Design and evolve AI infrastructure platform, standardize agent-tool integration, and lead platform evolution. 5+ years of experience in cloud platform engineering, including 2+ years building AI/ML infrastructure at enterprise scale. Proven experience leading multiple projects and mentoring engineers.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Job Description
Senior AI Architect – AI Infrastructure & Agent Platform (Remote, Europe)
Our client is scaling their enterprise AI platform and needs a hands‑on Senior AI Architect to own the infrastructure, automation, and reliability behind their production‑grade AI agents. This is a role for someone who thrives in high‑impact environments where agents must run with speed, safety, and repeatability.
You’ll work with data scientists, platform engineers, and multiple agent teams to design and evolve the cloud‑native platform that powers every agent across the organisation.
Fully remote, open to candidates based anywhere in Europe.
Key Responsibilities
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- Design and evolve the core AI infrastructure platform (AWS, Kubernetes, CI/CD, observability) with strict SLAs across uptime, latency, and cost‑per‑prediction
- Standardise agent‑tool integration using MCP (Model Context Protocol) and production‑grade patterns - no ad‑hoc scripts or brittle connectors
- Build extensible service layers (MCP servers, vector stores, feature stores, auth gateways) that multiple agent teams reuse safely with consistent security and performance
- Lead platform evolution - multi‑region, zero‑downtime deployments, automated cost optimisation - enabling teams to ship faster without platform bottlenecks
- Own delivery across multiple concurrent projects, guiding engineers and setting technical direction across workstreams
- Codify platform patterns into self‑service tooling (IaC templates, MCP SDKs, deployment playbooks) to reduce onboarding from weeks to hours
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Required Experience
- 5+ years in cloud platform engineering, including 2+ years building AI/ML infrastructure at enterprise scale
- Proven experience leading multiple projects and mentoring engineers across parallel workstreams
- Deep expertise with AWS (ECS, Lambda, API Gateway, Bedrock Agent Core) and infrastructure‑as‑code (Terraform, CDK)
- Hands‑on experience implementing MCP or similar agent‑tool integration patterns in production
- Strong knowledge of streaming/real‑time systems (Kafka, Redis Streams) and GPU scheduling for inference workloads
- Production reliability expertise — circuit breakers, graceful degradation, chaos engineering, capacity planning
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