Forward Deployed AI Engineer (Python) - Remote -Latin America

FullStack; Comisión de Fomento de Perú; Presencial; ARS 182.485.000 - 273.727.000; Jornada completa

Descripción de la vacante

FullStack is seeking a Forward Deployed Engineer to join our AI-native engineering partnership. You embed with enterprise teams, translate business problems into AI solutions, architect systems, build them, and ensure production readiness.

You operate as consultant, operator, and engineer, comfortable testing business cases with executives and delivering scoped work within days. You'll focus on data, retrieval, and model behavior to build trustworthy AI for regulated industries.

Descripción del empleo

About FullStack

FullStack is your AI-native engineering partner, built to turn AI capability into certainty. Most companies can demo AI; few can get it to production and prove what it produced. We close that gap with three capabilities, AI built into your products from the start, elite vetted talent who apply it, and transparent execution that shows value every step of the way. With now over 600 customers in North America, FullStack is one integrated partner for all your AI engineering needs. With FullStack, you move forward with confidence.

• Offering life-changing career opportunities to talented software professionals across the Americas.
• Building highly-skilled software development teams for hundreds of the world's greatest companies.
• Having delivered hundreds of successful custom software solutions, which have positively impacted the lives and careers of millions of users.
• Our 4.1-star rating on GlassDoor.
• Our client Net Promoter Score of 68, twice the industry average.

We’re Most Proud Of

• Offering life-changing career opportunities to talented software professionals across the Americas.
• Building highly-skilled software development teams for hundreds of the world's greatest companies.
• Having delivered hundreds of successful custom software solutions, which have positively impacted the lives and careers of millions of users.
• Our 4.1-star rating on GlassDoor.
• Our client Net Promoter Score of 68, twice the industry average.

The Position

Forward Deployed Engineers sit inside the client's problem, not next to it. You embed with an enterprise team, find the work that actually warrants AI, architect the system, build it, and stay long enough to make it survive contact with production.

This is a three-way role: consultant, operator, engineer. You should be as comfortable pressure-testing a business case with a COO or VP of Engineering as you are diagnosing why retrieval quality collapsed after a data refresh. The people who succeed here can hold a discovery conversation on Monday and ship what they scoped on Thursday.

On this track, your edge is data, retrieval, and model behavior: you make agents trustworthy by getting the data, context, and evaluation right.

We work with regulated industries and Fortune 500 clients who have AI mandates, real constraints, and low tolerance for demos that don't hold up.

How We Approach The Work

• Reframes the request. Treats "we need an agent for X" as a hypothesis, not a spec.
• Decomposes the problem. Outcome → process → decisions → data → systems → actors → constraints - before choosing technology.
• Chooses the intervention. Remove, simplify, traditional software, automation, LLM, RAG, agent, or multi-agent - and defends why.
• Owns the architecture decision. Documents trade-offs (ADRs), sets success metrics, pushes back on scope that won't deliver value.

Consultative Discovery

• Uncovers business drivers. What outcome matters, what it's worth, why now, and what happens if nothing changes.
• Uncovers personal drivers. What each stakeholder is measured on, what they're worried about, and what a win looks like for them individually.
• Surfaces constraints early. Security, compliance, data access, budget, skills, politics, timelines - the things that kill projects in month two.
• Aligns stakeholders. Spots conflicting goals between business, engineering, and risk, and brings them to a shared definition of success.
• Asks strategic questions. Follows the answer with "why," "how do you know," and "what happens today when…" - without interrogating. Clients leave the conversation understanding their own problem better.
• Earns authority through depth. Credibility comes from the quality of the questions and the insight in the playback, not from pitching technology.

What You'll Do

• Discover. Run workshops and process discovery with business, data, and engineering stakeholders. Assess data readiness honestly. Separate genuine AI problems from workflow problems wearing an AI costume.
• Structure the process and the spec. For any business process being automated, map the current state, decision points, data inputs,