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David Joseph & Company

Customer Engineer, Agent Builder

London
£110k – £150k/yr
Posted 10 days ago
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London, UK

On-site

Full-time

Compensation: £110,000–£150,000 + competitive equity


About The Company

Our client is a leading conversational-AI platform that lets brands deliver concierge customer experiences — deploying AI agents across voice, chat, email, SMS, and every other channel to replace support tickets and hold music with faster resolutions. Marquee enterprises across travel, fintech, and consumer sectors run its agents. It's a later-stage, well-funded company and an in-office team built around velocity and hands-on execution.

Founded: 2023

201–500 people (Series D+)

Industry: Conversational AI


The Role

A post-sales, deployed-engineering seat that owns end-to-end execution of AI agent builds for strategic enterprise customers — a highly technical delivery role split roughly 50/50 (up to 60/40) between hands-on build and customer-facing engagement, depending on where each customer sits in its lifecycle. It sits inside a newly formed Agent Builder org working in tight feedback loops with agent PMs, customer success, engineering, and go-to-market.

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.

P

Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your 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.

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It 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.

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Strong

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.

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Strong

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.

Tech stack: Python (core); LLM / AI-agent tooling (prompting, evaluation, guardrails, workflow design); enterprise integrations (CRMs, ticketing systems, data pipelines, APIs).


Requirements

  • 3–5 years of technical, customer-facing experience (post-sales)
  • Strong Python proficiency (hard requirement)
  • A CS or adjacent quantitative degree (preferred)
  • LLM / AI-agent build experience (a plus)

Nice to Haves

  • A software or forward-deployed engineer pivoting intentionally into customer-facing, post-sales delivery
  • Strong, demonstrable Python with end-to-end integration work, comfortable coding without AI assistants
  • A track record of delivering production-grade customer solutions requiring structured execution, testing, and iteration
  • A clear communicator who can be walked into a room with senior executives without hand-holding
  • A CS degree from a strong program plus hands-on LLM / AI-agent experience (prompting, evaluation, guardrails, tooling)

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Why Join

  • A category-leading platform with elite backing, powering agents for marquee global brands
  • Ground-floor on a brand-new org: the Agent Builder team is only 7–8 people in seat, with real influence over how it evolves
  • Genuine technical depth, not a slideware seat: a :50/50 (up to 60/40) split of hands-on build and customer-facing delivery, owning enterprise agent builds end to end

Details

  • Location — London, UK
  • Work policy — On-site, 5 days/week
  • Compensation — £110,000–£150,000 + competitive equity
  • Visa sponsorship — Not available
  • Employment type — Full-time
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Skills

Python
LLM
AI Agent Tooling
Prompting
Evaluation
Guardrails
Workflow Design
Enterprise Integrations
CRM
Ticketing Systems
Data Pipelines
APIs
Customer-Facing Delivery
Post-Sales Engineering
Technical Execution
Communication

Location

London, England, United Kingdom

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