Sanderson
DevOps Engineer

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Outside IR35 Contract: Senior AWS Platform Engineer (AI Platform)
Day Rate:
Up to £600 Outside IR3
Location / Arrangement:
Up to 3 Days per Week in office – either Bristol or London office
Duration:
6 Months with the intention to further extend – long term greenfield programme
About Our Client:
Our client is a FTSE100 Investment Management firm, we are seeking a AWS Platform Engineer to support on a £ multi-million greenfield AI platform build out with the long-term goal of DevOps automation.
About the Role:
As a Senior Platform Engineer, you'll own the foundations our engineering teams build on. This is a deep AWS role, you'll be shaping the multi-account estate itself, not just deploying workloads into it and a growing part of it is building the platform capability that lets teams ship AI-enabled products safely and at scale.
About You:
- Deep, hands-on AWS expertise at platform level. You've designed and built landing zones and multi-account environments from the ground up - account vending, SCPs, IAM/identity federation, VPC and hybrid networking, centralised logging, and guardrails - not just consumed them. For example, this role may not be suitable for someone whose AWS experience is shipping Lambdas into an account someone else built.
- (Highly Desirable) You've built AI/ML platform capability on AWS yourself. Bedrock in particular - model access, guardrails, knowledge bases, agentic patterns - plus the surrounding tooling (SageMaker, vector stores, evaluation and observability).
- Expert-level Infrastructure as Code (Terraform strongly preferred; CloudFormation/CDK welcome) and strong scripting (Python, Bash) for complex automation and self-service tooling.
- Strong CI/CD, containerisation and orchestration — Harness (or equivalent enterprise CD tooling such as ArgoCD, Spinnaker, GitLab), Docker, and Kubernetes/EKS, with pipelines and deployment policy managed as code.
- Deep cloud security and governance knowledge — identity management, policy-as-code, and compliance standards (ISO, SOC, GDPR) in a regulated setting.
- Proven track record designing scalable, resilient, cost-efficient AWS solutions in complex enterprise environments.
- Strong analytical and decision-making skills, and the ability to explain technical concepts clearly to technical and non-technical stakeholders.
- Experience mentoring engineers and raising the bar around you.
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.
What You'll Do:


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- Design, build and evolve our AWS platform foundations - multi-account architecture, landing zones, Organizations/Control Tower, guardrails, networking and identity.
- Drive platform design and engineering standards, and embed golden paths that simplify and standardise how we build and run services.
- Enable automation, reliability and cost optimisation at scale - treating infrastructure, pipelines and policy as code.
- Mentor and support engineers, influence technical direction, and work across teams to deliver cloud-native solutions aligned to our clients goals.
- Take our AI platform capability from early foundations to a production-grade, self-service platform: Amazon Bedrock and the surrounding tooling (model access and routing, guardrails, knowledge bases/RAG patterns, agentic workflows), with the observability, cost controls and security posture required to run it in a regulated environment (AI Experience not essential but highly beneficial).
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