Enablement Platform Engineer Azure w Warszawa, Polska - Jobeax
Opis oferty
Enablement Platform Engineer Azure w Warszawa, Polska
Endava
1k - 1700
Poland, Warszawa
Enablement Platform Engineer Azure w Warszawa, Polska is listed on Jobeax. Browse 110,000+ vacancies available.
Company Description Technology is our how. And people are our why. For over two decades, we have been harnessing technology to drive meaningful change. By combining world-class engineering, industry expertise and a people-centric mindset, we consult and partner with leading brands from various industries to create dynamic platforms and intelligent digital experiences that drive innovation and transform businesses. From prototype to real-world impact - be part of a global shift by doing work that matters. Job Description As part of Endava's strategic partnership with WTW, who provide data-driven, insight-led solutions in the areas of people, risk and capital, we're building dedicated software engineering teams to support WTW's Insurance Consulting and Technology Division. WTW's Insurance Consulting and Technology business is a global leader in P&C, Life and Health insurance software and advisory services, with over 1,700 colleagues across 35 markets. More than 1,000 insurers worldwide trust our combination of advisory insight and advanced software to help them navigate complexity and drive sustainable growth. Joining Endava, you'll work exclusively with WTW to help embed AI-enabled engineering practices, modern ways of working and deep insurance technology expertise, contributing to the next generation of products and services for insurers worldwide. Working as part of a dedicated team established through a Build-Operate-Transfer (BOT) model, you'll collaborate closely with WTW while building your career as an Endava employee, supporting the long-term success of this strategic partnership. About the Role As an AI Platform Engineer, you will help build, operate and evolve ICT's internal AI Engineering Platform, working on the services and tooling that enable AI-assisted software engineering across the technology delivery organisation. You will join the Engineering Enablement team, which develops the internal engineering platform used by software engineers across the organisation. Rather than delivering business applications directly, you will focus on the platform capabilities, automation and developer experience that help engineering teams adopt Agentic Engineering practices safely and effectively. WTW has developed an agentic engineering harness which combines GitHub Copilot, AI agents, engineering loops, Azure cloud services and developer tooling to accelerate software delivery, automate engineering activities and improve the overall developer experience. Your role will be supporting the continued development and operation of this harness and the surrounding engineering platform toolset which supports it. This is an ideal opportunity for engineers who enjoy solving infrastructure and platform challenges, working across cloud infrastructure, automation, observability, AI tooling, developer platforms and engineering governance, and contributing to one of ICT's strategic investments in AI-assisted software engineering. What Success Looks Like In this role you will: · Help build, operate and evolve ICT's internal AI Engineering Platform, enabling software engineering teams to adopt AI-assisted and Agentic Engineering practices. · Develop secure, reliable and reusable platform services across AI tooling, developer enablement, observability, automation and engineering governance. · Improve developer experience by creating self-serve capabilities, clear documentation, integration patterns and automation that make engineering workflows easier to adopt. · Design, automate and maintain cloud infrastructure on Microsoft Azure using Infrastructure as Code and modern CI/CD practices. · Strengthen the reliability, scalability, security and operational resilience of shared engineering platform services. · Collaborate with Engineering Managers, Architects, Platform Engineers and software engineering teams to support platform adoption and continuous improvement. · Actively learn, share knowledge and contribute to a positive engineering culture within the Engineering Enablement team and wider ICT engineering community. Key Responsibilities AI Engineering Platform · Develop, maintain and evolve platform services supporting AI-assisted software engineering. · Build capabilities that enable software engineering teams to adopt Agentic Engineering practices. · Support continuous evolution of WTW's internal AI Engineering Platform. · Improve developer experience through reusable engineering platform capabilities and automation. Platform Services · Own and evolve internal platform services including RAG knowledgebase systems, observability, package management and code quality tooling. · Support operational ownership of GitHub Copilot enablement services. · Contribute to engineering governance capabilities supporting AI-assisted development. · Maintain platform services that enable engineering teams to safely and efficiently consume AI capabilities. Cloud & Platform Engineering · Design, automate and maintain cloud infrastructure running on Microsoft Azure. · Develop Infrastructure as Code using OpenTofu/Terraform. · Build and improve CI/CD pipelines supporting engineering platform services in both Azure DevOps and GitHub. · Develop automation solutions supporting engineering workflows and platform operations with a high emphasis on self-serve operations. · Improve scalability, reliability, and operational resilience of engineering platform services. Observability & Operations · Implement and operate monitoring, telemetry and observability solutions supporting engineering platform services. · Improve operational visibility through logging, tracing and metrics. · Troubleshoot platform issues and support engineering teams adopting platform capabilities. · Participate in production support and operational improvements where required. Engineering Enablement · Work closely with software engineering teams to support adoption of AI-assisted development tools. · Collaborate with Engineering Managers, Architects and Platform Engineers to continuously improve engineering workflows. · Promote engineering best practices, automation and platform governance. · Evaluate emerging AI engineering technologies and contribute to future platform direction. Qualifications Required Skills and Experience Platform Engineering · 4+ years of experience in Platform Engineering, Cloud Engineering, DevOps Engineering or Software Engineering. · Experience building or operating shared engineering platforms or internal developer platforms. · Strong understanding of platform automation and engineering enablement. Cloud & Infrastructure · Strong experience with Microsoft Azure. · Experience with Docker and containerised workloads. · Experience with Infrastructure as Code using OpenTofu or Terraform. · Experience developing and maintaining CI/CD pipelines using Azure DevOps and GitHub. Automation · Experience automating engineering workflows and cloud infrastructure. · Strong scripting skills using PowerShell, Python or Bash. · Experience designing reusable automation solutions. Observability · Experience with observability platforms such as Datadog, Azure Monitor, Grafana or Prometheus. · Understanding of telemetry, logging and distributed tracing. · Experience supporting production platform services. Engineering Practices · Strong understanding of modern software engineering practices. · Experience collaborating with multiple engineering teams. · Excellent analytical and problem-solving skills. · Strong communication and stakeholder management skills. · Passion for continuous improvement and engineering excellence. Preferred Skills and Experience · Experience with GitHub Copilot and AI-assisted software development tools. · Experience with internal developer platforms, platform engineering or developer experience capabilities. · Familiarity with SonarQube, package management platforms and engineering governance tooling. · Familiarity with vector databases, Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs). · Experience contributing to AI engineering platforms or shared engineering services. · Understanding of service management practices in an enterprise technology environment.
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