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Software Engineer – AI-Native Automation

Job in 1001, Lausanne, Canton de Vaud, Switzerland
Listing for: Nexthink
Full Time position
Listed on 2026-06-01
Job specializations:
  • Software Development
    Cloud Engineer - Software, Software Engineer, AI Engineer, Full Stack Developer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 CHF Yearly CHF 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Position: Staff Software Engineer – AI-Native Automation

Imagine building the automation platform that powers the future of IT — not just for human operators, but for AI agents themselves. At Nexthink, we're evolving Flow
, our enterprise automation product, into something genuinely new: an AI-native platform where intelligent agents dynamically create and orchestrate the executions for enterprise scale and reliability.

This is a ground-floor opportunity to shape a product that doesn’t fully exist yet. You’ll be joining a small, high-impact team at the very beginning of this journey — working closely with leadership to explore, build, and define what next-generation IT automation looks like. If you thrive in ambiguity, love owning things end-to-end, and want your work to matter at scale, this role was built for you.

We're hiring Staff Software Engineer to join this initiative.

Responsibilities
  • Reimagining automation for the AI era — evolving Flow from a human-operated platform into one that AI agents can leverage to dynamically generate and execute workflows in secure, reliable, sandboxed environments.

  • Building at scale — designing and shipping large-scale, distributed, high-throughput, real-time systems that serve enterprise customers with hundreds of thousands of endpoints.

  • Shaping the product — working closely with Product Management and UX to define not just how to build things, but what is worth building and why. Your product instincts matter here as much as your technical skills.

  • Integrating Gen AI into real product capabilities — using generative AI as a core building block, not a bolt-on, and measuring and iterating on its effectiveness.

  • Driving technical direction — influencing architectural decisions, raising engineering standards, and mentoring teammates as a senior voice on the team.

  • Navigating early-stage exploration — this is a greenfield initiative. Priorities will evolve, approaches will be debated, and the best ideas will win. You’ll be expected to bring yours.

  • Partnering across teams — working with Product, Infrastructure, Security, Cost Governance, and AI/ML teams to align engineering strategy with product and business objectives.

  • Championing reliability and engineering excellence — driving observability, performance, resilience, and scalability across the stack.

  • Acting as a mentor and multiplier — raising the technical bar, supporting other engineers, and helping the team grow through strong technical leadership and collaboration.

Qualifications
  • Strong product engineering background — you’ve built products used at scale, you understand the why behind design decisions, and you care deeply about the value your work delivers to customers.

  • Experience with large-scale distributed systems — real-time requirements, high throughput, fault tolerance. You’ve been there and done it.

  • 10+ years of backend engineering experience
    , with 3+ years in Staff or Principal-level roles. Proven success designing and scaling backend systems for tens of millions of users or high-throughput real-time systems.

  • Expert in Java (17+), Python, or Node.js
    , with strong background in distributed systems, concurrency, and high availability.

  • Hands‑on expertise in cloud‑native architectures — AWS or equivalent, Kubernetes/ECS, containerized deployments, and large-scale database systems.

  • Deep understanding of API design, streaming data, and event‑driven systems
    .

  • Exceptional communication skills — able to influence cross‑functional teams and leadership with technical direction.

  • Mentorship and team elevation — a strong track record of mentoring engineers, raising the technical bar, and helping teams grow through technical guidance and collaboration.

  • Engineering excellence — CI/CD pipelines, observability, and a genuine commitment to quality are part of how you work, not afterthoughts.

  • Gen AI in production — you’ve used generative AI to build real product features, and you can speak to how you evaluated, measured, and iterated on those systems.

Nice‑to‑Haves
  • Advanced AI/ML experience — model fine‑tuning, training.

  • B2B enterprise product experience.

The Mindset We’re Looking For

More than any single technology, we’re looking for someone who:

  • Embraces ambiguity and can figure things out without…

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