Sr. Director, AI Operations & Enablement

Dow Jones•New York, NY

4d•$205,000 - $250,000•Hybrid

About The Position

Dow Jones is hiring a Sr. Director for AI Operations & Enablement, an operator-builder who pairs executive-grade strategic judgment with hands-on technical fluency in modern AI tooling. Reporting to the SVP, Head of Technology Operations, this leader will be the trusted force-multiplier for the most consequential Tech Ops priorities at Dow Jones: reengineering how work gets done across Product & Technology, prototyping AI-enabled workflows directly, and turning fragmented, manual processes into scalable, AI-native operating models. This is a high-autonomy mandate to interview senior leaders and frontline operators alike, diagnose the as-is, design the to-be, and ship the change, both quick wins and full rebuilds, across a 130-year-old global news and information business. This is a high-visibility, high-autonomy role with a mandate to shape something net-new at Dow Jones. You will work directly with the SVP, Head of Technology Operations on the priorities that move the enterprise with the latitude to design the operating model, the technical leverage to build it yourself, and the runway to scale a team underneath the work as it matures. If you are an operator-builder who wants to define what AI-first technology operations look like at a global news and information business, this is the seat.

Requirements

15+ years of progressive experience spanning technology operations, product or program management, management consulting, or transformation roles with a clear pattern of taking on increasingly ambiguous, high-stakes mandates.
Demonstrated ownership of cross-functional process reengineering at enterprise scale: you've personally interviewed leaders and operators, mapped as-is workflows, designed to-be operating models, and shipped the change.
Possess a strong System Thinking mentality.
Hands-on technical fluency with modern AI tooling; comfortable building prototypes, automations, and internal tools yourself using AI coding assistants and agentic development environments.
You read code, write code, and ship working software when speed matters.
Working understanding of how AI is reshaping enterprise operations: model capabilities, agent patterns, retrieval, evaluation, and the integration surface between AI tooling and the SaaS stack businesses run on.
Track record of operating as a trusted force-multiplier to a senior executive, taking ambiguous directives, returning structured outcomes, and consistently raising the bar on quality, accuracy, and judgment.
Equally credible interviewing a C-suite leader and a frontline operator; you adjust register without losing substance.
Proven ability to balance strategic framing (where this matters in 18 months) with tactical execution (what ships this week).
Strong relationship-building instincts across Product, Technology, and business/GM stakeholders; you build coalitions without authority.
Strong written and verbal communication — including the ability to translate technical decisions into business terms and back.
Bias toward shipping, prototyping, and learning in public over polishing in private.
Bachelor's degree or equivalent practical experience; advanced degree welcomed but not required.

Responsibilities

Independently own and drive critical Tech Ops priorities end-to-end, with the judgment to know when to escalate and when to ship.
Translate executive intent into structured plans, decisions, and outcomes, raising the bar on quality and accuracy without requiring oversight.
Represent Tech Ops in cross-functional forums where the SVP cannot be present, with full credibility to commit and decide.
Lead wholesale process reengineering across Tech Ops and adjacent Product & Technology functions.
Interview senior leaders and frontline staff to map current-state workflows, surface bottlenecks, and identify both quick wins and full AI-first rebuilds.
Design target-state operating models that materially improve speed, quality, and cost.
Define measurable efficiency outcomes (cycle time, manual hours saved, error rate, throughput) and own them through delivery.
Prototype AI-enabled automations and internal tools personally with no need to hand off to engineering for the first cut.
Use modern AI coding assistants and agentic development tooling to compress weeks of build into days.
Integrate AI capabilities into the SaaS stack the business already runs on, surfacing value where users already work.
Set the technical bar for what "AI-native" means inside Tech Ops through working artifacts, not slideware.
Build trusted relationships with leaders across Product, Technology, and the GM-led business teams (Consumer, Industries, Risk, Energy) as well as our parent News Corp organization.
Translate fluently between technical capability and business outcome; neither side should feel mistranslated.
Drive enterprise-wide AI adoption by meeting teams where they are, not by mandate.
Influence more efficient governance processes to unstick bottlenecks and review cycles.
Convert one-off wins into reusable playbooks, frameworks, and internal products.
Document, train, and enable others to extend the operating model without you in the room.
Identify when a workstream is mature enough to staff out and recruit/scale a team underneath the role over time.