Platform Engineer
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At a glance
Technologies & skills
What you'll be doing
Platform Engineer role in Dublin (Hybrid) for the financial services industry. Focus on platform management, cloud, CI/CD, IaC, containerized environments, LLM infrastructure, and automation. Requires 7+ years of DevOps/cloud infrastructure experience and strong skills in Kubernetes, AWS, Terraform, Ansible, and Linux.
Key requirements
Must-have
- 7+ years industry experience with DevOps/cloud infrastructure
- Strong understanding of automation and deployment through Infrastructure as Code
- Experience with Kubernetes
- Experience with AWS
- Experience with Terraform
- Experience with Ansible
- Systems proficiency across Linux
Experience: 7+ years industry experience with DevOps/cloud infrastructure
Role signals
- Technical focus
- DevOps/cloud infrastructure, platform management, automation, IaC, containerization, LLM infrastructure
- Architecture / system design
- Indicated in the listing
- Hands-on vs management
- Hands-on
Similar jobs
Full job description
Platform Engineer
Dublin (Hybrid)
€90,000-€110,000
Our client in the financial services industry is looking for an experienced Platform Engineer to join their team to help fuel innovation. In return, they will gain hands-on experience with modern technologies, in-valuable and transferrable skills, a flexible working model, and attractive compensation.
What you'll do
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Platform management across cloud, CI/CD, architecture, IaC, containerised environments
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LLM infrastructure- strong understanding of ai design
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Strong understanding and experience with Kubernetes and AWS
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Pipeline optimisation, security principles first
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Terraform/Ansible for automation
What you'll bring
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A strong 7+ years industry experience with a deep understanding of DevOps/cloud infrastructure
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Understands automation and deployment through Infrastructure as Code
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Systems proficiency across Linux, SaaS, networking
What you'll get
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Competitive salary
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Bonus
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Healthcare plans
Reperio Human Capital acts as an Employment Agency and an Employment Business.
Interview prep pack
Grounded in this listing. Use it to prepare examples before you apply.
Your interview focus
Based on this listing, the Platform Engineer role focuses on managing cloud-based platforms, automating infrastructure, and supporting containerized environments using modern DevOps tools within a financial services context.
- Hands-on DevOps/cloud infrastructure expertise·High
- Automation and IaC proficiency·High
- Containerization and Kubernetes management·High
- Security-first mindset in platform operations·Medium
Only have 30 minutes?
Follow a focused preparation plan based on this job.
Start 30-minute prep
Your 30-minute plan
Review and Summarize Key Projects
0–8 minList and outline 2-3 major projects involving Kubernetes, AWS, Terraform, and Ansible, focusing on your role and outcomes.
Refresh on CI/CD Security Practices
8–14 minStudy recent best practices and prepare examples of integrating security into deployment pipelines.
Practice Explaining LLM and AI Infrastructure
14–20 minPrepare a concise explanation of LLM infrastructure and your experience or approach to supporting AI workloads.
Prepare Questions for the Interviewer
20–25 minSelect and tailor 3-4 questions from the provided list to ask during the interview.
Review Linux and Networking Troubleshooting Scenarios
25–30 minRecall specific incidents where you diagnosed and resolved Linux or networking issues.
Talking points
, 6 itemsKubernetes and Container Orchestration
Demonstrate your experience deploying, scaling, and managing containerized applications, as this is a core requirement.
Infrastructure as Code with Terraform and Ansible
Showcase your ability to automate infrastructure provisioning and configuration, which is central to the role.
AWS Cloud Platform Expertise
Highlight your hands-on experience with AWS services, as cloud management is a key responsibility.
CI/CD Pipeline Optimization and Security
Prepare examples of how you have improved deployment pipelines and embedded security best practices.
Linux Systems and Networking Proficiency
Demonstrate your foundational skills in Linux and networking, which underpin platform reliability and performance.
LLM Infrastructure and AI Design
Be ready to discuss your understanding of large language model infrastructure and AI system design, as this is specifically mentioned.
What to research
, 4 itemsReview Kubernetes Architecture and Operations
Refresh your knowledge of deploying, scaling, and maintaining Kubernetes clusters, including troubleshooting and upgrades.
Deep Dive into Terraform and Ansible Projects
Prepare to discuss specific automation projects using these tools, focusing on modularity, reusability, and collaboration.
AWS Service Management
Be ready to explain your experience with AWS services, especially in designing, automating, and securing cloud infrastructure.
CI/CD Pipeline Security
Review best practices for integrating security into CI/CD pipelines and be prepared to discuss real-world implementations.
Questions to ask
, 6 itemsWhat are the main challenges your platform team is currently facing?
Why ask this? To understand the immediate priorities and pain points you would help address.
How is the platform engineering team structured and how do they collaborate with development and security teams?
Why ask this? To clarify team dynamics and cross-functional collaboration.
What is the current state of your CI/CD pipelines and what improvements are you targeting?
Why ask this? To gauge the maturity of automation and where your skills can add value.
How does the team support LLM infrastructure and what are the expectations for this area?
Why ask this? To clarify the scope and depth of AI/ML infrastructure responsibilities.
What is the process for evaluating and adopting new technologies or tools within the platform?
Why ask this? To understand the openness to innovation and your potential influence on technology choices.
How is success measured for platform engineers in your organization?
Why ask this? To align your contributions with the team's goals and performance metrics.
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