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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 make it hold up in the real environment. 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 debugging why an agent’s tool-calling loop degraded after a context change. 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 application engineering: you make agents real inside the client’s actual systems, workflows, and delivery pipelines. 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 FDEs are trusted to shape the solution, not only deliver it. Every engagement calls for architect-level judgment: 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 Clients rarely arrive with a fully formed problem, and the FDE’s first contribution is helping them see it clearly. You lead discovery with genuine curiosity, moving the conversation from stated requirements to underlying needs, and you build credibility through the depth of your understanding rather than the breadth of your pitch. 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 and engineering stakeholders. Separate genuine AI problems from workflow problems wearing an AI costume. Come back with a scoped, defensible point of view.Structure the process and the spec. For any business or engineering process being automated, map the current state, decision points, 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 — orchestration, context and retrieval architecture, tool and MCP integration, guardrails, human-in-the-loop checkpoints, and the boundaries between deterministic and non-deterministic components.Build. Ship working systems — agents, multi-step automations, internal tooling, integration layers. You are hands-on. Prototypes that prove value in weeks, not slideware.Engineer the delivery system. Own CI/CD for what you build: build, test, release, environments.Consult. Present to and defend decisions in front of CTOs, VPs of Engineering, 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 Engineering foundation 8–10+ years of professional software development; back-end-heavy, full-stack capable.Primary production experience in one of our core ecosystems: TypeScript / Node + React, Python, .NET / C#, or Java.Strong in APIs, service design, event-driven / distributed systems, and data modeling.Track record as a Solution Architect, Principal Engineer, or Tech Lead — can assess a current-state environment and define a credible roadmap.Has designed and owned CI/CD — build, test, release, environments — not just used someone else’s pipeline. Applied AI Has built and shipped LLM and agent systems beyond a demo.Deep fluency with agentic tooling: Claude Code, agent frameworks, MCP, tool/function calling, multi-agent orchestration.Context and spec engineering: structures codebases, specifications, process definitions, and context to produce reliable, context-efficient AI output.Integration literacy: understands integration methods and options — APIs, webhooks, event streams, iPaaS (n8n, MuleSoft, etc.), MCP — and the constraints and strategies behind connecting AI to systems of record. Doesn’t need to own every integration, but can design around them and guide the team that does. Consulting & business Demonstrates the discovery behaviors above: business and personal drivers, constraints, stakeholder alignment, strategic questioning.Runs client conversations without an account manager in the room: workshops, proposal walkthroughs, hard questions, pushback.Translates technical decisions into business outcomes — cycle time, cost per transaction, throughput, risk reduction, ROI.Exceptional written and verbal communication; credible in front of senior stakeholders. 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 United States on a full-time basis.FullStack will not sponsor applicants for work visas now or in the future. What We Offer Competitive Salary.Paid Time Off (vacation, sick leave, parental leave, holidays).100% remote work.The ability to work with leading startups and Fortune 500 companies.Health, dental, and vision insurance.401(k) w/ 4% match.Ample opportunity for career advancement.Continuing education opportunities. FullStack is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. Learn more about our Applicants Privacy Notice.