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Forward Deployment Engineer — Azure AI

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Forward Deployment Engineer — Azure AI
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Forward Deployment Engineer — Azure AI based in United Kingdom.
Join a high-impact engineering role where you will help organizations successfully adopt and operate cutting-edge Azure AI solutions. Acting as the bridge between platform engineering and project teams, you will guide deployments, streamline onboarding, and ensure AI workloads are delivered efficiently and securely. This position combines hands-on cloud engineering with stakeholder collaboration, offering the opportunity to influence platform improvements through real-world implementation feedback. You will work in a modern, remote-first environment alongside experienced engineers, contributing to scalable AI infrastructure while continuously enhancing deployment processes and best practices. If you enjoy solving technical challenges while working closely with customers and engineering teams, this role offers both ownership and meaningful impact.
Accountabilities
- Lead the onboarding of projects onto the Azure AI platform by following established deployment frameworks, runbooks, and best practices.
- Support requestor and client teams throughout onboarding, production launch, and the early operational lifecycle to ensure successful adoption.
- Configure and adapt Terraform modules, Infrastructure as Code, and CI/CD pipelines to meet project-specific requirements.
- Deploy and support machine learning workloads while assisting with lifecycle management across Azure environments.
- Identify deployment challenges, operational bottlenecks, and enhancement opportunities, providing structured feedback to Platform Engineering teams.
- Continuously improve onboarding documentation, reusable deployment patterns, and technical runbooks while ensuring compliance with security, governance, and operational standards.
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.
Requirements
- 5–8 years of experience in cloud engineering, platform engineering, DevOps, solution engineering, technical consulting, or a related field.
- Strong hands-on expertise with Microsoft Azure, including the Azure Well-Architected Framework and Azure AI services.
- Proven experience with Terraform, Infrastructure as Code, and CI/CD tools such as GitHub Actions, Azure DevOps, GitLab CI, or similar platforms.
- Good understanding of machine learning deployment processes and model lifecycle management.
- Excellent communication, stakeholder management, and client-facing consulting skills.
- Professional working proficiency in English.
- Experience with Azure Machine Learning, Azure AI Foundry, Azure OpenAI, Kubernetes, AKS, containerization, Python automation, LLMs, RAG solutions, or previous customer-facing engineering roles is considered an advantage.


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Benefits
- Competitive compensation package.
- Career growth and continuous learning opportunities.
- Flexible remote working environment with a high level of ownership.
- Collaborative, innovative, and engineering-driven culture.
- Opportunity to contribute to impactful AI and cloud infrastructure projects.
- International work environment with highly skilled and diverse teams.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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