
Founding AI Engineer
Description
The Role
We’re hiring a Founding AI Engineer to build systems that enable AI to operate safely, reliably, and repeatedly within Grand.
This is a high-impact individual contributor role focused on turning intelligence into production-grade capability. You’ll work AI-first by default, but with an engineer’s instinct for control, failure modes, and long-term system integrity.
This is neither a product feature role nor a research role. You won’t own UX or model theory. You will own how AI runs in the system: orchestration, guardrails, observability, auditability, and lifecycle management.
You’ll sit close to the founders, product, data science, and regulatory teams, shaping how AI decisions are triggered, constrained, inspected, and acted upon in a regulated environment. This is a seat at the founders’ table, helping build the company's nervous system.
What You’ll Do
Design and build the runtime and orchestration layer for AI systems across the platform
Turn probabilistic AI outputs into controlled, repeatable system behaviour
Define how AI decisions are triggered, gated, validated, and executed
Build guardrails, fallbacks, and confidence thresholds into AI flows
Design human-in-the-loop and escalation paths where required
Own prompt lifecycle management, evaluation, and versioning
Manage context assembly, scoping, and data boundaries for AI tasks
Build systems for logging, tracing, replay, and auditability
Control latency, cost, reliability, and degradation in production
Partner closely with AI data scientists to productionise models and signals
Collaborate with product engineers to integrate AI safely into workflows
Ensure AI systems are defensible, inspectable, and regulator-ready
Must Have
Strong backend engineering fundamentals
Proven experience shipping AI or LLM-based systems into production
Experience designing distributed systems with state, retries, and failure handling
Comfort working with probabilistic systems in high-consequence environments
Experience building guardrails, validation layers, or control flows around AI
Strong understanding of observability, logging, and system diagnostics
Experience managing model or prompt lifecycles in real systems
Ability to reason clearly about failure modes and degradation
Clear communicator who can explain complex system behaviour plainly
High technical judgment and strong ownership instincts
Nice to Have
Experience operating AI systems in regulated or high-stakes environments
Familiarity with agentic systems, task orchestration, or workflow engines
Experience with hybrid systems (rules + AI + humans)
Exposure to payments, fintech, or risk-sensitive domains
Background in early-stage or zero-to-one engineering teams
Experience designing systems that must be audited or replayed
Salary and Benefits
Excellent Salary: Competitive and reflective of the responsibilities of a founding role
Equity Options: Meaningful ownership in a long-term company
Hybrid Work: At least 3 days in our London or Dublin office
Extended Remote Work on Request: Outcomes matter more than optics
Builders, Not Tourists: Work with people who care deeply about getting this right
Who You Are
You’re a systems engineer first, who happens to work with AI. You’re less interested in demos and more interested in what happens when things go wrong.
You think in flows, constraints, and failure paths. You’re comfortable saying “this shouldn’t be automated yet” and designing for gradual trust.
You’ve seen what breaks when AI leaves the sandbox, and you build accordingly. You care about traceability, responsibility, and long-term credibility.
You thrive in ambiguity, enjoy hard systems problems, and take pride in building infrastructure that other engineers trust.
You’re based in Dublin or in close commuting distance (or ready to be), and ready to help build something genuinely new.
If this sounds like you, let’s talk.