AI Delivery Lead

Anthrobyte wins by putting AI
agents into the real operations of enterprise clients — and making them work,
in production, where it matters. We need a leader who does this exceptionally
themselves and builds a team that does it the same way. You'll own how we
deliver AI, from the client's messy reality to a system they trust — and turn
every engagement into repeatable capability inside our ATLAS platform.

This is a build-from-the-front
role. You lead from inside the problem, not from a whiteboard.

What
you'll own

— Embedded delivery. You
go where the work is — inside the client's environment, alongside their
operators — to understand their workflows, data, and constraints firsthand. You
don't design in the abstract; you build against reality.

— End-to-end ownership. From
business problem to architecture to a deployed, secured, monitored agent
running in production and driving outcomes. You own the whole arc, not a slice
of it.

— The product loop. You
turn what you learn in the field into reusable patterns, accelerators, and
standards inside ATLAS — so the next engagement is faster and we compound into
a product, not a services treadmill.

— Building the team. This
is the multiplier. You hire, mentor, and level up engineers to work the way you
do — codifying your instinct into a playbook others can run. Success is a team
who deliver like you, not you delivering everything.

— Client trust. You sit
across from client security, data, and business leaders and earn their
confidence — in architecture reviews, security reviews, and the room where
decisions get made.

Requirements

What
we're looking for

— Production track record. You've
personally taken AI, ML, or agent systems into enterprise production — not
demos, not pilots that died. You've worked with real client data and lived with
what you shipped.

— Proof you build people. You've
mentored engineers, set technical standards, and shaped how a team works.
Evidence you can reproduce your skill in others, not just exercise it yourself.

— Range. You're equally
comfortable writing code, whiteboarding architecture, and holding your own with
a client's CISO.

— Systems mindset. You
think in reliability and trust, not cleverness — enterprise AI is won on
auditability and things that keep working.

— Ownership drive. You're
energised by building something from early and shaping how it's done.

Bonus
points

— Domain experience in
supply chain, procurement, pricing, or other regulated / operational enterprise
environments.

— Exposure to enterprise
security, governance, and responsible-AI practices.

— A track record of growing
engineers into strong, independent operators.

What
this role is not

A back-office ML research lead.
A pure people-manager who's left the tools behind. An architect who designs
from a distance and never touches the client's reality. If you want to lead
from a whiteboard rather than from inside the problem, this isn't it.

How
we work

Small, high-trust, founder-close
team. Governance-first, because our work runs inside clients' live operations.
You'll have real authority over how we build and deliver — and the mandate to
shape the team around strong talent.

How
to apply

Tell us two stories. First: one
AI system you took into enterprise production — the messy problem, how you
built and secured it, and what broke along the way. Second: someone you made
better — an engineer you grew, and how. Those two stories tell us more than any
CV.