Help & Supportcareers@gravityer.com
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI Systems Architect & Fractional CTO · From Prototype to Production · Ex-Meta/AWS
I help early-stage and scaling B2B AI companies turn vague technical/product ideas into credible prototypes, architectures, and production-ready systems. My strongest fit is where the problem is messy: AI agents, ML platforms, distributed systems, workflow-heavy products, compliance constraints, reliability, data pipelines, and high-performance user interfaces. I’ve spent 15+ years working across the AI stack — ML modeling and training, MLOps, distributed systems, reliability engineering, frontend architecture, and product-facing technical leadership. That breadth lets me connect product intent with engineering reality faster than narrow specialists. Previously, I led technical delivery at Meta on multimodal support diagnosis systems, LLM/state-machine/logic-programming agent frameworks, policy enforcement, guardrails, fraud, privacy, and abuse controls. Before that, I worked on ML systems for robotaxi fleets at Mercedes-Benz and Vay, large-scale production ML at AWS, and high-performance mapping platforms at HERE/Yandex-scale environments. I’m currently building Swobu — a local-first boundary layer that unbundles AI clients from LLM vendors. Open to selective Outside IR35 / 1099 contract, advisory, prototype sprint, and fractional CTO work in AI/ML, agentic systems, developer tools, infrastructure, and complex production platforms. Useful engagements: — 2–4 week AI prototype sprint — technical/product architecture audit — fractional CTO support for nontechnical or product-led founders — agentic system design and reliability review — ML platform / infrastructure / workflow system design — investor or customer demo hardening
Taras Shevchenko National University of Kyiv
Master's Degree, Radio Physics, Electronics and Computer Systems
N/A – Present
Meta
Lead Machine Learning Engineer
January 1, 2021 – January 1, 2025
Greater London
Vay
Principal Machine Learning Engineer
January 1, 2020 – January 1, 2021
Mercedes-Benz AG
Machine Learning Tech Lead
January 1, 2019 – January 1, 2020
Amazon Web Services (AWS)
SDE II (Machine Learning)
January 1, 2016 – January 1, 2019
HERE Technologies
Senior Software Engineer
January 1, 2014 – January 1, 2016
Yandex
Full-Stack Web Developer
January 1, 2011 – January 1, 2014
Ukrainian Chamber of Commerce and Industry
Web Developer
January 1, 2011 – January 1, 2011
Informational and Computer Centre of Kyiv Taras Shevchenko National University
IT engineer (part-time)
January 1, 2008 – January 1, 2010
Getting Things Done
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's diverse experience across multiple prominent tech companies (Meta, Vay, Mercedes-Benz AG, AWS, HERE, Yandex) and various ML applications demonstrates adaptability and a broad skill set. Their progression into leadership roles indicates ambition and a drive for impact, aligning well with high-performance cultures. The breadth of projects, from web development to advanced ML, suggests a versatile and curious individual.
Soft Skills & Operational Fit
The candidate's resume highlights leadership in technical delivery, strategy, and cross-functional initiatives, suggesting strong operational fit and soft skills such as leadership, strategic thinking, and collaboration. Experience in defining OKRs and technical direction further supports this.