Solutions Engineer

Technical Solutions Engineer

This role is open to candidates based in LATAM, Africa, and Eastern Europe. Please note that as this role supports U.S.-based clients, candidates must be available to work during U.S. business hours aligned with the client's time zone.

Every pod engagement we sell is sold against a document: the 90-day technical roadmap — validated opportunities inside the client's business, sized, sequenced, and mapped to the three-person team that will build them. That document has to survive three audiences with conflicting incentives: a client executive who must want to buy it, an internal margin-and-feasibility review that rejects anything low-margin or unbuildable, and a delivery team that will live inside it for ninety days. Today one of our founders writes those roadmaps. You take that over.

You are the technical half of the sales motion. During the paid Leadership Intensive, you are the facilitator's technical counterpart: you go inside the client's systems and data while they run the room, and you make five executives' live first builds actually work. Then you go away and produce the roadmap that converts a paid diagnostic engagement into a monthly embedded pod. You are pre-sales in the sense that you work before the pod contract — but everything you produce is a delivery commitment someone else must keep, and you are measured on whether they can.

What you will own:

1. Technical discovery inside client environments

• Map an unfamiliar mid-market stack fast: CRM, ERP, finance tools, home-grown spreadsheets, the undocumented automation graveyard — in days, with limited access, without breaking anything or spooking IT.
• Run the deep-dive protocol during the Intensive's first session: while the facilitator drives the executives, you drive the systems — screen-share walkthroughs, data-structure probing, integration surface mapping. You are listening for what is automatable, what data actually exists (versus what they claim exists), and where the political landmines are.
• Own the data-collection instruments: the interview guide, the screen-share protocol, the process inventory. A dozen interviews with the people who do the work happen inside every Intensive; you design what gets asked and you synthesize what comes back.
• Operate safely in regulated or sensitive contexts: know when to demand a de-identified export or a synthetic dataset instead of production access, and never let enthusiasm outrun the client's data rules.

2. The live build sessions — making executives ship

• Pre-build the scaffolding: before the hands-on session, you prepare each executive's use case so that a non-technical leader can get a clickable first version working in under an hour — data samples loaded, tools configured, the failure modes pre-empted.
• Rescue in real time: something always breaks with five simultaneous first-time builders. You debug live, quietly, without ever making the executive feel stupid — the room's belief is the product.
• Calibrate honestly in the demos: when an executive's build is a toy, you frame precisely what the gap to real is — because that gap is what the roadmap sells, and overselling it is a delivery debt with an engineer's name on it.

3. The 90-day technical roadmap — your flagship artifact

• Author it end to end: from the Intensive's findings, produce the roadmap — the chosen outcomes (drawing on our catalog of proven, deliverable outcome patterns), honest effort sizing, sequencing across the ninety days, data prerequisites, and the team composition that delivers it.
• Design to the delivery model: every roadmap must respect our standard structure — roughly half the team's hours go to the foundation layer we build for every client, half to this client's specific outcomes. A roadmap that needs 80% custom work is a rebuild, not a plan.
• Consult the delivery engineers on buildability before anything is presented: they will live inside your plan; their veto on feasibility is real.
• Pass the internal review: every roadmap goes through a feasibility-and-margin gate. Your scoping honesty is the whole game — a roadmap that closes the deal and blows the margin is a failure with a delay on it.
• Arm the presentation: you do not present the roadmap to the client (the facilitator and delivery engineer do), so it must sell without you in the room — written clearly enough that a US executive reads it and sees their business, not our template.

4. Prototypes, the library, and the diagnosis system

• Build fast proofs-of-concept on client data when a working demo will close a gap that a slide cannot — typically hours of work, not days, using AI tooling aggressively.
• Maintain the opportunity library: every engagement teaches us new reusable patterns (symptom → opportunity → typical build → typical effort). You keep that library current so diagnoses and roadmaps get faster and more consistent every month.
• Feed the diagnosis system: the AI system that drafts our free diagnoses runs on schemas and knowledge you help maintain. When it gets a client's stack wrong, you are one of the people who fixes why.
• Support engineering hiring: observe and co-score live technical assessments; your read on "can this person scope?" shapes who joins the delivery bench.

What a typical week looks like

Two Intensive sessions supported live (a deep dive on one account, a build session on another), a half-day of preparation per session, one roadmap in active authorship and one in internal review, a prototype sprint of a few hours where a demo is worth more than a document, the weekly feasibility review, and an hour folding what you learned into the opportunity library. Roughly half your calendar is client-facing or preparing to be; the other half is authorship and system-building. Deadlines cluster: a roadmap is due roughly ten days after every Intensive ends, and Intensives overlap.

What you must bring:

• Client-facing engineering: 4+ years as a solutions engineer, sales engineer, technical consultant, or full-stack engineer in roles where you regularly sat with non-technical clients — discovery, demos, workshops — and where deals or projects turned on your credibility. Pure back-office engineering, however strong, does not prepare you for a room of executives watching you type.
• Hands-on AI build depth: you have shipped real things with LLM APIs, agent frameworks, retrieval pipelines, and workflow automation — and you can show them. Public GitHub repos or live products are strongly preferred and will be reviewed commit by commit. You know when a given approach is wrong, when an agent is over-engineering, and when the answer is a spreadsheet formula and an honest conversation.
• Stack archaeology: demonstrated ability to walk into an unfamiliar business systems landscape and map it in days — you can read a CRM schema, reverse-engineer a spreadsheet-driven process, and interrogate an API you have never seen. Mid-market messiness (a CRM, an accounting tool, and forty Google Sheets) should feel like home terrain, not a horror story.
• Estimation honesty: a track record of scoping work that came in roughly as promised, and at least one story of a scope you refused or cut down — with what it cost you socially and why you did it anyway. We will ask for exactly this story.
• Writing that sells without you: your roadmaps are read by executives when you are not there. You write clearly, concretely, and in the client's vocabulary — we will read something you wrote for a non-technical audience.
• English: full professional fluency, spoken and written. You run screen-shares and interviews with US teams; an accent is fine, unclear is not.

Strong pluses

• Prior pre-sales at a services firm, dev shop, or systems integrator where you scoped fixed-price or outcome-based work — you have felt the pain of your own bad estimate being delivered.
• Data engineering fluency: pipelines, warehouses, dashboards — the executive command-center is one of our most-requested outcomes.
• Experience with the executive-facing side of security and compliance: answering "where does our data go?" precisely, working under data processing agreements, handling regulated-data engagements with synthetic data.
• You have taught or mentored: internal enablement, bootcamps, or conference workshops — the Intensive is half classroom.
• Spanish or Portuguese for internal collaboration.

This is not for you if

• You