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Salary
$107k – $236k per year (Estimated)
Location
Remote (India, New Zealand)
Seniority
Senior · 5+ years exp
Overview
Company
Impact
Profile match
Theta is an AI software company that develops autonomous AI agents for complex enterprise workflows, enabling them to learn, adapt, retain memory, and autonomously execute end-to-end tasks across industries.

We are looking for a Founding Engineer with 5-9 years of experience to join Theta as one of the earliest engineering hires, bringing deep backend infrastructure and AI/ML expertise to a team solving some of the hardest data and systems problems in frontier AI. You'll be a mature, highly autonomous IC who elevates the entire engineering org with hard-won experience from deeply technical environments.

Responsibilities:

  • Work directly with founders across engineering, product, and operations to define priorities and execution strategy.
  • Own and scale core backend infrastructure powering Theta's data platform, managing cloud compute, optimising workers, and solving hard systems problems daily.
  • Tackle research-grade engineering challenges at the intersection of AI, agents, and data pipelines, implementing new model harnesses and staying ahead of the frontier.
  • Build and improve internal tooling and workflows that maintain high-fidelity, high-quality data output at scale.
  • Work directly alongside founders to define technical priorities and drive execution with minimal oversight.
  • Bring engineering maturity and hard-earned instincts to a small, fast-moving team raising the bar for how problems are scoped and solved.
  • Understand domain workflows and translate them into agent training environment tasks.

Requirements:

  • 5-9 years of experience at a deeply technical company (e. g., AI/ML-focused team at a top-tier startup or FAANG) where you've been solving infrastructure problems most engineers haven't encountered.
  • Strong backend infrastructure background: cloud compute management, distributed systems, worker optimisation, and scaling platforms under real load.
  • Hands-on experience with AI/ML systems, whether on an agent, post-training, or ML infra team, or building ML-adjacent infrastructure (not recommendation systems, ad ranking, or traditional ML pipelines).
  • Genuine, innate interest in the AI tooling landscape; you follow new model releases, harnesses, and frameworks closely and move fast to apply them.
  • High autonomy and scrappiness: you thrive in ambiguous, fast-moving environments and don't need hand-holding to ship.
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