Senior Platform Engineer

Intellias; España; Presencial; EUR 70.000 - 100.000; Jornada completa

Descripción de la vacante

Intellias seeks an experienced DevOps/Platform Engineer to design, build, and maintain the internal infrastructure platform. You will work with Python services and tooling, collaborating with engineering teams to translate pain points into platform features.

You will implement IaC with Ansible and Terraform, manage migrations, and enhance observability with Prometheus and Grafana. Strong Linux, CI/CD, security, and collaboration skills are required.

Formación

• 5+ years of experience as a DevOps/platform/systems engineer with hands-on infrastructure and platform engineering.
• Proficient in Python for production scripting and tooling, not just deployment.
• Strong Linux fundamentals and OS troubleshooting across fleets of machines.
• Hands-on IaC experience with Ansible and Terraform, treated as code with reviews and tests.
• Migration experience with OS and workload migrations and audits of existing workloads.
• Kubernetes knowledge for cluster lifecycle management and workload migration.
• CI/CD experience with GitLab CI, GitHub Actions, or Jenkins and related practices.
• Observability familiarity with Prometheus and Grafana; use metrics to diagnose distributed systems.
• Security awareness around secrets management and dependency hygiene.

Responsabilidades

• Designing, building, and maintaining Python services, libraries, and CLI tooling for the internal platform.
• Collaborating with engineering teams to understand workflows and convert pain points into platform features.
• Replacing manual operations with codified, self-service workflows for reproducible environments.
• Building observability into the platform via metrics, logging, and alerting to surface failures early.
• Owning production issues end-to-end from triage to root cause analysis and preventive fixes.
• Managing and scaling compute and storage across on-prem hardware as usage grows.
• Integrating security by default: secrets management, least-privilege access, and dependency hygiene.

Conocimientos

DevOps

Platform engineering

Python

Linux

IaC

Kubernetes

CI/CD

Observability

Security awareness

Collaboration

Problem solving

Herramientas

GitLab CI

GitHub Actions

Jenkins

Ansible

Terraform

Kubernetes

Prometheus

Grafana

Airflow

Descripción del empleo

Our client is a leading global investment management company headquartered in London. It manages over $228 billion in assets and serves institutional investors, pension funds, wealth managers, and other sophisticated clients worldwide. The firm specializes in quantitative investing, alternative investments, systematic trading strategies, and technology-driven asset management. Data science, machine learning, and AI are core components of its investment and research processes.

As part of our collaboration we will focus on two foundational capabilities required to enable safe and scalable AI adoption across the enterprise: Agentic Security and AI-Ready Data Foundations.

Requirements:

• 5+ years of experience as a DevOps / platform / systems engineer, with a track record spanning both infrastructure operations and broader platform engineering — not purely a helpdesk/ops role.
• Software development background: comfortable reading and writing production code, understanding how applications are configured and run, not just how they're deployed. This helps when working directly alongside dev teams on their workloads.
• Python (required): solid, production-level scripting and tooling ability — automation, integrations, and support for platform/migration work. Not necessarily building a Python platform product, but extending and maintaining real code.
• Linux systems (required): strong fundamentals — processes, networking, storage, permissions, package management. Comfortable troubleshooting at the OS level across a fleet of machines.
• Infrastructure as code: hands-on production experience with Ansible and Terraform. Able to write, review, and maintain IaC that's treated like application code (version control, review, testing).
• Migration experience (highly relevant): direct experience with, or strong aptitude for, OS-level migrations (e.g., CentOS to Ubuntu) and application/workflow migrations (e.g., Airflow 1.x DAGs to Airflow 2.x). Comfortable auditing existing workloads, identifying compatibility gaps, and planning cutover.
• Kubernetes: working knowledge of how clusters are built, upgraded, and retired, and how workloads get moved between clusters with minimal disruption — relevant to migrating teams off unsupported clusters onto supported ones.
• CI/CD: experience with at least one major pipeline tool (GitLab CI, GitHub Actions, Jenkins) and the practices around it — automated testing, staged rollouts, safe release processes.
• Observability: familiarity with Prometheus, Grafana, or equivalent, and the ability to use monitoring data to diagnose issues across distributed systems.
• Security awareness: practical understanding of secrets management, access control, and dependency/supply-chain hygiene — enough to spot and flag risk, even if not the platform's primary security owner.
• Collaboration and communication: able to sit with a dev team, understand their workload and pain points, and communicate technical trade-offs clearly to both engineers and non-engineers.
• Problem-solving: persistence in root-causing failures rather than just restarting services or working around symptoms.

Responsibilities:

• Designing, building, and maintaining the Python services, libraries, and command-line tooling that make up the internal infrastructure platform.
• Working with the engineering teams who consume the platform to understand their workflows and turn recurring pain points into platform features.
• Replacing manual infrastructure operations with codified, self-service workflows, so that environments are reproducible, reviewable, and safe to change.
• Building observability into the platform through metrics, structured logging, and alerting, so failures surface before consuming teams report them.
• Owning production issues in the platform end to end, from triage and root cause analysis through the code or configuration change that prevents a recurrence.
• Managing and scaling the compute and storage the platform provisions across on-premises hardware, balancing performance against cost as usage grows.
• Building security into the platform by default: secrets management, least-privilege access, dependency hygiene, and an auditable history of every infrastructure change.
• Evaluating new tools, libraries, and patterns, and folding the ones that earn their place into the platform roadmap.