AI Business System Engineer
Essentials
Job title: AI Business System Engineer
Location: Romania, remote
Type: employment contract
Offer
Remuneration & work-life balance:
Competitive salary and trust-based working hours.
Private health insurance.
Generous training budget.
2 extraordinary team events (4 days) per year.
Meal benefit.
Communication & trust:
Open, honest and direct communication. Your ideas are welcome!
A feedback meeting every quarter to help us grow together.
We encourage innovation and are open to new ideas that push the boundaries.
Modern working:
Everything you need for your daily work: MacBook, monitor, headphones and more.
Individual training:
One training day per month and a generous training budget for your personal development.
Buddy program:
An experienced team member will support you from day one to help you get started.
Client
Our client creates innovative, user-friendly and modern applications that make lotto accessible to everyone. They truly believe that dreaming and hoping together through lotto empowers life — and now they’re building a brand-new team in Romania.
Role
As AI Business Systems Engineer – Identify where technology can create the highest impact across the company, Marketing, Finance, HR/People, Product, Data, and beyond , build AI-powered systems that give us full control and outperform any off-the-shelf solution, and continuously improve them using AI as the primary development engine. The person does not write code manually, they direct AI tools as the developer while owning architecture, security, and production quality end-to-end
Your Tasks & Responsibilities
Discovery & problem definition (ongoing): Shadow every team — Marketing, Finance, HR/People, Product, Data, and Operations — run structured interviews, map workflows, identify bottlenecks and failure modes, translate into problem statements and measurable success criteria.
Solution design & proposal (project-based): Present solution options with effort/impact/risk tradeoffs; define architecture, security requirements, and rollout plan before building.
Marketing Intelligence Platform (flagship): Full-stack marketing OS: Ingests all channel data (paid, SEO, Trends, etc.), analyzes performance, auto-generates/tests/creatives/decisions. Ties to user behavior for personalized funnel (w/ Data Sci). Self-improving.
Customer Engagement Platform (flagship): Custom system: Lifecycle messaging/push/in-app flows integrated w/ Web/App data (w/ Data Sci personalization/segmentation). Lightweight SDK for frictionless event tracking + data ownership.
AI-driven system maintenance (ongoing): Feed error logs, performance anomalies, and failure patterns back into AI workflows that diagnose, propose fixes, and apply them. Systems improve autonomously over time.
Developer Enablement (ongoing): Support prod eng team w/ AI workflows/tooling/hands-on sessions: Own internal tracking SDK for frictionless Web/App event tracking. Bidirectional support; work adjacent to their roadmap.
Security & reliability (ongoing): Secrets management, least-privilege access control, user data handling, audit logging, monitoring, alerting, and clear failure handling across all systems.
Documentation (ongoing): Concise documentation per system — purpose, inputs/outputs, failure modes, how to modify — transferable and operable without the original author.
Your goals in this role
Within 1 month: Marketing Intelligence Platform live — all major paid media channels connected, data normalized, AI-generated recommendations in active use by the marketing team. Monitored, documented.
Within 3 months: Platform extended to all data sources. Campaign optimization running semi-autonomously — the system proposes, tests, and measures. Customer Engagement Platform live, handling the highest-impact engagement workflows. Both systems self-improving via AI diagnostic loops.
Within 6 months: Both platforms operating largely autonomously. Marketing decisions informed end-to-end by the system — from data ingestion to creative generation to campaign execution. At least two additional high-impact systems live across Finance, HR/People, Product, or Data — based on own discovery and prioritization.
Your Key Competencies
Must have:
- Full-stack engineering: TypeScript/JavaScript, React or comparable frontend framework, production-grade component design — enough to define architecture, review AI output critically, and make sound technical decisions.
- Backend engineering: API design, server-side logic, authentication flows, database modeling — build and own production backend systems end-to-end.
- AI-native development: Uses AI coding tools (Claude Code, Cursor, or comparable) as the primary developer — not as autocomplete. Directs, reviews, and takes full accountability for everything AI produces. When AI gets it wrong, catches it, fixes it, and builds guardrails.
- AI model evaluation: Actively monitors new model releases across providers; evaluates rationally — capability, cost, latency, reliability; integrates when it makes sense. Never runs last quarter’s stack out of inertia.
- LLM workflow design: Designs LLM-powered workflows with validation, guardrails, and human-in-the-loop patterns. Builds AI-driven maintenance loops that feed logs and anomalies back into workflows that diagnose and improve live systems.
- Multi-agent orchestration: Directs AI agents across build, test, QA, and deployment — treats them as a managed team, not a single tool.
- Security discipline: Secrets management, least-privilege access control, user data handling, audit logging — especially for user-facing systems.
- REST API integration: Auth, rate limits, retries, error handling, edge cases.
- SQL: Querying, validation, transformation, data quality checks.
Nice to have
- Familiarity with paid media APIs (Meta, Google, TikTok) or marketing data pipelines
- Experience with customer engagement and tracking systems — event schemas, analytics pipelines, behavioral data
- Experience with GDPR-sensitive user data in consumer products
- Prior work in a product company with real scale
Your soft skills
- Strong problem identification instinct — spots problems others have not yet articulated
- High ownership and accountability — ships, maintains, and improves; does not prototype and move on
- Structured thinking under ambiguity — scopes clearly, defines success criteria, executes without hand-holding
- Strong cross-functional communication — translates business pain into working systems; output understandable to non-technical stakeholders; aligns before building
- Reliability mindset — monitoring, failure handling, self-improving systems
- Documentation discipline — creates systems others can operate
Your impact in this role
- Full ownership and control over our most critical systems — marketing intelligence and customer engagement — with solutions tailored precisely to how we operate and designed to outperform any generic alternative
- Full-stack marketing operating system that turns data across all channels into autonomous campaign decisions and creative output
- Personalization at scale: individual-level engagement and marketing decisions informed by behavioral data, built in collaboration with Data Science and Analytics
- Company-wide leverage: high-impact systems across Marketing, Finance, HR/People, Product, and Data — discovered, built, and operated by one person using AI as the development engine
- Higher execution velocity across all teams through AI-powered automation
- Raised AI development capability across the existing engineering team
Your Background – Education & Experience
- 5–8+ years in software engineering, systems engineering, growth engineering, or similar high-output builder roles — with demonstrated experience shipping production systems to real users.
- Academic background in a technical field — Computer Science, Software Engineering, Mathematics, or comparable — that provided a solid foundation in engineering concepts, data structures, system design, and software quality. Demonstrably equivalent professional training accepted.
- Proven ability to design clean, maintainable systems: modularity, testing, code quality, performance, security — not just prototypes.
- Startup/scale-up experience strongly preferred.
- Has fully transitioned to AI-driven development: uses Claude Code, Cursor, or comparable tools as the primary developer. No longer writes code manually. Can review, validate, and take full ownership of every line AI produces.
- Candidates who rely on AI to generate code without understanding architecture, security, and maintainability are not a fit.
Apply today
IIf you meet the minimum requirements and are interested in applying for this position, please send your details to careers@key-talents.com with “AI Business System Engineer ”, in the subject line.