Do you want to superpower engineering with AI? At Monolith AI, we help engineering teams turn complex test and simulation data into better decisions, faster. As we scale our customer delivery, we’re looking for a Lead Customer Success Engineer to act as a technical delivery lead on client engagements.

This role is for someone who enjoys owning complex, customer-facing delivery -designing end-to-end solutions, coordinating multiple workstreams, and translating technical execution into clear customer value.

What you’ll be doing

You will act as the primary owner of delivery for a set of strategic customers, combining technical depth with active project leadership.

You’ll be responsible for:

· Owning end-to-end customer delivery, acting as the single accountable lead within a client team

· Designing bespoke, multi-product solutions that deliver clear and measurable customer value

· Breaking down complex customer objectives into structured workstreams, milestones, and success metrics

· Actively managing delivery: scope, timelines, dependencies, risks, and trade-offs

· Coordinating execution across internal teams (product, data science, software, forward deploy)

· Translating technical progress into clear, customer-facing updates and reports

· Acting as a trusted technical advisor to senior customer stakeholders

· Getting hands-on where needed to unblock delivery or validate technical approaches

A bit about you

· You have significant experience leading complex, technical, client-facing projects

· You are comfortable owning ambiguity and making delivery and prioritisation decisions

· You have a strong engineering or scientific background and can go deep when required

· You enjoy designing solutions, not just executing predefined tasks

· You communicate clearly and confidently with both technical and non-technical stakeholders

· You work well autonomously but thrive in cross-functional environments

· You are happy to travel for up to ~30% of your work

It’s a bonus if you have

· Experience applying AI/ML or data science in an engineering context

· A Physics, Maths, or Engineering degree