AI Engineer (Forward Deployed)

Hiring for Smart Bricks — via Flexiple, the recruiting partner on this role.
About CompanySmart Bricks is the applied AI lab for real assets. It builds frontier AI systems and autonomous agents for the global real estate and AI infrastructure industries, so institutions can do in minutes what used to take months of manual work. Smart Bricks is backed by a16z Speedrun, Techstars, 500 Global, HBS Angels and others, supported by Balderton Capital, and was selected for the Palantir Startup Fellowship (Cohort 003). It works with institutional investors, fund managers and family offices across the UK, Middle East and US.
Job Roles & ResponsibilitiesBuild agentic systems: multi-step agents, tool use and workflows for sourcing, underwriting, due diligence, IC memos and portfolio monitoringOwn the AI stack: RAG and document pipelines, model routing across frontier and open models, prompt and context engineering, structured outputs into Excel and IC formatsBuild evals and observability for accuracy, cost, latency and reliability so every number traces back to sourceBuild reusable connectors, data pipelines and components that make each new deployment fasterEmbed with clients (real estate PE funds, institutional investors, family offices) to learn their data, workflows and decisionsPartner with GTM on discovery and scoping calls, turn messy client problems into a technical plan, and help close and expand accountsPrototype within days, iterate on client feedback and take solutions to production; own the technical relationship through rolloutTurn one-off client builds into platform features
Ideal Candidate Profile3+ years shipping production software, ideally in Python and/or TypeScriptDeep hands-on experience building with LLMs in production: agents, RAG, tool use, evals and context engineering (LangGraph, LlamaIndex, MCP or similar)Strong grasp of the AI model landscape and accuracy/cost/speed trade-offs; solid ML fundamentals, including knowing when not to use an LLMA builder's track record: founding engineer, early startup hire, ex-founder/CTO, or a top engineering team where you owned outcomes end to endComfortable in front of clients and able to explain technical trade-offs to a fund partnerCloud fundamentals (AWS, GCP or Azure), data pipelines, and awareness of enterprise security (data isolation, access controls)Comfortable working across UK and GCC hours; available to join immediatelyStrong plus: finance, real estate, private markets or consulting exposure; forward-deployed or solutions engineering experience; document-heavy AI (PDFs, spreadsheets, data rooms); quantitative degree
Originally posted on: 13 Oct 2026

Skills
Python, AWS, Azure, GCP, Excel, Sourcing, Due Diligence

Work arrangement
Yes