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Software Engineer / AI Engineer

JuiceLabs AI

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Interviews for software roles keep coming back to Python, Java, AWS, System design. Practise those questions before you sit with JuiceLabs AI.

Questions you are likely to be asked

  1. Why do you want to join JuiceLabs AI?
  2. What is your experience with AWS? Tell me one thing you learned the hard way.
  3. How did you know your model was actually good, and not just good on your test set?
  4. Tell me about a time the data was messy or wrong. What did you do?
  5. How would you explain your model's result to someone who is not technical?

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**About Juicelabs** *Where creative engineering meets applied AI.* We build vertical, AI-native tools that unlock fresh insights and creative superpowers for clients in advertising, ecommerce, and beyond. We're a nimble team of founders and builders obsessed with using AI to solve real problems in ways that didn't exist eighteen months ago. **The Opportunity** A year ago, we would have posted this as a backend role. That role doesn't really exist any more. Code has become nearly invisible. Agents write it, test it, and iterate on it faster than anyone could read it. What's left is the work above it: deciding what's worth building, designing systems that hold up at 10x, and building the setup that turns a clear spec into working software. That's the job. At your level, it isn't one system. It's several workstreams, running at once. You'll work directly with our Cofounder/CTO on products going from zero to one, with AI at the core of both what we build and how we build it. Real ownership, real scope, and an unusual amount of leverage: one engineer with good judgment and a well-tuned agent setup now ships what a small team used to. **What you'll do** * **Own multiple workstreams in parallel.** Two or three features of the same product moving at once, each with its own scope, edge cases, and failure modes. You decide where your attention goes this week, and nothing goes stale. * **Run a fleet, not a single agent.** Design the setup that makes high-throughput work possible: how work gets broken down, specced, and run across many agents at once, so output scales without things breaking. * **Design the system.** Service boundaries, data models, failure modes. Make the architectural calls before a line gets generated, and be able to explain the trade-off six months later. * **Write the spec.** PRDs and technical designs are the new source code. A vague spec produces confidently wrong software, fast. Scope, edge cases, non-goals, what "done" means. * **Own it end to end.** Ideation → design → build → deploy → monitor → iterate, including functional UX. Nobody hands you tickets. * **Set the workflow. Bring your harness**: CLAUDE.md, AGENTS.md, subagents, custom commands, eval loops — whatever makes agents reliable rather than merely impressive. We want to steal your good ideas. **What we're looking for** * **High agency.** You see the gap and close it. You don't wait for direction, and you don't need to be chased for follow-through. This is the single trait we screen hardest for. And you can do it across several workstreams at once, without dropping threads. * **Real system design depth.** You can reason about consistency, caching, queues, and scale — and about complexity, because you need to know when an elegant-looking solution is quietly quadratic. LeetCode ninja not required. Being able to explain why this won't blow up at 10x, very much required. * **Clear thinking, put to paper.** You get the thinking straight first, then write it down so nobody has to guess: PRDs, design docs, PR comments. Writing is most of how you'll direct both humans and models, and muddy thinking on paper becomes muddy software. * **You've shipped to production.** Deployed things, monitored them, been paged by them, fixed them. Docker, CI/CD, cloud infra. Our stack is mostly Python (FastAPI), Postgres, GCP/AWS — but we care more about how you think than which framework you've memorised. * **You orchestrate AI, not just use it.** Not "I've tried Copilot," and not just "I use Claude Code." You've run multiple agents in parallel and developed opinions: how to split work so they don't step on each other, where they excel, where they confidently lie, how you structure a repo so they don't wander, and how you verify what comes back at volume. * **Startup energy.** Multiple hats, fast cycles, and the judgment to balance "ship it now" against "will this survive contact with real users?" **Experience** 3–6 years of professional experience (full-time positions, excluding internships). **Location / How to apply** On-site at our office in HSR Layout, Bangalore.

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Listed on wellfound · posted 2026-10-22. ApplySarthi collects openings and links to application pages; the role is advertised by JuiceLabs AI, not by us.