Staff AI Platform & Reliability Engineer
eJam
| Company | eJam |
| Category | Uncategorised |
| Location | Santa Ana |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 30 Jul 2026 |
| Last verified | 2 Aug 2026 |
| Source | Employer career page (workable) |
Description
Location : Santa Ana, California — on-site Employment type : Full-time Salary : $172,000 – $220,000 About us Created.ai is an AI-powered creative platform combining text, image and video generation into production tools for commercial creative work. The platform is operated by eJam, a multi-brand consumer products and technology company. We are expanding our engineering team with two appointments covering our AI platform infrastructure and our product engineering surface. Both roles carry substantial technical ownership and report directly into engineering leadership. This position is AI-native by design. Our engineers work with agentic coding tools as a primary part of their daily workflow, which allows a small team to operate at a scope that would conventionally require a much larger one. We are looking for engineers whose judgement, architectural thinking and review discipline scale that leverage rather than being replaced by it. Role summary We are seeking a Staff Engineer to take ownership of the AI generation services, provider integrations, billing integrity, tenant security and overall platform reliability underpinning created.ai. The role is Python and GCP-first, with sufficient TypeScript proficiency to trace and modify cross-service contracts. This is a senior individual contributor position with architectural authority over the platform layer. Key responsibilities Own the design, delivery and operation of AI generation services and all third-party provider integrations Ensure billing and usage-metering integrity across the platform, including reconciliation and credit accounting Maintain tenant isolation and platform security controls Lead reliability engineering: failure handling, degradation strategy, capacity and incident response Strengthen deployment safeguards, observability and cost attribution Set technical standards for the Python services and mentor engineers working within them
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