VP R&D

A fast-growing, venture-backed enterprise AI startup (post-Series A), developing an advanced compliance and governance platform for the global financial services industry, is seeking for a VP of R&D. The company’s proprietary AI platform automates oversight, risk management, and regulatory compliance across customer communication and marketing channels for tier-1 financial institutions. Currently at an inflection point of rapid enterprise adoption, the company is scaling its platform to support complex architectures inside highly regulated environments

The Role

We are looking for an experienced, highly technical, and business-oriented VP of R&D to lead our engineering organization. In this role, you will hold single-point accountability for the overarching technical vision, platform architecture, and execution. You will establish a unified LLM strategy, scale our enterprise-grade infrastructure, and ensure the engineering organization moves with the urgency required by the business. Working directly with the Co-Founder & CTO and the executive team, you will ensure engineering execution and business strategy are completely aligned.

Key Responsibilities

• Engineering Leadership: Lead, mentor, and grow an organization of ~20 engineers across 3 cross-functional teams, owning overall output, retention, and team growth. Manage the operational and coordination overhead of multiple teams with distinct contexts.
• Technical Strategy & Roadmap: Define, build, and execute the multi-team technical roadmap in an agile, high-velocity environment. Thrive in ambiguity by shaping and executing plans collaboratively rather than waiting for fully scoped requirements.
• AI & LLM Strategy: Set and own the enterprise LLM strategy, including model selection, fine-tuning, RAG architecture, evaluation frameworks, deployment, and cost optimization.
• Platform Architecture: Design and scale an enterprise-grade AI platform built for high reliability, strict security, and high throughput. Oversee distributed systems and event-driven data pipeline architectures.
• Compliance & Governance: Treat regulatory constraints as primary design inputs. Ensure every AI output and model decision can be defended to enterprise compliance, security, and risk officers.
• Executive Partnership: Partner directly with the Co-Founders, Product, Sales, Customer Success, and HR to translate business priorities into engineering deliverables. Act as an executive-level partner in strategic and customer-facing technical discussions.
• Culture & Standards: Foster an output-driven engineering culture where success is measured by shipped impact rather than headcount or process overhead.
• Hiring & Talent Development: Own engineering hiring end-to-end, maintaining high hiring standards and holding proactive conversations to continuously raise the team's bar.

Requirements & Qualifications

• Experience: 10+ years in software engineering, with at least 5+ years of experience leading multiple engineering teams simultaneously. Proven ability to build, structure, and scale an engineering organization.
• Production-Grade LLM Expertise: Real-world architectural experience delivering LLM-based products into enterprise production environments under strict SLAs, well beyond basic API integrations or theoretical prototypes.
• Modern AI Tech Stack: Hands-on knowledge of the modern LLM stack, including prompt engineering, fine-tuning, RAG, evaluation frameworks, and inference infrastructure.
• Cloud & Distributed Systems: Deep cloud-native background (AWS / GCP / Azure) with hands-on experience designing, scaling, and operating distributed systems.
• Data Pipelines: Proven experience with high-throughput, event-driven data architectures and efficient data flows.
• Regulated Environments: Experience in FinTech, RegTech, or other heavily regulated industries where security, data integrity, and compliance are non-negotiable.
• Leadership Range: High communication versatility—equally comfortable presenting technical strategy to executive peers and participating in granular architecture and code reviews.
• Execution Mindset: Strong sense of ownership, bias for action, and ability to navigate fast-moving startup dynamics.

Compensation & Culture

• Competitive executive compensation package and meaningful equity.
• Direct access to company leadership with zero bureaucracy.
• Flexible, output-first culture focused on delivered results.
• Opportunity to lead high-impact technical innovation in an industry undergoing major transformation.