Chief Technology Officer

Accountabilities:

• Define and execute the overall AI technology strategy, including model selection and fine-tuning, agentic architecture, retrieval, context engineering, orchestration, tool and MCP integration, guardrails, evaluation, and cost management.
• Deploy agentic systems across critical business workflows, including matching, vetting, onboarding, delivery, and internal operations, while owning measurable outcomes from those systems.
• Establish rigorous AI evaluation frameworks, regression suites, quality standards, and review processes to ensure model and agent improvements are measurable and reliable.
• Transform engineering practices through AI-assisted development, code review, testing, and operations to significantly increase engineering productivity without sacrificing quality.
• Own the technical architecture end to end, including services, data flows, interfaces, system boundaries, platform infrastructure, security, and responsible AI practices.
• Drive throughput, reliability, technical debt reduction, build-versus-buy decisions, and the cost structure of engineering and AI infrastructure, including inference, latency, and token usage.
• Work closely with Product and executive leadership to expose core business capabilities through modular, scalable interfaces that other teams can build upon.
• Own workforce planning by translating the roadmap into team structures, headcount plans, role definitions, hiring priorities, and time-sensitive staffing commitments.
• Set and maintain a high performance bar across engineering, assess talent objectively, develop team members, and make difficult performance decisions when necessary.
• Establish clear operating rhythms, technical reviews, accountability mechanisms, and execution cadences that turn strategy into production outcomes.
• Build and lead a globally distributed engineering organization capable of delivering against ambitious technical and business goals.
• In the first months, assess engineering and AI maturity, establish priorities, develop a resourcing strategy, stand up shared AI architecture and evaluation capabilities, and move agentic workflows into production.
• Within the first year, embed AI leverage into the architecture and operating model, demonstrate measurable business impact from production agents, strengthen leadership capacity, and improve throughput and reliability across critical systems.

Requirements:

• Bachelor’s degree in Computer Science, Engineering, or a related technical field is required, with an advanced degree strongly preferred.
• 15+ years of progressive engineering leadership experience, including significant experience as a CTO, VP of Engineering, or direct report to a senior technology executive at meaningful scale.
• Deep and current hands-on expertise in modern AI engineering, including foundation models, agentic architectures, harness design, retrieval, context engineering, fine-tuning, and evaluation.
• Proven experience building, fine-tuning, deploying, and operating foundation models or advanced AI systems in production.
• Demonstrated success deploying agentic systems at scale against real business processes with measurable impact on cost, cycle time, quality, revenue, or other business outcomes.
• Strong expertise in AI evaluation and the ability to demonstrate precisely how model, prompt, or agent changes improve performance.
• Strong understanding of AI economics, including model routing, hosted versus self-hosted infrastructure, inference capacity, latency, cost controls, and provider portability.
• Proven ability to stay ahead of rapidly evolving AI capabilities, educate executives and engineering teams, and drive adoption of technologies the organization was not previously asking for.
• Strategic thinking combined with strong execution, with the ability to develop an independent technical vision and influence decisions through evidence rather than authority.
• Proven ownership of workforce planning and a measurable track record of hiring exceptional technical talent and maintaining a high performance bar.
• Current hands-on coding ability, with the capacity to review and challenge architecture, design documents, evaluation harnesses, and production systems directly.
• Strong command of distributed systems, service architecture, data-intensive applications, cloud infrastructure, and large-scale software platforms.
• Experience modernizing and scaling large existing codebases while maintaining business continuity, including replacing critical systems in production rather than focusing only on greenfield development.
• Experience leading globally distributed and remote engineering teams within a technology or hyper-growth environment; experience with high-volume marketplaces or multi-tenant platforms is a significant advantage.
• Outstanding written and verbal communication skills, with the ability to work effectively with executives, product leaders, engineers, and cross-functional stakeholders.
• Strong ownership, urgency, judgment, and attention to detail, with the ability to make decisions and deliver results in environments where information is incomplete.
• Ability to operate as a world-class individual contributor while simultaneously leading and developing a high-performing engineering organization.
• Ability to work independently, prioritize competing demands, manage deadlines, and reliably participate in virtual meetings and digital collaboration environments.
• Professional communication and application materials must be submitted in English.

Benefits:

• Fully remote position with a globally distributed working environment.
• Full-time, exempt employment.
• Opportunity to shape the organization’s entire technology and AI strategy at executive level.
• Significant hands-on ownership across AI architecture, engineering, infrastructure, product technology, and organizational design.
• High-impact opportunity to deploy advanced AI and agentic systems across core business workflows.
• Direct collaboration with executive and product leadership on company-wide strategy and execution.
• Opportunity to build and scale a world-class, globally distributed engineering organization.
• Environment focused on innovation, rapid execution, technical excellence, and measurable business outcomes.
• Broad exposure to emerging AI technologies, agentic engineering practices, distributed systems, and large-scale platform architecture.
• Opportunity to influence how AI transforms engineering productivity and the wider organization.
• Remote-first culture designed around distributed collaboration and independent execution.
• Resumes and communication must be submitted in English.