About this opportunity

We're building an AI-native Internal Developer Platform (IDP) and are hiring multiple Platform Engineers with complementary strengths (CI/CD, Developer Portal & Golden Paths, Observability/SRE, DevSecOps, AI Tooling). You don't need to cover everything, we're intentionally building a team with different profiles so that, together, we can evolve the full stack of the platform.

Key Responsibilities

• Build and evolve a highly usable, AI-native Internal Developer Platform (IDP) that delivers an exceptional Developer Experience (DX), reduces cognitive load for product teams, and enables fast, reliable delivery.
• Own the platform "as a product": contribute to roadmap, prioritize improvements based on developer feedback and telemetry, and drive adoption through great UX and clear value.
• Collaborate empathetically with developers: obsessively understand pain points and workflows and turn insights into platform features that continuously improve the DX.
• Optimize and scale GitLab-based CI/CD services to support fast, reliable, and compliant software delivery (runners, templates, pipelines at scale, policy enforcement).
• Lifecycle management (LCM) of the IDP and its components: versioning, upgrades, deprecation strategies, backwards compatibility, reliability, and operational readiness.
• Design and own the IDP observability, ensuring developers have clear insights, actionable data, and self-service troubleshooting capabilities (dashboards, alerts, traces, runbooks).
• Drive cloud-native and GitOps practices using Kubernetes, Helm, Terraform, focusing on repeatability, safety, and developer self-service.
• Implement secure-by-default workflows, including vulnerability management, pipeline security, supply-chain integrity, and S&I-aligned guardrails that keep teams compliant without slowing them down.
• Develop and enhance of the IDP Portal (Backstage-based), providing intuitive interfaces, golden paths, documentation surfaces, and self-service capabilities that improve onboarding and day-to-day flow.
• Incorporate AI-native engineering patterns into the platform, enabling LLM-assisted development, agentic workflows, and next-generation productivity tooling with pragmatic governance.
• Integrate Ericsson application, cloud and infrastructure services into a Platform Engineering ecosystem.

Core Tasks

• Actively attend feedback from developers and observe the IDP through telemetry to identify DX improvement opportunities.
• Develop and operate automation, tooling, and backend services that enhance DX, platform reliability, observability, and security.
• Build automation workflows using GitLab CI/CD, including reusable templates and paved-road patterns.
• Build production-grade observability: dashboards, alerts, traces, health checks, SLIs/SLOs, and operational playbooks using Prometheus/Grafana (and/or OpenTelemetry patterns where applicable).
• Implement secure development workflows: dependency scanning, policy checks, artifact integrity, SBOM-style practices, SCA/SAST integrations, and guardrails embedded into pipelines.
• Work closely with PDUs and Security & Compliance actors to align the IDP with compliance, security, resilience, and productivity needs - balancing enablement with governance.
• Operate and evolve Kubernetes workloads and platform services: cluster configuration, networking, scaling, resilience testing, capacity planning, and cost-awareness.
• Extend and maintain the Backstage-based IDP Portal: build plugins, components, APIs, and developer-friendly UI features; improve discoverability and reduce "time-to-first success."
• Enable AI-native developer workflows: prompt engineering patterns, LLM evaluation/quality signals, safe-by-default usage, agentic processes, and automation powered by LLMs.
• Troubleshoot complex issues across CI/CD, cloud infrastructure, integrations, security tooling, and platform UX; contribute to incident response and post-incident learning.
• Contribute to IDP architecture and technical direction: reference architectures, golden paths standards, API contracts, documentation quality, and long-term maintainability.

Required Skills

Technical Skills in priority order:

• Strong Python and scripting skills (OOP, data structures, automation/tooling, API integrations, testability).
• Expert knowledge of Git and GitLab CI/CD, including runners, templates, security features, pipeline scaling, and the design of multi-step automation workflows using GitLab environments.
• Strong observability skills using Prometheus and Grafana (and an understanding of logs/metrics/traces and alert quality).
• Secure software engineering mindset: vulnerability management, dependency scanning, compliance automation, and guardrails that scale.
• Solid Kubernetes experience: deployments, networking, scaling, troubleshooting, and production operations.
• Proficiency with Docker and containerization workflows, including image hygiene and supply-chain considerations.
• Familiarity with Backstage (or React/JS frameworks) and modern developer portal concepts (self-service, catalog, templates, docs-as-code).
• Previous experience as software developer, with exposure to all stages of the SDLC
• Experience or strong interest in AI-native development models, including agentic programming, LLM-assisted workflows, and practical automation.
• Hands-on exposure to prompt engineering and LLM evaluation (quality signals, regression testing for prompts, workflow safety, cost/performance tradeoffs).
• Familiarity with enterprise tooling (JIRA, ARM...) is a plus.
• Familiarity with Ericsson tooling (Mimer, NOVA...) is a plus.

Soft Skills & Behaviors

• Deep empathy for developers and a passion for enabling a frictionless, intuitive Developer Experience.
• Customer-driven mindset: able to translate pain points into actionable platform improvements and iterate quickly.
• Strong collaboration across teams, programs and organizations; communicates clearly with both engineers and stakeholders.
• Security-first and observability-first mindset: you build systems that are measurable, supportable, and safe-by-default.
• Curious about the future of AI and motivated to explore innovative ways to improve software flow responsibly.
• Proactive and accountable, comfortable making engineering decisions in ambiguous environments and learning fast.
• Passionate about automation and simplification; you reduce toil and build paved roads, not bespoke one-offs.