[Hiring] Senior AI Platform Engineer @Dev.Pro

Role Description

We are seeking a Senior AI Platform Engineer to own the core platform layer that powers every EasyBee AI agent in production — from multi-tenant agent configuration and schema architecture, to data pipeline contracts, evaluation harnesses, and customer onboarding automation. This role sits at the intersection of backend platform engineering, LangGraph-based orchestration, and AI evaluation systems.

• Own the infrastructure that makes all features possible: the agent orchestration graph, the customer configuration schema, end-to-end conversation logging, automated eval pipelines, and the scripts that deploy new customers in under 30 minutes.
• If you love owning systems that other engineers depend on, ship at high velocity across a wide surface area, and take pride in leaving codebases cleaner than you found them — we want to hear from you.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
• Proficient or Advanced use of agentic workflows for coding in tools like Cursor AI or Claude Code.
• 4+ years building and owning production-grade backend systems in Python.
• Proven experience owning a core platform or shared infrastructure layer used by multiple teams or customers.
• Hands-on track record with multi-tenant system design — schema isolation, config-driven parameterization, and deployment automation.
• Experience building evaluation harnesses for LLM-based systems with quantitative metrics.

Requirements

• Strong systems thinking — ability to see how schema decisions in the core platform ripple downstream to eval, logging, onboarding, and customer deployments.
• Comfort owning wide surface area — this role crosses platform, data, eval, and ops without a narrow specialization.
• High individual shipping velocity — ability to close multiple GitHub issues per day with clean PRs and minimal back-and-forth.
• Strong schema discipline — treats data contracts as first-class artifacts, not afterthoughts.
• Ability to work autonomously with minimal supervision in a fast-moving startup environment.
• Strong written communication for PR descriptions, Notion documentation, and deployment SOPs.

Benefits

• 30 paid days off each year — use them for vacation, holidays, or personal time.
• 5 paid sick days, up to 60 days of medical leave, and 6 paid days off for family events like weddings, funerals, or having a baby.
• Partially covered health insurance - after probation.
• Wellness bonus for gym memberships, sports nutrition, and similar needs.

What success looks like

• A core platform where every new customer can be deployed in under 30 minutes from a configuration template + KB content — zero custom code per customer.
• An eval pipeline with automated simulation scenarios and distributed tracing that runs on every PR and blocks deployment when scores drop below threshold.
• A conversation logging system that captures every production interaction with full metadata, enabling the data strategy and future fine-tuning.
• A clean, schema-validated platform codebase where new nodes, customers, and capabilities can be added with predictable behavior and no silent regressions.
• A deployment SOP so reliable that any engineer on the team can onboard a new customer without escalation.