About the Role

Cross River is building the financial infrastructure of the Intelligence Age - the regulated backbone on which AI-era finance runs. The Intelligence organization is where that ambition becomes operational: the models, platforms, and data products that power credit, compliance, payments, and strategic decision-making across the bank.

We are hiring an SVP, Head of Intelligence to own this organization end to end. This is not a caretaker role. You will inherit a function mid-transformation - a Modeling Organization being rebuilt around automation, a data infrastructure team being re-platformed, and a new class of intelligence products being stood up from redeployed talent - and you will own the whole build chain. This is a Commercial Product Role - you need to of course be an Engineering Leader but Commercial Strategist First.

You report directly to the EVP & Chief AI Officer.

What You Will Own

• CRB Intelligence. The bank's intelligence platform - the models, tooling, and serving layer purpose-built for the Intelligence organization, built vertically on top of the bank's horizontal enterprise AI platform. You are the enterprise platform's most demanding internal customer, and you make it real.
• Data Infrastructure. The architecture and engineering of the data foundation Intelligence runs on, including a senior architecture team reporting to you. Data operations (ingestion, curation, production support) run in the COO organization under a written SLA to Intelligence - uptime, freshness, schema stability. You are the customer; you enforce the contract.
• Intelligence Products. A new product line turning the bank's data exhaust into decision products for the business: credit intelligence, counterparty intelligence, market and network analytics. You define the roadmap, ship the products, and prove the P&L logic.
• Modeling - The bank's model development organization - credit and compliance modeling

What Success Looks Like (First 9 Months)

• CRB Intelligence is in production, with the Model development lifecycle running on it - automated and observable.
• Build/run separation is real: nothing transfers to operations without runbooks, SLOs, and alerting; nothing comes back over the wall.
• Intelligence Products has shipped at least three products with named internal customers and measurable decision impact.
• The Model Factory operates at materially higher throughput with a smaller, more senior team.
• The seam with the enterprise AI platform is clean: you consume horizontal, you build vertical, and there is one AI platform strategy at the bank.

What We Are Looking For

• A builder-executive: 12+ years across data/ML platform engineering and quantitative or decision-science organizations (not engineering only), with 5+ years leading multi-team engineering orgs (30+ people) through platform transitions. High Pressure Experience - Trading desks, Quant shops, Algorithmic houses is a HARD requirement.
• A P&L-first architect. Every product in this organization follows the same cycle: ideate 1 test 1 measure 1 deploy 1 measure 1 tweak 1 measure 1 scale 1 measure. Architecture serves that loop - commercial outcomes are the design input, not a downstream discovery. If you cannot name the P&L question a system answers, you should not build the system.
• We are NOT looking for Technology romantics. Engineers who fall in love with architecture for its own sake. If elegant systems are the reward and the commercial outcome is an afterthought, this is the wrong role. Ship-and-measure beats admire-and-refactor, every time.
• Proven ownership of an ML/AI platform in production at scale - model lifecycle, feature/data infrastructure, serving, observability - ideally in a regulated environment (banking, payments, lending, insurance).
• AI Native and Bias for automation - small senior teams over headcount; you measure yourself on throughput per engineer. Demonstrated ability to lead senior, technically formidable direct reports - including leaders who previously ran their own organizations - and make them more effective.
• Fluency in model governance realities: SR 11-7, first-line/second-line separation, and how to build controls into systems rather than committees.
• Product instinct: you have turned internal data capabilities into products with customers, roadmaps, and adoption metrics, not just dashboards.
• Comfort operating across organizational seams: negotiating SLAs with peer organizations, consuming shared platforms, and escalating on contract rather than on relationship.

Why This Role

You get the rarest thing in enterprise AI: a mandate with the org chart already cleared for it. The build chain is yours, the operating contract with the run organization is written down, and the architect of the vision is the executive sponsor of the role - the EVP Chief AI Officer. What's left is execution per the exact vision- and that's the job.

#LI-ZN #LI-Hybrid #LI-Onsite

Salary Range: $280,000.00 - $310,000.00