The posting
What We Do
Companies know AI is reshaping their industries but don't know what to do about it. We help them figure it out. Our work spans strategy and implementation: sometimes we're building decks that explain what's possible, sometimes we're deploying the systems we proposed. Often both in the same engagement.
Recent Work
Financial Statement Review. $XXXB AUM PE firm. Before sending investor statements out the door, someone has to check them. We built a vision model pipeline that reads the PDFs, cross-references every figure against source data, validates internal consistency, and flags anomalies. Replaced side-by-side document review with structured static analysis. LPA Document Extraction. At the same firm, limited partner agreements are dense legal docs with investor-specific terms buried throughout. We built a document processing system that extracts those terms into structured data their CRM can use. Work that used to require a human reading hundreds of pages now runs automatically. Portfolio AI Assessment. $XB AUM PE firm with a dozen portfolio companies. They wanted to understand where each company stands on AI and share what's working across the portfolio. We built the survey tool, scoring system, and recommendation engine to make that happen.
The Role
You'll operate like a founder on each project, owning strategy and execution, business context and technical implementation. One week you're presenting an AI roadmap to a leadership team. The next you're shipping the system you proposed. You need to do both well.
Our project-based structure means the stack changes frequently. You'll use whatever fits the problem, which often includes newer tools (Rust, Effect-TS, etc.) that rarely make it into enterprise environments.
This is a strong fit if you want to start a company someday. You'll build the muscles (scoping problems, selling solutions, shipping under constraints) without the capital risk.
What We're Looking For
Strong CS fundamentals and evidence of a high ceiling. We care less about what you already know and more about how fast you can learn when dropped into unfamiliar territory. The AI landscape moves too quickly for static knowledge to matter much.
We're looking for generalists: people energized by variety who enjoy learning new domains and switching contexts.
Requirements: CS degree or equivalent experience Solid fundamentals in data structures, systems design, and debugging Clear communication: you'll present to clients, write proposals, and translate technical tradeoffs for non-technical audiences Curiosity, flexibility, low ego
If you have experience in financial services, banking, or consulting, you'll ramp faster. But we'd rather have a great engineer learning a new domain than the reverse.
The Hard Parts
You'll work across multiple clients, industries, and tech stacks simultaneously. There's no product team handing you specs. Clients often don't know what they need, and part of your job is helping them discover it.
You'll thrive here if you're comfortable with ambiguity and enjoy shaping undefined problems into concrete solutions.
Details
We're based in Fulton Market, Chicago. We work in-person four days per week because the work moves faster when we're together. Client travel is limited, typically just a few days per quarter at most. Many of our clients are within a short walk of our office. We're open to new graduates and experienced engineers. What matters is your ability to learn and ship, not your years in industry. We offer both contract and full-time arrangements depending on what fits best for you and the role.
