Ai Engineer

AI Engineer — Automation Squad

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.