Aleph - Staff+ Software Engineer, AI
Requirements
• You've shipped production LLM systems - evals, context management, multi-model or multi-provider routing - and can talk concretely about what broke and what you changed • You build proof of concepts, decide quickly, and ship v0s. Evals drive your quality bar • Strong judgment about abstractions: opinionated about design, pragmatic about shipping incrementally • Experience with LLM APIs and agent frameworks, and shipped user-facing products • You want to ship production systems, not do research • What we expect from all Staff+ Engineers • Adoption: teams you don't manage have picked up systems you built - because they were that good • Strong fundamentals: you can trace requests from UI to data store and make good technical decisions at every layer • High agency: background as a founder, engineering lead, or startup builder. You have a builder's mindset and find creative ways to ship • Pragmatism: you choose the fewest and simplest tools that will actually work • Craft: you care deeply about code quality and write code that's correct and easy to understand • Communication: clear, direct, and persuasive across technical and non-technical audiences • Experience: you've built complex B2B products, ideally from scratch • While this is a remote-first opportunity, we're focusing on candidates within the Americas to better align with our working hours as a team.
Responsibilities
• Own the AI foundation product teams build on: model selection and routing, the model proxy layer, context management, and tool design • Own eval infrastructure. Work with customers and finance domain experts to define what excellent output looks like, then encode it in evals every team can run - in FP&A, a wrong answer ends up in someone's board deck • Ship agentic features end to end, from v0 through the optimization loop: prompt and context engineering, caching, parallel tool calls, subagent patterns • Build observability into agent behavior so we can profile it, find bottlenecks, and decide what to fix with data • Track what's changing in agentic systems and bring the practices that prove out into how we build
Benefits
• US$225K – $350K • Offers Equity • Canada$185K – $265K • Offers Equity • LATAM$130K – $210K • Offers Equity • These ranges are in USD and span 3 tiered locations (US, Canada, LATAM). Within each location, ranges are also tiered by city. • In addition to the salary range listed, total compensation includes generous equity and benefits: • Fully remote in the US, CAN, and LATAM • Regular, in-person Retreats • Provided MacBook Pro or Lenovo • Health insurance (US + CAN employees) • Guideline 401(k) (US employees) • Upload your resume here to autofill key application fields. • Drop your resume here! • Parsing your resume. Autofilling key fields... • or drag and drop here • Have you led a company or team through going AI-native, in the product or in how you build? Tell us what you'd want to walk us through in an interview, and any AI features you've shipped to real users. 1-2 sentences each is plenty. • Tell us about something you built that other teams started using on their own. Why do you think they did? • Not Applicable (I do not reside in the United States) • Prefer not to answer
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