Ref Id: HREZ-12456
Published Date: Jun 3, 2026
Job location: Brazil, Colombia, Costa Rica
General information
Description
HATCHWORKS AI Forward Deployed Engineer Client-Embedded · AI Delivery · HatchWorks AI · Remote / Costa Rica, Brazil, Colombia |
Remote / LatAm | Full-Time | English Required | Client-Embedded |
WHY THIS ROLE EXISTS
An MIT study found that 95% of enterprise generative-AI pilots never deliver measurable business impact. The models work. The demos are impressive. Then the project stalls the moment it meets a real company's data, systems, and people.
Forward Deployed Engineers exist to close that gap. It is the fastest-growing role in AI right now: job postings grew more than 800% in the first nine months of 2025, and every serious AI company from Palantir to Anthropic to OpenAI is building teams around it.
At HatchWorks AI, the FDE is the person who turns "AI could help here" into a system the client's team actually uses. You embed with an enterprise client, find where AI creates real value, and build and ship the whole thing end-to-end through our GenDD methodology. Not a prototype that dies in a sandbox. Working software, running in production, owned through to the outcome.
This is the role we are hiring fastest for right now.
ABOUT HATCHWORKS AI
AI is all we do. We help enterprises turn AI into ROI by automating high-impact work and building AI-native products grounded in their data. Our proprietary Generative-Driven Development (GenDD) methodology is a repeatable path from idea to production that blends AI, agents, and engineering to ship faster with less risk.
We are an Anthropic, Google Cloud, and Databricks partner, named the #1 AI Services Company by Clutch and an Inc. AI Power Partner. We measure success in business impact, not pilots or prototypes. And we have won four Best Places to Work awards, because we invest in the people here.
THE ROLE
Most embedded engineering roles come with a product manager, a clear backlog, and a defined stack. This one doesn't.
You'll embed directly with an enterprise client's business teams, learn how the work actually runs, determine what's worth building, and ship it to production — largely standalone, with light oversight and weekly direction check-ins rather than a dedicated product owner. The engineer operates in ambiguous, undefined problem spaces and makes their own build decisions. This is not an advisory seat. You own the solution through to production.
The first engagement is the client's START program: an initiative to onboard new franchise owners and move them to operational profitability. The problem space is deliberately open — there is no predetermined answer on whether the right solution is an agent, an application, or a workflow tool. Your job is to find out. Then build it.
The platform runs on Azure, .NET, and React. The client's platform team provisions infrastructure. You own the build and the deploy.
This is a role for someone who thrives in white space.
WHAT YOU'LL ACTUALLY DO
- Embed with the business owner and their team, map the current process, and determine what is actually worth building — there is no pre-written spec to execute.
- Scope, design, build, and ship the solution to production end-to-end. The platform team provisions infrastructure; you own the build and the deploy.
- Make day-to-day product and build decisions independently, with a weekly check-in for direction rather than a dedicated product owner holding your backlog.
- Apply AI where it adds genuine value — agents, LLMs, RAG — while recognizing that a deterministic build is an equally valid and fully successful outcome.
- Run delivery in real sprints and keep the client's team able to operate the solution after handoff. The engagement is not complete at a prototype.
- Own the solution through adoption, not just deployment. Success is measured by whether stakeholders actively use what you built and whether it moves the needle on the outcome it targets.
DEFINITION OF SUCCESS
The engagement is complete when a working solution is running in production, owned end-to-end within the client's platform infrastructure, that measurably advances the START program. Not a prototype. Not a proof of concept. A deterministic build that ships and gets adopted counts fully.
Definition of Success |
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THE TECHNICAL BAR
We set a firm minimum on technical competence, but technical skill is not the differentiator for this role. What matters is that you can own a full build in an undefined problem space and get it to production. The path you took to get there is open.
Must-Haves | |
Production Engineering | Several years building and shipping production software as a full-stack engineer, with genuine command of fundamentals rather than familiarity with patterns alone |
Full-Stack Range | Owns backend, frontend, and data layer end-to-end. Client stack is Azure, .NET, and React; strong Node or Python full-stack is acceptable provided the engineer can integrate and owns the whole build. Single-stack specialists are not a fit — technology needs vary widely |
Ownership in Ambiguity | Demonstrated ability to operate in undefined problem spaces, scope independently, and drive to a result without waiting to be told how |
Communication | Clear, concise communication with senior business stakeholders and technical peers — in the moment, without translation overhead. You extract requirements by sitting with people, not by waiting for documents |
AI Delivery | Hands-on experience building and deploying AI, LLM, or agent solutions into production — not merely experimenting with them |
NICE TO HAVE
- Experience with agent frameworks, RAG architectures, MCP, or evaluation tooling
- A consulting, product, or operations background alongside the engineering
- Enterprise delivery experience in regulated or complex environments (healthcare, finance, or similar)
- Familiarity with Azure AI and Azure OpenAI; ability to read and understand an existing .NET codebase
THE HUMAN BAR
Technical competence is the floor. Entrepreneurial self-direction is the differentiator.
Two archetypes are viable for this role, and we match the candidate to the engagement rather than seek one fixed profile:
- Product-minded engineer who leans technical — suited for open-ended, undefined problem spaces like the START engagement, where scoping is as much the job as building.
- Technical engineer who works comfortably with the business — suited for more defined builds where the problem is clearer and execution depth matters more.
The four traits that matter, in order of importance:
- Entrepreneurial self-starter — the most critical and hardest to find. Thrives in white space, presents options, and tries things without waiting for direction. This is the trait that determines whether the engagement succeeds.
- Communication — sits alongside the above. Extracts needs from stakeholders, validates ideas directly, and keeps the right people informed without overhead.
- Technical competence — a firm minimum bar rather than the differentiator. You need to be able to build the thing; the bar is real.
- Formalized product methodology — the least essential, given the iterative, hands-on nature of the work. User research and formal product process can be sacrificed.
WHAT MAKES THIS DIFFERENT
Most embedded roles are scoped before you arrive. This one isn't. The problem space is open, the solution is undefined, and the build decisions are yours. You are not a contractor executing a spec — you are the engineer and the product decision-maker, working directly with the business.
The client's infrastructure is already provisioned. You don't spend weeks spinning up environments. You spend week one mapping the workflows and the data, and week three shipping something the team can react to.
The measure of success is explicit and non-negotiable: production deployment, active adoption, and measurable progress on the outcome. The engagement is not complete at a prototype. That bar is higher than most roles — and it is also what makes the work matter.
YOU'LL WORK INSIDE A PROPRIETARY AI DELIVERY FRAMEWORK
Most teams using AI tools today are flying blind — they feel faster but can't prove it. We built GenDD (Generative Driven Development) to change that, and you'll be running it from day one on this engagement.
GenDD is a proprietary methodology and toolset built around one belief: great engineers need full context to move fast without breaking things. It gives you the scaffolding to run real sprints in undefined problem spaces, instrument every build decision, and turn your work into repeatable, client-ready evidence of impact.
Zero Ramp-Up | Proven Value | All-In Team |
Our tooling surfaces full project context — architecture, data flows, history — so you hit the ground running on every engagement. | GenDD instruments every agent interaction, commit, and deploy — turning your work into clear, client-ready evidence of real impact. | Everyone here uses agents seriously. You're not evangelizing — you're exploring. We learn fast, share everything, and enjoy the work. |
FDEs operating in open-ended engagements like START are exactly who GenDD was built for. You bring the judgment; we give you the framework to move fast and prove it.
COMPENSATION & SETUP
Contract Type | Full-Time, Nearshore |
Location | Remote — Latin America (Costa Rica, Brazil, Colombia preferred) |
Time Zone | Client timezone alignment required |
Language | English required — professional working level |
Start Date | Open — engagement starts as soon as the right engineer is placed |
HOW TO APPLY
Send us three things:
1. Why this type of engagement — A brief note (3–5 sentences) on why you're drawn to undefined problem spaces rather than scoped delivery. Be honest about what excites you — the ambiguity or the execution, or both.
2. Something you scoped and shipped — A project or feature you owned from an undefined starting point through to production. Tell us what the problem was when you arrived and what was running when you left.
3. Your resumé or LinkedIn profile.
We read every application. We respond to the ones that show us you've actually done this.
HatchWorks AI is an equal opportunity employer. We evaluate candidates on demonstrated capability, communication, and ownership — not credentials, geography, or background.
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