Senior AI / Full-Stack Engineer (m/f/d) flyvAI Platform Lead
Detalji posla
- Podatkovno Inženjerstvo
- Data Mining
- Procesiranje Podataka
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- Devops
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- Mrežna Administracija
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- Arhitektura Riješenja
- Arhitektura Sistema
- Back-end Razvoj
- Nove Tehnologije
- Front-end Razvoj
- Full Stack Razvoj
- Funkcionalni QA
- Dizajn Mobilnih Platformi
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- IT I Mreže - Drugo
AI / Full-Stack Engineer (m/f/d)
flyvAI Platform Lead
Location: Remote (EU preferred) | Zagreb - Stuttgart | Full-Time / Long-Term
About flyvbird
flyvbird is building what traditional airlines never managed to build:
A demand-first, AI-driven regional air mobility platform.
Our platform is already live and operational. We combine:
Customer booking system (Next.js, TypeScript)
Admin Operations Console
API backend (Express.js, PostgreSQL)
ML service (FastAPI, scikit-learn)
Demand clustering & predictive routing (flyvAI)
We are now moving from Phase 1 “Human Algorithm” to Phase 2 autonomous AI optimization.
For this, we are building our own long-term in-house tech leadership.
Your Mission
You will take technical ownership of flyvAI and the entire booking platform stack.
This is not a feature-factory role.
This is a platform-stabilization, AI-evolution, and architectural leadership position.
You will:
Ensure platform stability in a business-critical environment
Eliminate structural weaknesses
Strengthen ML intelligence and automation
Prepare the system for scaling beyond 100k+ search events
Technical Environment
Frontend
Next.js
TypeScript (strict mode)
Framer Motion
i18n (DE/EN)
OAuth (Google, Apple)
Computop 3DS + PayPal integration
Backend
Express.js + tRPC
PostgreSQL (Cloud SQL)
Drizzle ORM
Redis
JWT authentication
PDF generation (Invoices, BCBP, Apple Wallet)
Dynamic pricing engine
Atomic seat inventory locking
ML Service
FastAPI (Python)
scikit-learn Random Forest
pandas / numpy
SQLAlchemy
APScheduler (auto retraining)
Dockerized deployment
Model versioning & metadata storage
Demand clustering & route prediction
25-feature prediction model
Automated retraining (24h)
Responsibilities
1️⃣ Platform Stability & Architecture Control
Audit full stack (Admin, User App, API, ML)
Identify structural bottlenecks
Eliminate recurring bugs
Improve performance under load
Strengthen monitoring & observability
2️⃣ AI & flyvAI Evolution
Improve prediction model accuracy
Enhance DemandMatch clustering logic
Implement dynamic route optimization
Develop advanced ML pipeline
Prepare model infrastructure for multi-model architecture
3️⃣ Business-Critical Ownership
The platform is contractually defined as business-critical
SOFTWARE MAINTENANCE Agreement …
You must:
Understand booking/payment impact
Ensure SLA compliance
Prevent revenue-impacting incidents
Architect for zero downtime
4️⃣ Transition & Knowledge Transfer
The current stack was developed externally.
You will:
Build internal technical documentation
Reduce vendor dependency
Prepare platform for partial or full internalization
Design clean handover strategy if needed
You Should Have
Core Skills
Strong Node.js + TypeScript
PostgreSQL performance optimization
Real production payment system experience
Experience with booking/inventory systems or similar atomic locking
AI / ML
Strong Python experience
scikit-learn or equivalent
Feature engineering knowledge
Production ML deployment
Model evaluation (F1, precision, recall)
Experience with prediction services at scale
Architecture
Cloud Run / containerized environments
CI/CD pipelines
Observability (Sentry, logs, monitoring)
Scalability & load considerations
Bonus
Aviation domain knowledge
Dynamic pricing systems
Revenue optimization systems
Demand clustering / recommendation engines
What We Offer
Direct impact on a live aviation platform
Equity participation possible
Full ownership and architectural freedom
Work directly with founder & CTO
Build the “Uber-logic” for aviation
Ideal Profile
You:
Think in systems, not tickets
Care about stability
Hate fragile architectures
Want to build something category-defining
Can work independently
Prefer responsibility over bureaucracy
Growth Path
Year 1:
Platform stabilization
AI improvement
Ownership transition
Year 2:
Multi-aircraft scaling
Real-time demand routing
Advanced revenue AI
Long term:
CTO or Head of AI opportunity possible
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