Senior Software Engineering Manager, Core Cloud Compute- AI

Conteúdo da vaga extraído em seções para revisão mais rápida.

Developing technical excellence and leadership among the members of a high-performing engineering team.
Fostering effective use of AI-assisted software development across your team — from code agents and AI-augmented code review to automated operational tooling — and contribute to org-wide standards for how we integrate AI into the SDLC.
Scaling and extending Rescale's core job orchestration engine, leveraging VM and Kubernetes-based compute for large scale engineering simulations, across multiple public cloud providers.
Maintaining high operational expectations on core product — driving incident response, SLO discipline, and reduction of toil and incident load.
Driving alignment across EPD (Engineering, Product and Design) and with customer-facing teams (Support, Solutions, Sales) on product delivery and technical architecture.

Track record of leveling up engineers and building collaboration within the team.
Evidence of strong end-to-end ownership of their own and their team's decisions and product charter, including the operational posture of a 24/7 production system.
Ability to credibly engage in architecture discussions on scalable distributed systems — comfortable going head-to-head with senior and staff engineers on design trade-offs.
Excited by AI-assisted development and pushes the boundaries of what's possible — using AI agents, code generation, and automation as multipliers for engineering velocity and quality.
Clear written and interactive communication.
Deep collaboration with Product and ownership in product delivery.
Effectively balances the needs of their team (and themselves) with that of the business, including reliability investment vs. product delivery.

3+ years experience managing high-performing Software Engineering teams of 3–10 people, including senior and staff ICs.
Technically proficient as an IC, at least to Senior Engineer level, with demonstrated depth in scalable distributed systems.
Hands-on experience using AI tools in the SDLC as well as driving AI adoption on a team previously in a sustainable manner.
Production experience with at least one major cloud (AWS or Azure) at scale and familiarity with managed Kubernetes (EKS, AKS).
Led the delivery of, at least one multi-quarter architectural change with quantifiable impact in the past.
Experience managing a SaaS system powering a complex backend product, with meaningful on-call ownership, incident command, and SLO discipline.

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