We are hiring an AI Systems Engineer to design compute pipelines for custom LLM routing gateways, write core execution logic for multi-agent systems, and deploy infrastructure at scale. The ideal candidate is a software engineer with cloud architecture expertise and experience with AI systems. Active GCP certification is required.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Job Description
Hiring: AI Systems Engineer (GCP Certified)
About Bayseian We do not build traditional software; we build autonomous work systems. Bayseian is an AI-native consultancy that transitions global enterprise clients toward outcome-based, multi-agent architectures. We operate with strict precision, favoring highly optimized, minimalist engineering over bloated infrastructure.
The Role We are scaling our engineering operations and looking for AI Systems Engineers. You are a software engineer first and a cloud architect second. You will design the compute pipelines for custom LLM routing gateways, write the core execution logic for multi-agent systems, and deploy the infrastructure that powers them at the scale of national giga-projects.
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To Apply: If your engineering standards match ours and your credential is active, send me a direct message with a link to your verified Google Cloud Certification badge and a brief overview of an AI-driven system you built end-to-end (or email: tech@bayseian.com).
The Baseline (Strict Prerequisites): We maintain uncompromising technical standards. To ensure immediate alignment with our enterprise deployments, you must meet the following criteria:
- Active Certification: You must currently hold an active GCP Professional Cloud Architect or GCP Professional Data Engineer credential.
- Core SWE Foundation: You write clean, scalable code (Python/TypeScript/Node) and understand complex system design. You don't just provision infrastructure; you build the connective tissue.
- The AI Infrastructure Stack: Proven, hands-on experience provisioning and integrating AI systems at scale. You must be fluent with Vertex AI, relational databases tuned for AI (AlloyDB), VectorDBs (pgvector, Pinecone, etc.), and Agent Development Kits (ADKs) or custom orchestration frameworks.
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The Environment & Execution:
- Outcome-Oriented: We sell results, not hours. High autonomy is given to those who deliver.
- Elite Standards: Secure architecture, algorithmically efficient code, and precise execution are expected daily.
- Remote Integration: Fully remote, strategically bridging our UK and Middle East operations.
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