# Jobgether — Chief Technology Officer

- Generated: 2026-09-15 11:30:43 AM EDT
- Original/canonical posting: https://www.linkedin.com/jobs/view/4466522065/
- Provider: LinkedIn
- Posted: approximately 2026-09-15 10:30 AM EDT (from '1 hour ago')
- Elapsed since posting: represented by the provider's relative posting label and approximate Eastern timestamp when available
- Applicants: Be among the first 25 applicants
- Work model/location: Fully remote — United States; end employer is not identified
- Compensation: Not disclosed; Chief title qualifies
- Travel: Not disclosed
- Positioning track: Executive leader
- Fit outcome: PASS — 89%

## Direct-match strengths

Hands-on AI and engineering executive leadership, agentic architecture, RAG, MCP, evaluation, guardrails, AI economics, distributed systems, cloud platforms, reliability, security, engineering productivity, workforce planning, global teams, and measurable production outcomes.

## Hard or material gaps

The end employer is not identified. Keith's strongest production evidence is advanced LLM application, agent, retrieval, evaluation, and platform engineering rather than training foundation models from scratch. Large legacy-codebase replacement and high-volume marketplace depth are less directly documented than cloud/platform modernization and multi-tenant SaaS delivery.

## Evidence map

1. Own company-wide technology, engineering, and AI strategy (weight 3, evidence 3/3) — Direct founder, VP, and senior-director ownership of strategy, architecture, budgets, delivery, and operations.
2. Deploy agentic systems across business workflows (weight 3, evidence 3/3) — Built a production platform supporting 70+ automations across more than 20 workflows.
3. Evaluation, regression, guardrails, and AI quality (weight 3, evidence 3/3) — Direct evaluation harnesses, guardrails, human review, monitoring, and continuous-improvement practices.
4. Hands-on coding and architecture review (weight 3, evidence 3/3) — Built the AssistX core and first 80% of its initial application hands-on.
5. Workforce planning, hiring, and performance leadership (weight 3, evidence 3/3) — Recruited and led organizations up to 25, including managers, with budgets and performance accountability.
6. Distributed systems, cloud, data-intensive platforms (weight 3, evidence 3/3) — Longstanding AWS, API, distributed, data, SaaS, security, and operations experience.
7. AI economics, latency, model routing, and cost controls (weight 2, evidence 3/3) — Direct production routing, caching, provider selection, latency, reliability, and cost-control evidence.
8. Fine-tuning or operating advanced AI systems (weight 3, evidence 2/3) — Advanced production AI systems are direct; foundation-model fine-tuning is not a primary claim.
9. Modernize large existing codebases without disruption (weight 2, evidence 2/3) — Direct platform modernization and production migration; very-large monolith replacement is less explicit.
10. 15+ years leadership at CTO/VP/direct-report level (weight 3, evidence 2/3) — Long engineering leadership and VP/founder scope; recent company scale is smaller than some CTO mandates.
11. Global remote teams and marketplace platforms (weight 2, evidence 2/3) — Distributed teams and multi-tenant SaaS are direct; marketplace specialization is not.

## Keyword diagnostic

Exceptional current overlap across agentic AI, retrieval, context, MCP, evaluation, model routing, cost, architecture, engineering operations, talent, and remote organization leadership; no unsupported foundation-model-training or marketplace claim added.

## Full normalized job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Chief Technology Officer based in the United States.
This is a hands-on executive leadership role responsible for the full technology, engineering, and AI strategy of a high-growth, fully remote organization.
You will define the technical architecture and make AI, agentic engineering, and automation foundational to how products and systems are built.
The role combines deep technical ownership with responsibility for engineering execution, platform reliability, AI quality, and organizational scalability.
You will work directly with executive leadership and product teams to turn technical strategy into measurable, production-ready outcomes.
You will also own workforce planning, hiring standards, team development, and the structure required to build a high-performing engineering organization.
Success will be measured through business impact, engineering throughput, reliability, AI adoption, and the ability to move quickly without compromising quality.
This is an environment for a world-class technical builder who remains deeply hands-on while shaping the future of engineering and AI across the organization.
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.
How Jobgether Works
We use an
AI-powered matching process
to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice:
By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

## Artifact metadata

- Resume: https://bit.ly/4hcS9Mf
- Cover letter: https://bit.ly/46ryUJT
- Validation: PASS — 2-page resume (936 words), 1-page cover letter (228 words); PDF geometry, bounds, annotations, links, and visual pages verified.
- Google Drive used: No