MidFull TimeEN
About MoonTech
MoonTech is a performance marketing platform for influencer commerce. We connect brands and creators and help campaigns deliver measurable outcomes. We're building a scalable, self-serve platform where performance improves as more campaigns run, powered by strong workflows, reliable data, and automation.
About the Role
We're looking for an AI Engineer with 5+ years of experience and strong full-stack skills to join the Automation Squad. You'll build AI-enabled workflows and automation that reduce manual effort, increase platform scalability, and improve speed and reliability across core operations. This is a hands-on role spanning model integration, backend services, and product-grade interfaces.
Key Responsibilities
Build and ship AI-enabled automation that improves scalability, reliability, and cost-to-serve across MoonTech workflows.
Design, implement, and own production services for AI features — APIs, orchestration, background jobs, and monitoring.
Build full-stack product surfaces for internal tools and user-facing automation, including clean UX, resilient backend logic, and secure data handling.
Partner with Product, Data, and Engineering to translate business workflows into automated systems with clear success metrics.
Implement evaluation and quality loops for AI features, including test datasets, online measurement, and feedback-driven iteration.
Integrate with third-party systems and internal services (payments, CRM, attribution/analytics, messaging, partner platforms) to automate end-to-end journeys.
Establish operational excellence for AI workflows: observability, incident readiness, cost controls, rate limiting, and reliability safeguards.
Contribute to platform standards around data privacy, access control, and safe deployment patterns
Shape AI use cases in partnership with Product and Engineering, and measure impact through clear evaluation metrics.
Use AI tools and automation in your own day-to-day work to streamline analysis, documentation, and planning.
What Success Looks Like
Key operational workflows become automated, measurable, and scalable — without linear headcount growth.
AI-enabled features ship reliably, are monitored in production, and improve through disciplined iteration.
Automation reduces cycle time, error rates, and manual interventions across core journeys.
Internal stakeholders trust the tools and services as stable, secure, and easy to operate.
Requirements
5+ years of experience shipping production software, including AI-enabled systems and full-stack delivery.
Strong backend engineering skills — API design, distributed systems basics, async processing, queues, caching, and observability.
Strong full-stack capability, including building usable web interfaces integrated with backend services.
Practical experience with modern AI stacks: LLM integration, prompt engineering, RAG, embeddings, and model routing — with emphasis on production quality and measurable outcomes.
Experience building automation workflows and integrations across systems (webhooks, event-driven architecture, ETL/ELT basics, third-party APIs).
Solid engineering fundamentals: testing, CI/CD, security basics, and reliability mindset.
Clear communication and strong ownership in cross-functional environments.
Nice to Have
Experience with data pipelines and analytics instrumentation (event tracking, logging, metric governance).
Experience building internal tooling and operational platforms (admin panels, workflow orchestration, case management).
Experience with cloud infrastructure and deployment (AWS/GCP/Azure), containers, and scalable storage patterns.
Familiarity with privacy-sensitive environments and access control patterns.
