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

FullStack; Huancayo; Remote; PEN 90,000 - 150,000; Full time

Benefits offered by this job

100% remote work

Competitive pay

Continuing education opportunities

Grow with leading startups and Fortune

Opportunity to work with top clients

Job summary

FullStack is seeking a Forward Deployed Engineer who embeds with enterprise teams to identify AI opportunities, architect solutions, and ship production-grade systems. You will balance consulting, engineering, and operational duties, working with regulated industries and Fortune 500 clients to ensure reliable AI outcomes.

Ideal candidates have strong software fundamentals, experience delivering AI-enabled products, and comfort with fast-paced discovery conversations with executives.

Qualifications

• 5+ years of professional software development experience with production stacks.
• 4+ years shipping agentic AI solutions or RAG architectures in production.
• Advanced English required.
• Four-year college degree required.
• Experience with frontier AI developer tools like Cursor, Claude Code, Gemini CLI, or OpenAI Codex.

Responsibilities

• Discover workflows with business/data/engineering stakeholders.
• Map current state, decisions, data inputs, and exceptions; convert to actionable specs.
• Design end-to-end agentic systems emphasizing context and retrieval architecture.
• Build working systems: agents, retrieval services, and evaluation tooling.
• Own CI/CD for AI-enabled applications, including prompt/context versioning and eval suites.
• Operate post-launch: eval harnesses, observability, cost, and latency management.

Skills

Senior software

AI/ML knowledge

Client-facing

Discovery facilitation

Agile / Scrum

Education

Bachelor's degree

Tools

Cursor

Claude Code

Gemini CLI

OpenAI Codex

Job description

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.

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, and exceptions, then turn it into specifications that both people and AI systems can execute against reliably.
• Architect & design. Design agentic systems end to end with emphasis on context and retrieval architecture — data sourcing, chunking, embeddings, hybrid search, reranking, permissions-aware retrieval, knowledge graphs where warranted — plus orchestration, MCP/tool integration, guardrails, and human-in-the-loop checkpoints.
• Build. Ship working systems — agents, retrieval services, evaluation tooling, and the data flows that feed them. Prototypes that prove value in weeks, not slideware.
• Engineer the delivery system. Own CI/CD for what you build, extended to AI: prompt and context versioning, eval suites that run in the pipeline and gate releases.
• Operate (Day 2). Own what happens after launch — eval harnesses, groundedness and retrieval metrics, observability and tracing, cost and latency management, drift, and the handoff that lets the client’s team run it without you.
• Consult. Present to and defend decisions in front of CTOs, VPs of Engineering, CDOs, and business leadership. Quantify impact in their terms. Support pre-sales scoping and proposal work when the deal calls for it.

What We’re Looking For

• 5+ years of professional software development experience with at least one mainstream production stack (Python, TypeScript/Node.js, Java, C#/.NET, or Go).
• 1 - 4 years of professional experience shipping agentic AI solutions, LLM workflows, and RAG architectures in production environments.
• Advanced English is required.
• Successful completion of a four-year college degree is required.
• Hands-on experience with frontier AI developer tools including Cursor, Claude Code, Gemini CLI, or OpenAI Codex.
• Track record of leading client-facing discovery calls, asking “why” before “how” to decompose unstructured business problems.
• Solid understanding of architecture paradigms such as RESTful APIs, microservices, and event-driven systems.
• Well-versed in agentic orchestration tools and frameworks like LangGraph, LangChain, N8N, or direct Model Context Protocol (MCP) and LLM APIs.
• Skilled at exercising end-to-end delivery ownership and managing project scope without requiring product manager supervision.
• Ability to work through new and difficult issues and contribute to libraries as needed.
• Ability to create and maintain continuous integration and delivery of applications.
• Forensic attention to detail.
• A positive mindset and a can-do attitude.
• Experience working on Agile / Scrum teams.
• Meaningful experience working on large, complex systems.
• Ability to take extreme ownership over your work. Every day is a challenge to ensure you are performing to the expectations you and your team have agreed upon.
• Ability to identify with the goals of FullStack’s clients, and dedicate yourself to delivering on the commitments you and your team make to them.

Strong Plus

• Production AI operations (Day 2): eval harnesses, observability and tracing, cost and token economics, drift, debugging non-deterministic systems.
• Prompt- and eval-level regression testing running in CI and gating releases.
• Delivery in regulated environments (financial services, healthcare, insurance, manufacturing).
• Pre-sales support: discovery calls, SOW and estimate shaping, technical proposal defense.
• Process mining, operations analysis, or transformation consulting background.
• Client enablement and training — building the client team’s capability, not just the system.
• Prior consulting or agency environment; comfort with ambiguity and multiple accounts.

Work Authorization Requirements

• Applicants must be currently authorized to work in the country of this job posting on a full-time basis.
• FullStack will not sponsor applicants for work visas now or in the future.

What We Offer

• Competitive pay.
• 100% remote work.
• The ability to work with leading startups and Fortune 500 companies.
• Continuing education opportunities.
• Opportunity to grow and expand your career.

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