5 дней назад
Chief Technology Officer (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Chief Technology Officer (AI): Driving Toptal’s product and engineering execution through AI-first architecture, agentic engineering, and scalable platform development with an accent on foundation models, evaluation, retrieval, orchestration, and cost control. Focus on deploying measurable agentic workflows, modernizing distributed systems, scaling engineering teams, and improving reliability, throughput, and business impact across core marketplace operations.
Location: Remote; candidates based in Canada, South America, or Europe
Company
is a global network of business, design, and technology professionals that enables companies to scale teams on demand.
What you will do
- Set the technical strategy and own the architecture across ’s products, services, data flows, interfaces, and system boundaries.
- Build and lead an AI-first technology platform covering model selection, fine-tuning, retrieval, context engineering, orchestration, tool and MCP integration, guardrails, evaluation, and cost control.
- Deploy agentic systems across matching, vetting, onboarding, delivery, and internal operations, with measurable outcomes for cost, cycle time, quality, or revenue.
- Modernize engineering practices through AI-assisted development, review, testing, and operations while maintaining quality, security, reliability, and responsible AI standards.
- Own workforce planning, team structure, hiring commitments, talent assessment, and leadership development.
- Partner with Product and executive leadership to turn strategy into production-ready outcomes and business impact.
Requirements
- Bachelor’s degree in Computer Science, Engineering, or a related technical field; an advanced degree is strongly preferred.
- 15+ years of progressive engineering leadership experience, including significant time as a CTO, VP of Engineering, or direct report to one at meaningful scale.
- Hands-on production experience with foundation models, agentic architectures, harness design, retrieval, context engineering, fine-tuning, evaluation, distributed systems, service architecture, data-intensive applications, and cloud infrastructure.
- Demonstrated experience deploying agentic systems at scale, measuring results, evaluating model and agent changes, and retiring ineffective solutions.
- Experience scaling and modernizing large existing codebases, managing model economics, inference capacity, latency, cost budgets, and provider portability.
- Experience leading globally distributed remote teams in a technology or hyper-growth company, with strong written and verbal communication skills.
Culture & Benefits
- Fully remote work within the stated geographic regions.
- High-ownership environment focused on speed, execution, measurable outcomes, and quality.
- Hands-on leadership culture requiring active participation in design reviews, coding, hiring, and technical decision-making.
- Opportunity to establish shared AI architecture, evaluation practices, and agentic engineering standards across the organization.
Hiring process
- The first week focuses on learning the platform architecture and establishing a working rhythm with the CEO and business leaders.
- Within the first month, assess engineering and AI maturity, team capability, and the required strategy.
- Within the first three months, present a resourcing plan, establish shared AI architecture and evaluations, and put an agentic workflow into production.
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