Nebuly
Solutions Engineer - London or Remote

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Location: London or Remote
Type: Full-time
Level: Senior
Reporting to: Solutions Lead
About Nebuly
Nebuly is a fast-growing, VC-backed startup building the platform that proves the ROI of enterprise AI.
Every enterprise function — sales, customer support, HR, finance — is deploying AI agents at scale, and budgets are following fast. But most companies can't answer a basic question: is this spend actually working? Every enterprise deploying AI agents is asking the same question: is this actually delivering value? Today, almost none of them can answer it. The signal that could answer it is right there — millions of conversations happening every day between employees, customers, and these agents — but it's unstructured, high-volume, and invisible without the right infrastructure. So the ROI question stays unanswered, not because the answer doesn't exist, but because no one can see it. Nebuly makes that signal visible. It sits on top of any enterprise AI deployment, turns those conversations into a clear answer — is this working, and where — and connects the dots back to ROI. Think of it as the accountability layer for enterprise AI: connect once, see the impact, prove the value — with no data ever leaving your environment.
Every new data category has created a new software category. CRM turned customer interactions into pipeline accountability. Product analytics turned user behavior into growth accountability. Nebuly is building that same layer for AI — turning millions of invisible conversations into a clear answer on value.
Our customers include Oura, CNH Industrial, Vodafone, and Moncler. Demand is accelerating fast, and we're building the team to match.
Why this role matters
Winning enterprise deals is hard. Turning it into a long-term, expanding contract is harder, and that's where this role lives.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
You own the technical side of the customer journey, from first demo to expansion. You convince technically skeptical enterprise teams that Nebuly works in their environment, then make sure it does. Above all, you translate technical data into a meaningful value proposition for C-level audiences.
This is not a support role. You are a technical closer and a value driver, directly accountable for pilots conversion and revenue expansion.
Why it's fun
You work hand in hand with large enterprises across UK on their AI projects.
You show customers the ROI they get from AI, and help them improve it with Nebuly insights.
You shape the product: we're customer-obsessed, and what you see in the field drives what we build.
What you'll do
Pre-sales
- Partner with Sales Directors to win technically complex enterprise deals.
- Own pilots end to end, from technical setup to demonstrating value, and build the technical business case that turns them into signed contracts.
- Run demos for prospects, from technical teams to C-level.
- Lead technical discovery: the customer's AI stack, data infrastructure, security requirements and deployment constraints.
- Design the integration and deployment architecture for customers and prospects (cloud or on-premise).
Post-sales
- Monitor adoption, identify risks early, and work proactively with the customer to drive usage and value realization.
- Identify and develop expansion opportunities in collaboration with the Sales team.
- Work closely with Sales to meet customer expectations and grow accounts.
- Work closely with Product Management and Engineering to evolve the product based on customer needs.


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What we're looking for
- 5+ years of experience in a Solution Architect, Sales Engineer, Solutions Engineer, or Technical Account Manager role in a B2B SaaS environment.
- Deep familiarity with enterprise observability, monitoring, or analytics infrastructure - background at or with companies like Datadog, Dynatrace, Splunk, New Relic, or similar is a strong signal.
- Excellent communicator, at ease with prospects, customers and large audiences: you can pitch to a C-level in the morning and dig into infrastructure with a DevOps team in the afternoon.
- Strong commercial instinct: you understand how technical success drives revenue, and you act on it.
- You like owning decisions, finding creative solutions and tackling hard technical challenges.
- Solid knowledge of LLMs, Kubernetes and cloud deployments.
- Comfortable discussing deployment architectures with senior technical stakeholders.
- Willing to travel about 20% of the time.
Nice to have
- Additional languages, always welcome.
- Startup or early-stage experience.
- Experience with self-hosted or on-premise enterprise deployments.
- Experience in a startup or early-stage environment where you had to build process from scratch.
What we offer
- A seat at the table with Fortune 500-scale customers on their most strategic AI projects.
- A small, senior team with high ownership and autonomy, working directly with the founders.
Hiring process
- Application review.
- Screening Interview.
- Logical Test.
- Hiring Manager Interview.
- Sales presentation.
- Final Call.
If you've done this before and want to do it again, at the right moment and in the right market, apply now.
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