AI Architect: LLM Platform, Governance & Safety

AutoThink Group

Rochdale

Hybrid

GBP 120,000 - 180,000

Full time

4 days ago
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Job summary

AutoThink Group seeks an AI Architect to own the technical blueprint across retrieval, evaluation, safety, routing, and cost governance for all products. You will set standards the group builds on and drive architectural decisions at scale.

You'll build a group-wide reference architecture for LLM, RAG and agent workflows, implement a model-routing layer, and develop evaluation harnesses to gate every production release while ensuring privacy and GDPR alignment.

Qualifications

  • 8+ years engineering experience with 3+ shipping production LLM/ML systems.
  • Deep knowledge of transformer models, RAG, vector search and agent frameworks.
  • Experience designing systems at scale on AWS, GCP or Azure.
  • Strong opinions on evaluation, safety and cost control with receipts.
  • Excellent written and verbal communication; able to pitch to board and staff engineer.

Responsibilities

  • Own the technical blueprint for AutoThink products across retrieval, evaluation, safety, routing, cost governance and orchestration.
  • Develop a group-wide reference architecture for LLM, RAG and agent workflows.
  • Create model-routing and cost governance layer to select providers per request.
  • Build evaluation harnesses and offline benchmarks gating production releases.
  • Define guardrails, PII handling and audit trails aligned with UK GDPR guidance.

Skills

LLM/ML systems
RAG & vector search
Agent frameworks
Cloud platforms (AWS/GCP/Azure)
Evaluation & safety
Cost governance
Effective communication

Tools

AWS
GCP
Azure
Vector databases
Model routing

Job description

AutoThink Group seeks an AI Architect to own the technical blueprint across retrieval, evaluation, safety, routing, and cost governance for all products. You will set standards the group builds on and drive architectural decisions at scale.

You'll build a group-wide reference architecture for LLM, RAG and agent workflows, implement a model-routing layer, and develop evaluation harnesses to gate every production release while ensuring privacy and GDPR alignment.

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