Presential Limited is building the privacy layer for enterprise AI, allowing tier-1 banks to use sensitive data with external models safely. As Founding Engineer, you will own the core platform architecture, designing the AI systems that transform PII into semantic twins. Your work ensures AI pilots survive compliance and reach production.
Founding Engineer at Presential Limited
Presential Limited is looking for a Founding Engineer to build the definitive privacy layer for enterprise AI. Operating at a funded pre-seed stage with tier-1 UK banking clients already in the sandbox, Presential Limited solves the critical compliance bottlenecks that prevent major financial institutions from deploying AI. You will own the core technical architecture, building sophisticated agentic loops and RAG systems from the ground up. This role offers meaningful equity and a direct path to engineering leadership within a senior founding team. If you have 5+ years of experience and deep LLM expertise, join us to define a new category at the intersection of privacy and AI.
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Location
London, United Kingdom
Compensation
Not Disclosed + Equity
Company
Presential Limited
Role overview
What? Presential is building the privacy layer for AI.
Why? Every organisation with sensitive data is stuck between a technology that works and a rulebook that says no. That gap is our market and it widens with every model release.
How? Using our RSP technology, sensitive data goes in, fictional substitutes that carry the same meaning come out, the model runs on those, and we reverse the mapping so the answer arrives whole. The model never sees the real thing. Never.
Who? A small team that has already built successful companies and lived this problem first hand.
Where? London based and already working with enterprise scale customers.
What you will do
- Architect and experiment with the core platform to optimize latency, reliability, and system resilience for enterprise-grade throughput.
- Build advanced AI workflows, including agentic loops, RAG architectures, and dynamic prompt chaining to handle complex document processing.
- Configure and fine-tune models while switching fluidly between backend architecture and task-specific evaluation to ensure data privacy.
Who this is a fit for
- Has 5+ years of software engineering experience building scalable production systems using Python, TypeScript, Go, or Rust.
- Demonstrates deep expertise with the modern LLM stack, including tool-use execution, memory systems, and AI evaluation frameworks.
- Possesses a track record of delivering enterprise-ready features, ideally with experience in SOC2, data isolation, and VPC deployments.
Why this role is remarkable
- Build the foundational architecture from scratch for a pre-seed startup defining the intersection of privacy and enterprise AI.
- Directly solve the primary compliance bottleneck preventing major financial institutions from deploying state-of-the-art AI models into production.
- Gain significant ownership and a clear trajectory toward engineering leadership as a core member of a senior founding team.
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If your profile’s a match and Presential Limited wants to meet, Jill will make the intro. In the meantime, Jack will send you excellent alternatives.