Forward Deployed Engineer

The company builds and operates production AI systems for companies ranging from seed-stage startups to Meta, delivered through small teams working inside each client's environment. We are hiring Forward Deployed Engineers: the engineer embedded in a client's team who owns the system and whether it works, from the first conversation through to whatever breaks after release. The role is fully remote across Latin America, aligned to your client's working day.

The company has shipped production AI & Software since 2016, and on these engagements there is no analyst writing the requirement, no QA phase waiting to catch what you missed, and no architect approving your design. Those calls are yours to make and yours to answer for. If you have only ever worked with those roles in place , this is not the seat to start in. We have other openings that probably fit you better.

Where this role sits

You are the engineer the client works with . On most engagements you are the only one, sitting inside their team, with their repository, their constraints and their deadlines.

Your lane says what you build: software, data pipelines, models, or AI systems in production. This role says how you are accountable for it. We hire Forward Deployed Engineers out of all four lanes .

One question places the boundary: when the client is unhappy, "was it the wrong feature, or a feature that does not work?" As the technical lead on the account, anything that does not work as expected is yours.

Not quite your profile? Check our other openings

• 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 ship product software with agents in your toolchain — AI-Augmented Software Engineer

What you will build

• The whole thing. Discovery, design, build, verification, release, and the incident afterwards. Not a slice of it handed to you already specified.
• The work nobody assigns. The access nobody granted, the dataset nobody can explain, the integration everyone assumed was someone else's. Unclaimed work is yours by default.
• Saying no to the client directly yourself. Not escalating it, not absorbing it quietly. A reason, an alternative, and the standing to be believed.
• Verification. You demonstrate that the acceptance criteria are met. There is no testing phase behind you.
• Reproducible delivery, run with agents. Specification and tests first, agent context committed to the repository, gates on every change. One engineer carrying a whole delivery only works when the process is reproducible.
• Work inside the client's environment. Their repositories, their standups, sometimes their customer calls. The company is SOC 2 certified, client code stays in client repositories, and some engagements carry additional requirements such as HIPAA.

How we work

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.

About the company

The company 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 [link for members] or write to us at [link for members]

Requirements

Basic qualifications

• 7+ years building and shipping production software, with depth in at least one of our four lanes: product software, data pipelines and retrieval, modeling and applied AI, or AI systems in production.
• Experience as the only engineer on an engagement, or the first one on a new client.
• A track record of delivering inside someone else's environment — their repository, their conventions, their constraints — without supervision and without a specification written for you.
• Direct client-facing experience. You have run the conversation, not attended it: scoped work with the person paying for it, pushed back on a request, and been believed.
• End-to-end ownership of at least one system in production, including the incidents. You were the one who got called.
• 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.
• Cloud deployment experience on Azure or AWS, with Docker, CI/CD pipelines, and infrastructure as code (GitHub Actions, Terraform, or Bicep).
• English at C1/C2. You will be in the room with the client, and the engagement depends on what you can explain in that room.
• Bachelor's degree in Computer Science, a related field, or equivalent professional experience.

Preferred qualifications

• Working depth in a second lane.
• Delivery under a compliance regime such as SOC 2 or HIPAA.
• Consulting, agency, or client-services background, with the commercial instinct that comes from it.
• Contributions to open-source projects, published technical writing, or active participation in an engineering community.

Benefits

• Paid time off (PTO)

• U.S. Holidays

• AI Training

• Mentored career development

• Profit sharing

• $US remuneration