Enterprise Head of AI Engineering (Founding)Sales Development Representative (SDR)

About Pyxos Pyxos is the agentic operating platform for data privacy compliance. Where incumbents sell workflow tracking tools and dashboards, we ship agents that execute compliance work — RoPA, DSARs, DPIAs, vendor risk, breach response, cross-border transfers — under human oversight. Our benchmark is an 80%+ reduction in manual privacy work. We have one paying enterprise customer and six design-partner pilots launching with enterprise customers in KSA and the UAE. Pyxos is led by a six-time Silicon Valley venture-backed technology CEO with four significant exits, now based in London, alongside operating leaders with deep enterprise software and AI experience. The position You will own the technical direction of our agent surface, the proprietary build environment behind it (our Agentic Studio), and the evaluation, observability, and safety layers that make the system trustworthy enough for regulated enterprise deployment. We build with AI: agentic development tooling is core to how Pyxos ships, and we expect the person in this position to extend that approach, keeping the team deliberately lean. You will be part of the founding team, the most senior technical person, reporting to the CEO as part of the founding leadership team, and architectural authority over the AI layer. You will work closely with our VP, Product & Operations (based in the US), who owns product and operational engineering. You inherit one strong engineer and a working production system, and your job is to ship — writing code, designing agents, owning the evaluation work, making the architectural calls. Hiring happens in parallel, deliberately and slowly, with a strong bias toward keeping the team small and leveraging AI tooling to extend its output. You will step into it, take ownership of the AI engineering path to that milestone, and make the technical calls needed to land it on time. You will be writing code, not just directing it. Shipped agentic systems in production. For us, this is the clearest indicator of someone who has shipped LLM systems in production. • Deep, current LLM engineering practice. Prompt injection mitigation, dual-LLM or plan-then-execute patterns, output validation, tool-use restrictions, policy enforcement. • Production engineering rigor. Strong Python; cloud fluency (AWS, GCP, or Azure); Engineering leadership at startup pace. Nice to have: regulated-industry experience (privacy, finance, healthcare, legal tech); BYOC or on-prem deployment experience; familiarity with the EU AI Act or GDPR Article 22; Arabic language capability. we are not training foundation models or publishing papers as a primary output. We are building production systems where the cost of a wrong answer is a regulatory fine, which calls for a different set of disciplines and a different kind of engineer. Logistics Remote, UK or EU. Occasional travel to customer sites and team gatherings. We hire on the basis of capability, judgment, and fit with what we are building.