EMPONICS LIMITED
AI Deployment Engineer

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AI Deployment Engineer
Location: Bristol/London - Hybrid, 3 days in the office
Salary: to £130,000 p/a dependent on experience + excellent benefits
Our client is a Global FinTech with offices around the world including Bristol and London in the UK. This AI Deployment Engineer role can be based out of Bristol or London offices. Ideally 3 days per week in the office but could be a little bit more flexible for the ideal candidate.
You will be the deep technical engine behind their internal AI deployment team. Where the AI Deployment Strategist scopes and builds agents, you own the infrastructure underneath data pipelines, system integrations, and everything that ensures deployed AI solutions work reliably at scale.
You will take prototypes to production, ensure all business systems communicate correctly, and build the technical backbone that our AI tooling depends on.
Job Responsibilities
- Own the data infrastructure underpinning AI deployments pipelines, storage, and data serving
- Integrate AI solutions into the existing business ecosystem: CRMs, ERPs, SaaS tools, and internal systems
- Build and maintain APIs, webhooks, and middleware that allow AI agents to interact with business systems
- Take Strategist-built prototypes to production-grade hardening, scaling, and ensuring reliability
- Set up monitoring, logging, and alerting across deployed pipelines and agent infrastructure
- Manage data models, schemas, and storage supporting current and future AI deployments
- Troubleshoot integration failures, data inconsistencies, and production issues
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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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.
Key Skills
- Python & SQL (production-grade pipeline development)
- REST APIs, webhooks, OAuth, event-driven architecture
- Orchestration tools: Airflow, Prefect, or Dagster
- Cloud platforms: AWS, GCP, or Azure
- Docker & Kubernetes
- Microsoft 365 & Microsoft Copilot
Desirable Skills
- Vector databases and embedding pipelines
- Real-time streaming (Kafka, Flink)
- RPA tooling (UiPath, Power Automate)
- dbt for data transformation
- Claude Code, Claude Cowork, or Claude Skills
Experience
- 3-5 years in software or data engineering with strong exposure to system integrations, data pipelines, and production infrastructure.
- Strong Python and SQL skills; experienced building robust, production-grade data pipelines from scratch.
- Deep familiarity with integration patterns: REST APIs, webhooks, OAuth, and event-driven architectures.
- Experience with orchestration tools (Airflow, Prefect, or Dagster) and transformation frameworks (dbt or similar).
- Comfortable across cloud platforms (AWS, GCP, or Azure) and with containerisation (Docker, Kubernetes).
- Experience connecting disparate business systems SaaS platforms, internal databases, and third-party APIs and making them work reliably.
- Strong debugging instincts and a high bar for reliability and data integrity.
- Comfortable with Microsoft 365 and Microsoft Copilot. Familiarity with AI productivity tools including Claude Code, Claude Cowork, and Claude Skills is a plus.


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Qualifications
- Bachelor's degree in Computer Science, Engineering, or equivalent practical experience
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