, cost savings, and improved operational clarity.
Identify where the company should simplify, consolidate, standardize, automate, or establish clearer systems of record.
Lead domain discovery and alignment workshops to define bounded contexts, ownership, decision rights, and interfaces across business domains.
Help the organization establish rigorous domain ownership so teams take clear responsibility for their processes, data, controls, and change management.
Create practical models such as capability maps, domain maps, RACIs, and responsibility boundaries that leadership and teams can actually use.
Map end-to-end process and data flows, identify bottlenecks and ambiguity, and drive clarity around upstream/downstream responsibilities.
Define stable interface patterns and data contracts between systems and teams, with enough rigor that engineering teams can build against them.
Drive architectural decisions around systems of record, integration patterns, workflow automation, and domain boundaries.
Clarify which capabilities should live in third-party enterprise platforms versus proprietary internal systems, and define the interface, ownership, and control model between them.
Build prototypes, reference implementations, lightweight tools, or code-based proofs of concept when needed to validate architecture decisions and accelerate execution.
Engage directly with APIs, integrations, data pipelines, automation platforms, and application architecture to de-risk key decisions.
Bring enough programming and technical depth to challenge assumptions, pressure-test designs, and help teams move from concept to implementation.
Run and shape the architecture decision-making process, including principles, design reviews, escalation paths, and follow-through on critical decisions.
Present and defend the architectural vision to senior management, while also working effectively with domain owners, product leaders, engineers, and operators.
Proactively identify blockers, risks, and cross-team dependencies, and drive them to resolution rather than letting work stall in ambiguity.
Raise the overall quality of decisions across the organization by coaching teams, improving standards, and introducing reusable patterns.
Maintain a strong working understanding of the current state of AI/LLM systems and how they can be applied pragmatically in an enterprise environment.
Identify opportunities to use AI/LLM capabilities to improve business processes, internal tooling, automation, knowledge access, and engineering leverage.
Help teams adopt AI/LLM-enabled patterns responsibly, with attention to governance, evaluation, quality, security, reliability, latency, and cost.