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AI Automation​/Application Engineer

Job in City of London, Central London, Greater London, England, UK
Listing for: Randstad Technologies Recruitment
Full Time position Listed on 2026-11-11
Job specializations:
Salary/Wage Range or Industry Benchmark: 500 - 600 GBP Daily GBP 500.00 600.00 DAY

Job Description & How to Apply Below

Position: AI Automation / Application Engineer
Location: City of London

As an AI Automation / Application Engineer, you are a hands-on builder reporting to the Digital, Data & AI Infrastructure Lead. You turn operational business challenges into functional, high-impact tools-delivering rapid prototypes, automated data flows, and AI-enabled dashboards that streamline everyday workflows across the organization.

Key Responsibilities

Here is an overview of the core responsibilities:

AI Agents &

Skills:

Build practical AI assistants to handle repetitive tasks, automated document checks, and self-assembling reports.

Agentified Dashboards:
Develop and deploy R Shiny (or Shiny for Python) applications embedded with natural-language AI co-pilots.

Process Automation:
Streamline manual operational processes across spreadsheets, enterprise tools, and business systems.

Human-in-the-Loop Workflows:
Implement supervised automation patterns requiring human review and approval gates.

Data Pipelines & Scheduled Jobs:
Create reliable ETL jobs pulling, cleaning, and reconciling data across systems via REST APIs and SQL.

User Adoption & Maintenance:
Test prototypes directly with non-technical users, gather feedback, iterate rapidly, and maintain production tools as underlying systems evolve.

Must-Haves

Candidates must meet the following minimum criteria:

Experience:

3+ years building data applications, process automations, or internal business tooling.

Python:
Strong scripting, data wrangling (pandas, requests), and automated testing skills.

R & Shiny:
Demonstrated ability to build and deploy interactive R Shiny applications.

Integration & Data:
Proficient in SQL and connecting services via RESTful APIs.

Generative AI:
Practical experience integrating LLM APIs, prompt engineering, and structured JSON outputs.

Delivery Mindset:
Disciplined version control (Git) and ease working iteratively with non-technical end users.

Preferred Qualifications

The following qualifications are advantageous:

Experience with cloud data warehouses (Snowflake) and containerization/cloud deployment (Docker, AWS).

Exposure to agent orchestration frameworks (e.g., Lang Graph) or custom tool connectors.

Familiarity with pharmaceutical R&D, clinical development, or GxP-regulated workflows.

An active Git Hub profile or portfolio showcasing live data apps and automations.

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