12 дней назад
Platform Engineer (AI Enablement)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Platform Engineer (AI Enablement) (AI infrastructure and agentic workflows): Building governed model-access infrastructure, secure production environments, and developer tooling for AI agents with an accent on safety, observability, cost control, and operational reliability. Focus on designing scalable platform primitives, implementing governance and auditability, and operating distributed systems with Kubernetes, cloud infrastructure, and infrastructure as code.
Location: London, United Kingdom
Company
is an AI company developing platforms and tools for safe, reliable, and scalable AI adoption.
What you will do
- Design, build, and operate infrastructure for safe, reliable, and cost-effective access to AI models and tools.
- Build runtimes, services, and developer tooling for production agentic workflows.
- Implement observability for cost, performance, reliability, and usage through metrics, tracing, and logging.
- Develop governance, security, compliance, auditability, reusable platform primitives, integrations, and guardrails.
- Partner with Security, IT, and engineering teams on platform integration, policy, rollout, documentation, and adoption.
- Own projects end to end, support platform users, and participate in the on-call rotation for critical systems.
Requirements
- 3+ years of software engineering experience building APIs, services, and developer tooling.
- Strong system-design fundamentals and experience building and operating platforms used by engineering teams.
- Hands-on experience with cloud infrastructure, Kubernetes, and infrastructure as code.
- Familiarity with LLM APIs, model providers, gateways, MCP, agent frameworks, and retrieval-augmented generation.
- Experience with observability in distributed systems and with authentication, authorization, and auditability.
- Clear communication, documentation, ownership, and the ability to work effectively in an ambiguous, fast-moving environment.
Nice to have
- Experience operating an LLM gateway or model-routing layer in production, including cost controls and budget enforcement.
- Experience with agent orchestration frameworks or tool-calling protocols such as MCP.
- Exposure to AI governance, model risk management, or responsible AI practices.
- Experience in autonomy, robotics, or another safety-critical field.
Culture & Benefits
- Opportunity to join an early platform team and shape AI infrastructure used across the organisation.
- Ownership of technical decisions and projects across the full delivery lifecycle.
- Close collaboration with Security, IT, and engineering teams.
- Participation in an on-call rotation with out-of-hours support for critical systems when required.
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