Engineering Manager (Cloud & SRE)

DeepstreamtechBerlin

Stellenbeschreibung:

Requirements

3+ years leading an engineering team (hiring, coaching, performance management, career development)
Strong technical background in cloud infrastructure - you can guide architectural decisions and hold a high quality bar
Experience with at least one major cloud provider (GCP preferred; AWS or Azure transferable)
Familiarity with Kubernetes in production, CI/CD pipelines, and Infrastructure as Code (Terraform or similar)
Active user of AI-assisted development tools (Claude, Copilot, Cursor, or similar)
Exposure to AI/ML supporting infrastructure such as agent observability, model serving, AI development lifecycle, or ML pipeline operations
Track record of driving team outcomes using metrics, OKRs, or KPIs
Effective communicator across engineering, product, and leadership audiences
Experience with Agile/Scrum
(Desirable) Experience with platform consolidation, multi-cloud environments, or infrastructure migrations
(Desirable) SRE practices: SLOs, incident management, on-call, observability
(Desirable) GCP Landing Zones, GitOps (ArgoCD/Kargo), or service mesh
(Desirable) Cloud cost optimization experience
(Desirable) Experience supporting AI/ML workloads at scale (GPU scheduling, model deployment infrastructure, vector databases)
(Desirable) Background managing platform/infrastructure teams specifically
Not sure if you meet all the requirements for this role? Please apply anyway. You might bring something special to the team that we hadn't considered previously

What the job involves

Lead and grow the team:
Hire, coach, and develop cloud/SRE engineers - run meaningful 1:1s, set development goals, and actively manage performance
Build a high-performance team culture rooted in psychological safety, ownership, and continuous improvement
Champion AI adoption within the team - encourage AI-assisted workflows and continuously raise the bar on how AI is used to improve productivity
Evaluate capacity, balance workloads, and advocate for the resources your team needs
Own delivery and reliability:
Own the team's outcomes against OKRs - prioritise effectively, track progress with metrics, and delegate without micromanaging
Ensure rigorous deployment pipelines, production readiness, and incident management practices
Drive SLO adherence and operational excellence across production infrastructure
Shape platform strategy:
Partner with Technical Leadership and Architecture to align infrastructure work with the technology strategy
Lead your team's contribution to platform consolidation and evolution across the Taxfix group
Support AI/ML platform needs - including agent observability, AI workload infrastructure, and AI development lifecycle tooling
Evaluate technical trade-offs - balancing reliability, cost, security, and delivery speed - and communicate them clearly to stakeholders
Partner across the org:
Bridge your team and its stakeholders: Product Engineering, AI Engineering, Security, Data, and Architecture
Align priorities with peer EMs across Platform Engineering
Proactively surface blockers, manage dependencies, and keep information flowing