Oliver Bernard
Senior Data & AI Engineer - Hybrid (London)

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Senior Data & AI Engineer - Hybrid (London)
Salary: £90k-£100k + benefits
Location: London (3 days on-site)
We have partnered with a leading professional services firm that are building out their internal AI capability. They’re looking for a Senior Data & AI Engineer to design and deliver the systems powering their transformation.
You’ll join a small, high-impact team and build the core platform used across Tax, Audit, Advisory, Ops, and Leadership.
Why This Role Exists
Their services rely on documents, advisory processes, compliance and repeatable workflows, and these need to be automated + augmented to improve speed, consistency and quality.
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.
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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.
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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.
Main Responsibilities
- Design, build and deploy production-grade AI systems - from ingestion pipelines to LLM applications
- Develop and maintain reliable data pipelines & lakehouse infrastructure supporting analytics and AI workloads
- Own technical decisions across the stack - data modelling, retrieval patterns, evaluation frameworks, deployment approaches
- Run discovery with business teams to understand workflows, gather requirements and scope high-impact AI solutions
- Partner with stakeholders across service lines as a trusted advisor, shaping point solutions that deliver measurable value
- Raise engineering standards - testing, observability, CI/CD discipline, mentoring others, and driving operational excellence
- Stay close to the evolving AI ecosystem and introduce relevant innovations into production systems


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You’ll Bring
- Strong Python & SQL skills
- Hands-on experience building LLM-powered and RAG applications
- Solid understanding of data engineering foundations (ETL/ELT, data modelling)
- Business-facing approach, strong ability to act as the bridge between business and technology
- Experience with Databricks or equivalent Lakehouse platforms
- Bachelor’s or master’s degree in a STEM field
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
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