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Infinity Constellation

Junior AI Engineer (Clients) - Supernal

Posted An Hour Ago
Be an Early Applicant
Remote
Hiring Remotely in USA
15-20 Hourly
Junior
Remote
Hiring Remotely in USA
15-20 Hourly
Junior
As a Junior AI Engineer, you will design and build backend features, own projects end-to-end, write automated tests, debug production issues, and improve system reliability, communicating effectively across teams.
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Title: Junior AI Engineer (Client)

Location: Remote (Global)

Reports to: Director of Engineering

Company: Supernal

Type: EOR FTE or Contractor

Rate: $15 - $20 per hour

About Supernal

At Supernal, we help SMBs hire their first AI employee. Our AI teammates are built with intelligent, agentic workflows and deployed on our proprietary platform. We don't build tools — we deliver working, value-generating AI Employees.

Now, we're looking for a Software Engineer (Mid-level) to help build and ship the systems behind these AI teammates.

The Role

As a Software Engineer, you'll build and ship production software that powers customer-facing AI workflows and the internal platform that supports them.

You'll design and implement backend services and integrations, work across APIs and data flows, and contribute to reliability and scalability as we grow.

Beyond writing code, you will take ownership of scoped projects: clarify requirements, propose an approach, deliver iteratively, and ensure the result is solid in production.

This is a hands-on role. You're not just closing tickets — you're shipping meaningful features, debugging real production issues, and raising the quality bar through testing and good engineering practices.

Responsibilities

  • Design and build backend and platform features (APIs, services, integrations, and data flows)

  • Own scoped projects end-to-end: requirements clarification, implementation, testing, rollout, and follow-through

  • Write automated tests — unit tests for isolated logic and integration tests for system behavior

  • Apply solid engineering fundamentals: error handling, retries/backoff where appropriate, and clear interfaces between components

  • Debug production issues using logs/metrics/traces; drive issues to resolution and add safeguards to prevent recurrence

  • Improve reliability and maintainability through refactors, performance improvements, and better observability

  • Communicate progress, tradeoffs, and risks clearly to engineering and cross-functional partners

  • Contribute to team standards: code review, documentation, and best practices that keep builds predictable and supportable

You Might Be a Fit If You...

  • Have 2 to 4 years of experience as a software engineer shipping production systems

  • Have built and maintained backend services and APIs in a production codebase

  • Are comfortable with integrations: third-party APIs, webhooks, auth patterns (OAuth / API keys), and data modeling

  • Write automated tests as a matter of course and treat testing as part of shipping, not an afterthought

  • Apply strong fundamentals: clean architecture, separation of concerns, and pragmatic tradeoffs

  • Can take ownership of a scoped problem and drive it to completion with minimal hand-holding

  • Are a solid debugger who can reason through edge cases and production failures

  • Communicate clearly and fluently in English — both in writing and verbally — especially when articulating tradeoffs and implementation choices

  • Provide your own laptop with reliable internet and be willing to work primarily in Americas time zones

  • Thrive in fast-paced, ambiguous environments and take ownership without being asked

  • Bring a low-ego, high-integrity approach to collaboration

What Success Looks Like

  • Customer-facing workflows and internal platform systems ship on time and perform reliably in production

  • Scoped projects are delivered end-to-end with good engineering discipline: clear scope, solid implementation, tests, and safe rollouts

  • Production issues are diagnosed quickly, resolved thoroughly, and followed up with lasting fixes (tests, alerts, runbooks)

  • Code is well-tested, well-documented, and maintainable — not just functional

  • Technical decisions and tradeoffs are communicated proactively, with risks surfaced early

  • Team quality improves over time via thoughtful reviews, refactors, and shared standards

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