Europe
We are toogeza, a Ukrainian recruiting company that is focused on hiring talents and building teams for tech startups worldwide. People make a difference in the big game, we may help to find the right ones.
Currently, we are looking for a CTO to join one of Toogeza’s clients.
AI-native consumer mobile company with a subscription monetization model. Our iOS app is live: an AI agent with voice control that automatically assembles a finished video clip with music and subtitles from multiple videos a user uploads from their camera roll. The agent determines the theme, selects shots, edits, and adds audio. Android is in active development.
We build a full-stack product: the AI agent is the core, with mobile apps, performance marketing, growth, and product analytics built around it. Industry references — Lightricks, Bending Spoons, Codeway, Photoroom: subscription mobile publishers with in-house R&D and mature growth infrastructure.
The architecture is hybrid: AI video analysis runs server-side, the final clip assembly happens on-device. A strategic direction the CTO will own — gradually migrate decisions from backend to device without quality loss, to improve unit economics.
The voice stack is built on third-party providers (Whisper / Deepgram / OpenAI Realtime / ElevenLabs). The CTO must evaluate trade-offs between providers across latency, cost, and quality, and decide when to replace or hybridize parts of the stack.
The LLM agent (Operator / Director / Producer hierarchy) uses a memory system on pgvector + Neo4j (GraphRAG hybrid retrieval). The user portrait is built from multi-signal data — camera, voice, gallery, social analytics.
The engineering team today is 6 people, all reporting directly to the CTO:
AI / Agent: 2 people (including a recently hired AI Engineer)
iOS: 2 engineers
Android: 1 engineer
Backend: 1 engineer
Plus product, marketing, and growth. The plan for engineering team growth is targeted — +1–2 people over 6 months. This is not "build a team from scratch" — it is "lead an existing team and reinforce it where needed".
Our product is entering a phase where the engineering team must become a full product engineering vertical with its own tempo, processes, and culture. We need a CTO who simultaneously owns three intersections:
Production mobile video stack at the level of Core Image / Metal / OpenGL ES / AVFoundation, video processing, rendering, on-device inference — real experience, not theory
Agentic AI and LLMs in production — LLM orchestration, RAG/GraphRAG, agentic architectures, memory systems, evaluation frameworks, hands-on with voice stacks
Subscription growth infrastructure at Codeway / Bending Spoons / Lightricks level — paywall A/B, MMP attribution, SKAN/AdAttributionKit, LTV/ROAS pipelines, cost optimization
This is the owner of the product engineering vertical, with direct accountability for the production product, hiring, unit economics, and technical strategy.
Full technical ownership of the live iOS app and the Android launch
Auto-edit quality and stability: scene understanding, shot selection, beat matching, subtitle generation, thematic coherence
Voice agent: latency, recognition accuracy, dialog quality, selection and optimization of third-party providers (Whisper / Deepgram / OpenAI Realtime / ElevenLabs)
Hybrid pipeline: video analysis server-side, assembly on-device — and the strategic shift toward more on-device without quality loss
Operational excellence: uptime, incident management, AI output quality monitoring
Migrating tasks from backend to device as the key unit-economics lever — prioritization, technical plan, quality metrics during migration
GPU inference and server-side video pipeline optimization (FFmpeg, queues, CDN)
Cost management for third-party AI APIs (LLM, ASR, TTS, music generation/licensing) — hybrid of in-house and third-party
Cost-aware decisions across cloud, third-party SDKs, infrastructure
Manage the current engineering team (6 people: 2 AI, 2 iOS, 1 Android, 1 backend)
Targeted hiring of 1–2 people over 6 months to address specific tasks and stack gaps
Performance reviews, technical onboarding, engineering culture
Process design — sprint cadence, code review, on-call, incident management — proportionate to stage, without premature process overhead
Evolve product's agentic architecture (Operator / Director / Producer hierarchy)
Memory system on pgvector + Neo4j (GraphRAG hybrid retrieval), Knowledge Graph, user portrait pipeline
Voice-first interface — optimize end-to-end latency and cost through provider selection and stack hybridization
Evaluation infrastructure for LLM agents — LLM-as-judge, regression tests for edit quality and tone of voice
iOS: Swift, Core Image, Metal, AVFoundation, Vision; on-device CoreML inference where it improves unit economics
Android (in development): Kotlin, OpenGL ES / Vulkan, MediaCodec, CameraX, ML Kit / TensorFlow Lite
Server-side rendering pipeline (FFmpeg, GPU inference), CDN, video delivery
On-device video composition, real-time preview, optimization across device classes
Subscription stack: RevenueCat / Adapty, paywall A/B testing, server-driven paywalls
Attribution: AppsFlyer / Adjust / Branch, SKAN / AdAttributionKit, probabilistic modeling, web-to-app funnels
Product analytics and data warehouse: event pipeline, BI, cohort analysis, LTV/ROAS dashboards
Translate company strategy into a roadmap: from tactical quick wins to stable long-term
Tech due diligence readiness for the next round
Direct partner to the founder on product and business decisions
CTO / VP Engineering / Head of Engineering experience in a consumer mobile subscription company. Experience leading a team of 10+ engineers is required; companies of 30+ people — strong plus
Production video/photo stack: Core Image, Metal, OpenGL ES / Vulkan, AVFoundation, MediaCodec — both mobile platforms
Experience migrating workloads from backend to device (on-device inference, on-device video processing) with measurable unit-economics impact
Subscription growth experience at the level of Codeway / Bending Spoons / Lightricks / Photoroom — paywall optimization, MMP attribution, post-ATT/SKAN, LTV-driven decisions
Agentic AI / LLMs in production: you understand the difference between "calling the OpenAI API" and building an agent system with memory, tools, and an eval loop. Hands-on experience with voice stacks (ASR/TTS, real-time voice agents) — required
Management maturity: hiring, performance reviews, budgeting, cost-aware decisions, business orientation
Production launch experience with an auto-edit video or voice-controlled app (Captions / Descript / Opus Clip / Submagic / CapCut-class)
Proprietary ML models in production — fine-tuning, on-device CoreML/TFLite, model distillation
Experience optimizing third-party AI API cost and latency (LLM, ASR, TTS) through hybridization and in-house replacements
What’s next?
If this role sounds like a fit — we’d love to hear from you! Just send over your CV and anything else you’d like us to consider.
We’ll review everything within five working days, and if your background matches what we’re looking for, we’ll get in touch to set up a call and get to know each other better.
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