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Open nowPosted 24 days ago

Senior/ Staff Software Engineer, Platforms

sagora-ai3 open roles

Where
Boston, MA
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Your applicationOpen nowSenior/ Staff Software Engineer, Platformssagora-ai · Boston, MA
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This job: posted 24 days ago

The posting

The Mission

Founded by MIT CSAIL professors and their former PhD students, and built on a decade of their research, Sagora is the autonomous engineering platform for AI systems. We compress weeks of expert engineering into hours, continuously improving the performance, cost and quality of customers’ AI models, pipelines and inference.

Our agents do what expert engineers do: diagnose problems, form hypotheses, run experiments and ship validated, production-ready code. You’ll build alongside the founders.

We’re backed by $13.5M in seed funding and engineering leaders including Jeff Dean and Ion Stoica, and we’re already in production at multiple S&P 500 companies. We’re headquartered in Boston.

What You’ll do

  • Own critical platform systems end to end: you design them, you build them, you run them in production. That includes APIs, orchestration and scheduling of agent workloads, deployment pipelines, and observability.
  • Establish the technical architecture and the defaults that every project here starts from, and build the shared infrastructure that makes them real.
  • Keep the platform reliable, fast, and cost-efficient as usage grows.
  • Own the developer experience: the tooling and workflows that keep a small team shipping fast.
  • Collaborate with the founders and research team to turn research insights into reliable, production-grade systems.
  • Mentor engineers and raise the bar through design and code reviews. Build prototypes quickly, validate them, and iterate based on user and customer feedback.

What We’re Looking For

  • This role calls for experience: engineers who have designed, built, and operated production systems and developed the judgment that only comes from doing so for years.
  • We are hiring at both Senior (5+ years) and Staff (8+ years) levels; for Staff, we expect a track record of setting technical direction beyond your own projects.

Strong Signals Include (few people will have all of these; if several describe you, we want to hear from you)

  • You have designed and operated large-scale distributed systems in production, and made architecture decisions that are still holding up years later.
  • You have built platforms and infrastructure that other engineers build on: internal platforms, developer tools, control planes, or cloud services.
  • You have designed APIs that other teams depend on, and kept them stable while the systems behind them changed.
  • You have led a major migration (a datastore change, a service split, a replatform) and landed it without disrupting the business.
  • You have made a system simpler: fewer services, less code, fewer dependencies, easier to operate.
  • You have built on Kubernetes APIs: controllers, operators, or schedulers (not just deployments).
  • You have shipped production systems in one or more of Go, TypeScript, or Python. You have run services on a major cloud (e.g. AWS) with infrastructure-as-code (Terraform or similar).
  • You write design docs that make trade-offs clear, and use them to help a team commit to a decision.
  • You have mentored engineers who now own critical systems themselves. You use AI tools in your daily engineering work, and have formed real opinions about where they help and where they fall short.

Why Join Sagora?

  • Strong pedigree: Work alongside a team of renowned experts in AI-driven systems.
  • Massive impact: Our technology delivers significant improvements in long-running engineering research and design tasks, spanning performance engineering, model pipeline development and efficiency.
  • Robust financials: Our $13.5M seed round closed in September 2025. We’re backed by top-tier VC firms (Pillar, E14 and Neotribe) and luminaries including Jeff Dean, Ion Stoica, Aparna Chennapragada, Nick McKeown and Srinivas Narayanan. We’re in production at multiple S&P 500 companies and running paid proofs of value with more.
  • Solving hard problems: We’re solving the fundamental bottlenecks of the AI revolution: performance, cost and quality.
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