AI-Augmented Software Engineer

Azumo builds and operates production AI systems for companies ranging from seed-stage startups to Meta. We are hiring Software Engineers to deliver product software in our clients' stacks, with coding agents as part of how the work gets done rather than as a side experiment. The role is fully remote across Latin America, aligned to your client's working day.

We do not hire by language. Azumo has shipped production software since 2016, and what we test for is whether you can take a problem into a codebase you did not write and leave it better, at a pace a client can plan around. Which language you reach for first tells us where to place you, not whether we want you.

Azumo's engineering organization is built around four lanes. The Data Engineer lane owns pipelines, storage, and the retrieval layer. The Data Scientist lane owns the question and the method. The AI Engineer lane owns production behavior. This role is the Software Engineer lane, and it owns AI-augmented product delivery.

One question places the boundary: "do you build AI, or do you build with AI?" The AI Engineer answers for what the model does.You answer for what the software does.

- If you own how an AI system behaves in production — AI Engineer

- If you build the pipelines and retrieval layer models depend on — Data Engineer

- If you decide what to measure and which method answers it — Data Scientist

- If you've done all of the above and answered to the client directly — Forward Deployed Engineer

- Product software, end to end. APIs, services, data models and interfaces in the client's stack, from a problem statement to something running in front of their users.

- Delivery you can hand over. Specification and tests before implementation, agent context committed to the repository and kept current, and gates that run on every change. The test is whether another engineer reaches your result, not whether you got there quickly.

- Review of what actually lands. You read every diff that ships under your name, whoever or whatever wrote it. Volume is not the deliverable.

- Quality you own. Automated tests, CI/CD, and the failure handling that keeps a third-party outage from becoming your client's outage.

- Work inside the client's environment. Their repositories, their standups, sometimes their customer calls. Azumo is SOC 2 certified, client code stays in client repositories, and some engagements carry additional requirements such as HIPAA.

Our engineers build with AI every day. Claude Code, Codex, and similar tools are part of the standard toolchain here, not an experiment. We run an automated audit across the whole codebase on day one and every day after, grading security, cost, and architecture findings by severity with the exact file and line, so a small team can move quickly without quality drifting. We stay vendor-neutral across OpenAI, Anthropic, and open-weight models, and we run Valkyrie, our own production layer, when a single interface to any model is the right call.

Azumo is a San Francisco based software development company that has been building intelligent applications since 2016. We provide nearshore AI engineering teams to organizations that need production AI faster than they can hire for it: as an embedded engineering team, as AI staff augmentation alongside an existing team, or as a full project build. Our engineers work from Latin America, aligned to United States time zones, and have delivered for Twitter, Meta, Discovery Channel, Omnicom, UnitedHealth, and CENTEGIX.

We hire for seniority and test for it before anyone joins a client team. We support engineers in going deep on the modern AI stack, and we give time back to open-source work, community teaching, and philanthropy.

Apply at https://azumo.com/join-our-team or write to us at people@azumo.com.

- 5+ years building and shipping production software in at least one modern language and stack, plus the engineering fundamentals that go with it: testing, code review, CI/CD, Git, containers, and API design.

- Depth in one stack and the willingness to work in another. We hire for engineering judgment rather than a keyword match, and you will meet codebases you did not choose.

- Practical work with relational and non-relational databases, including schema design and the query performance problems that follow it.

- Integration with third-party APIs and services (REST, OAuth, JSON), and the retries, timeouts and degradation that keep someone else's outage from becoming your client's.

- Automated testing as a habit rather than a phase: unit, integration, and tests written alongside the code that they cover.

- Cloud deployment experience with Docker, CI/CD pipelines, and infrastructure as code (GitHub Actions, Terraform, or Bicep).

- Daily delivery work with AI coding agents, beyond autocomplete: agents running inside the repository, repo-level context you maintain, and review of everything that lands.

- Clear written and spoken English, C1 or above, and the confidence to explain a technical trade-off directly to a client.

- Bachelor's degree in Computer Science, a related field, or equivalent professional experience.

- Frontend depth alongside backend: React, Vue, or an equivalent framework, and the UI and accessibility work that comes with it.

- Mobile delivery, native or cross-platform.

- Agent tooling you built rather than configured: MCP servers, hooks, sandboxes, or CI gates of your own.

- Performance and cost work on systems already in production.

- Delivery under a compliance regime such as SOC 2 or HIPAA.

- Contributions to open-source projects, published technical writing, or active participation in an engineering community.