Staff AI Infrastructure / Platform Engineer (IT)
On-siteLimerick, Munster, Ireland
Job Summary
Build and operate the platform and tooling teams use to develop, deploy, and monitor AI-powered applications. Create reusable components, APIs, and integration patterns that accelerate AI adoption across the enterprise. Own integrations with cloud model providers like AWS Bedrock and Google Vertex AI, managing usage, cost, and reliability. Serve as a key point of contact for internal users, understanding their AI use cases and routing them to the appropriate approach. Drive observability through logging, metrics, and tracing to debug system failures. Uphold AI engineering standards regarding security, compliance, cost, and governance within a multi-cloud environment. Contribute to MLOps and LLMOps practices as the team matures. Requires solid Python, cloud fundamentals, and a strong operations mindset.
Required Qualifications
- Solid software engineering fundamentals
- Strong, working Python
- Hands-on experience with at least one major cloud provider
- Working knowledge of cloud fundamentals: IAM/permissions, networking basics, and a healthy awareness of cost
- Docker and comfort working with containerized applications
- A strong operations and reliability mindset
- Experience building or operating platforms, internal tooling, or services that other engineers depend on
- Strong communication and a service mindset
- A demonstrated ability to learn fast
- Foundational Knowledge: The LLM landscape (hosted model via gateway, tokens, cost, latency, context limits)
- Foundational Knowledge: RAG (retrieval-augmented generation)
- Foundational Knowledge: Fine-tuning (training process, GPU compute)
- Foundational Knowledge: Agentic AI (reasoning, planning, autonomous workflows, orchestration frameworks like LangChain)
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field (or equivalent practical experience)
- 4-6 years of platform engineering experience
- Experience delivering and operating production systems in cloud environments, with an eye to security and reliability
- Export licensing approval from the U.S. Department of Commerce - Bureau of Industry and Security and/or the U.S. Department of State - Directorate of Defense Trade Controls
Desired Qualifications
- AWS is a plus given our stack
- Strong GCP/Azure experience
- Exposure to CI/CD (GitHub Actions, GitLab CI, or similar)
- Exposure to Infrastructure as Code (Terraform, Pulumi, CloudFormation)
- Kubernetes, or a strong desire to learn it
- Familiarity with the broader model provider ecosystem (OpenAI, Anthropic, Hugging Face, etc.)
- Hands-on exposure to ML/LLM tooling or agentic systems
- A background in distributed systems, scalability, or performance optimization for demanding workloads
- Experience including cloud-native infrastructure, backend services, or internal developer platforms
- Exposure to the AI/ML or MLOps/LLMOps space
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