Forward Deployed Engineer - AI Solutions Architect

Requirements

• Experience with AI tools and LLMs
• Ability to work in client-facing roles
• Comfort with ambiguity and fast-paced environments
• Low ego and ability to take feedback
• Ability to work directly with executives and founders

Job Description
Build AI systems for clients, embedding at different companies every 4–6 weeks, translating client problems into AI solutions, and working directly with the founder.

BEFORE YOU READ THIS
Sequoia published a piece called Services: The New Software. It argues that AI is collapsing the gap between services and software companies — that services firms can now build compounding IP, run at software-like margins, and scale without the traditional headcount pyramid. If that thesis excites you, keep reading. If it doesn't, this role probably isn't for you.

ABOUT THE COMPANY
We're an AI transformation firm. We help companies turn AI ambition into working business systems — combining strategic advisory with hands-on and agentic execution, from board-level governance to AI systems deployed in real workflows.

A small team of practitioners augmented by AI agents. Two to three people delivering what a 14-person consulting team used to deliver. Every engagement produces working software and leaves behind reusable IP that makes the next engagement faster.

ABOUT THE ROLE
You'll build AI systems inside other people's companies. Every 4–6 weeks, you embed at a different client — a PE portfolio company, a manufacturing firm, an e-commerce platform — and work alongside our founder to deliver a working AI system. You'll see inside 10 different industries in your first year, solve problems for executives, and build your network while building software.

You translate client problems into working AI systems. The founder handles strategic direction and C-suite relationships. Your job: figure out what to build, coordinate the build, and make sure it lands.

HOW AN ENGAGEMENT WORKS

Weeks 1–2 — Discovery (you lead the technical side)

• Map the client's processes, systems, and data environment.
• Run 5–10 structured stakeholder interviews to understand how the company actually operates.
• Assess data quality and integration possibilities.
• Score AI opportunities by business impact, feasibility, and speed to value.
• Identify where AI agents can replace manual work — which processes become agentic, which stay human.
• Work with the founder to select the right build target.

Weeks 3–5 — Build (with the engineering team)

• Translate discovery into architecture — agent workflows, integrations, data flows.
• Work alongside our Founding AI Engineer during the build phase.
• Manage client-side coordination — access, testing, feedback loops.
• Run parallel user training so the system doesn't die on delivery.
• Demo working progress to stakeholders weekly.

Week 6 — Prove

• Measure results against the original business case.
• Support the founder's leadership presentation with concrete numbers.
• Map the next 3–5 AI opportunities for the client's roadmap.
• Extract patterns and templates for our internal IP library.

Between sprints

• Refine discovery frameworks based on what worked.
• Help build AI agents for our own delivery — discovery agents, process mapping agents, analysis automation.
• Contribute to the IP library — interview templates, process mapping tools, scoring frameworks.
• Prep for the next engagement.

WHAT WE LOOK FOR

You can code and you can talk
Technical enough to assess a system architecture. Articulate enough to run a stakeholder interview with a COO. You don't need to be the strongest engineer in the room — but you need to understand what's being built and why.

Curious about how businesses work
You ask "why does this process exist?" before asking "how do we automate it?" You care about second-order effects. You don't just build — you think about what you're building into.

AI-native
You use AI tools daily — Claude, GPT, Cursor, Claude Code, whatever your stack. You understand what LLMs can and can't do from direct experience. This is a dealbreaker.
Required.

Client-facing
You can walk into a boardroom, run an interview, and present a finding without rehearsing. Client environments are political. Stakeholders have agendas. You handle this without creating friction. Dealbreaker. Required.

Velocity is everything
We deliver in 4–6 weeks what others take quarters to scope. That speed is the product. You ship weekly, decide daily, and never wait for permission within your scope. If you need long runways or extensive planning before you act, this pace will break you. Dealbreaker. Required.

Low ego
You'll work alongside a founder, an engineer, client executives, and AI agents. The best idea wins regardless of source. If you can't take direct feedback, adjust on the fly, and put the outcome above your own contribution, this won't work. We reference check. High ego gets spotted fast.

Comfortable with ambiguity
Every engagement starts with incomplete information. You figure out what questions to ask rather than waiting for a spec.

WHAT YOU'LL GET

• 20,000 – 40,000 PLN per month net on a B2B contract.
• Remote with occasional vistis in Warsaw.

Exposure you can't buy
Direct access to C-suite executives across industries, the founder's 500+ decision-maker network, and board-level conversations at PE firms and enterprises.

Variety
Different client, different industry, different problem every 4–6 weeks.

A compound skill set
Process mapping, stakeholder management, AI system design, business case construction. This role builds consulting, engineering, and sales instincts at the same time.

AI-native environment
AI agents do 40–50% of delivery work. Maxing out tokens for 24/7 agentic work is the way. You'll have the tools and the budget to push what's possible.

Founder mentorship
You work directly with the founder on every engagement. You'll see how deals get structured, how client relationships evolve, and how strategy becomes execution.