Location: London · Reports to: Founder & CEO
About Lua
Lua is the Agent OS. We build digital employees — agents that do a real job end to end: they read a company's own systems, make the decision, take the action, and get a little better every time they run. Not chatbots that answer questions — digital workers that do the work, on the company's own data and workflows, and everything they build stays owned by the business. Teams write their logic on Lua (agents, skills, tools, jobs, webhooks, guardrails) and we run the hard parts underneath: infrastructure, multi-provider model orchestration, data, channels (WhatsApp, Slack, Email, Instagram, Messenger, a voice-capable website widget, HTTP API) and monitoring.
Our customers are the companies that run their markets — the operator of one of the world's most-visited heritage sites, a major travel-and-hospitality group, the largest supermarket chain in its country, a listed conglomerate spanning healthcare and consumer goods, large regional banks, social-commerce companies and a microinsurer covering over a million people — across Africa, the Middle East and South Asia. Together they employ 64,000+ people and turn over $5bn+ a year, and they all want the same thing: to be AI-native on the systems they already run, with nothing to rip out. Backed by Y Combinator, we've raised $5.8M — and this is a chance to build the playbook, not inherit one.
What you'll do
Every one of our customers buys the same way: they have a real operational problem, and they need to see a working agent on their own data before they commit. That's you. An account executive owns the relationship; you own the technical win from discovery to signature. You turn a vague AI mandate into a scoped architecture on their real stack — an ERP, a payments system, a claims platform — prove it with a live agent, and answer the ownership and data-isolation questions that decide regulated deals (the logic and IP stay theirs). Win it right and you're not closing one deal — you're setting the pattern a whole portfolio inherits.
Discover. Interview operators, map the current-state workflow, and find the high-value automation behind a vague ask. Quantify the pain in a metric the buyer already tracks.
Architect the solution. Turn discovery into a clear architecture: the data, triggers, tools, decisions and integrations behind the workflow. Which capabilities map to which skills and tools; which CRM, payment processor, inventory system or third-party API they hit; which channels the agent lives on; and, the part that wins deals, what's in scope and what's explicitly not. You work at the architect level, in Lua's terms, without disappearing into line-by-line code.
Present demos. Get a working agent in front of the customer, grounded in their real context. You can prototype this yourself with AI assistance or pair with an engineer; the point is a tailored, data-grounded proof, not a canned tour. Most of our shipped verticals (finance ops, KYC/AML onboarding, healthcare portal, e-commerce, logistics) lift almost directly as a starting point. Run tailored demos and technical reviews for both technical and business stakeholders, holding the boardroom and the integration detail in a single meeting.
Win. Own the technical win. Understand who makes the decision and what they need to see, agree clear success criteria for the POC up front, and tie them to a business outcome the buyer cares about, so your champion can make the case internally without you in the room.
Answer the hard questions. Lead technical reviews on security, data isolation, compliance and data handling. Draw the line honestly between what the platform guarantees (managed infra, per-user isolation, server-side secrets, model orchestration) and what the customer implements (their compliance logic). It's a shared-responsibility conversation, and getting it right is how you win regulated buyers.
Partner with sales. Work hand in hand with the account executive and wider sales team throughout the deal cycle. You're strong in front of clients and own the technical win.
Scope. Size each engagement accurately before signature: known integrations, known risks, realistic effort.
Hand off clean. Give Delivery a documented scope, the success criteria, the integration map and the known risks. No re-discovery.
Feed product. You see the same gaps and patterns across deals before anyone else. Route them back; you're a primary signal for what we build next.
What we're looking for
Must-haves
5+ years in a customer-facing technical role (solutions engineering, pre-sales engineering, forward-deployed engineering or similar).
You've run technical discovery: interviewed operators, mapped existing workflows, and identified high value automation opportunities.
You've translated business problems into technical architectures (data, triggers, tools, decisions, integrations) and chosen the right components. You've designed and built proof-of-concept and pilot solutions and presented them to customers.
You've led technical reviews and answered security, compliance and data-handling questions credibly, with an understanding of enterprise governance, data isolation and security requirements.
You've partnered with a sales team on technical evaluations and been responsible for the technical win.
A hands-on technical background: you can read and write code, are comfortable in a CLI, are fluent in at least one scripting language, and have working knowledge of APIs and integrating systems together.
Strong written and verbal communication: you present effectively to both engineers and senior business stakeholders, with strong attention to quality and detail, comfortable working independently and managing competing priorities.
Nice-to-haves
Experience with LLM / agent applications (tool-calling, RAG, evals, agent orchestration).
Experience selling or delivering into regulated or security-sensitive industries (fintech, healthcare, insurance).
Workflow-automation platform experience.
A cloud / enterprise-architecture credential (AWS Solutions Architect, GCP, Azure or similar).
