Avance Consulting
AWS AI Engineer

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Role Title: AWS AI Engineer
Location: Manchester, UK
Days on site: 2-3 days per week
Job Type: Contract
Role Description:
An AWS AI Engineer designs, builds, and deploys production-grade artificial intelligence and machine learning applications using Amazon Web Services. They bridge the gap between data science and cloud infrastructure by setting up scalable data pipelines, managing model lifecycles, and integrating foundation models via tools like Amazon Bedrock and Amazon SageMaker.
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.
Key Responsibilities


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- Model Deployment & Integration: Build and host generative AI or machine learning models, connecting large language models (LLMs), RAG architectures, and AI agents into reliable cloud services.
- Pipeline Management: Develop secure data ingestion, transformation, and vector search pipelines using services like Amazon S3, AWS Glue, and OpenSearch.
- MLOps & Infrastructure: Automate deployments, monitor model drift, and scale cloud infrastructure using Infrastructure as Code (IaC) tools like Terraform or AWS CDK.
- Security & Compliance: Enforce enterprise security rules, data privacy, and access management via AWS IAM and KMS.
“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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