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Avance Consulting

AWS AI Engineer

Manchester
Posted about 20 hours ago
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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.

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.

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.
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“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.”

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Skills

Amazon Web Services
Amazon Bedrock
Amazon SageMaker
Generative AI
Large Language Models
RAG Architectures
MLOps
Terraform
AWS CDK
AWS Glue
Amazon S3
OpenSearch
AWS IAM
AWS KMS
Infrastructure as Code
Data Pipelines

Location

Manchester, England, United Kingdom

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