AI Automation / Application Engineer

Proclinical; England; On-site; GBP 45,000 - 75,000; Full time

Job summary

Proclinical is seeking an AI Automation - Application Engineer to join a team building AI solutions that automate processes and improve decision-making across the business.

You will design, develop, and maintain tools, integrate data from multiple systems, and deliver well-documented, scalable applications for regulated environments.

Working with data science, IT, and compliance, you will ship reliable dashboards and automation features while supporting users through testing and training.

Qualifications

• Proficiency in Python for scripting and data tasks.
• Experience with R and Shiny for apps.
• Strong SQL and API integration skills.
• Experience with generative AI tools and LLMs.

Responsibilities

• Develop and maintain AI agents to automate reports, document checks, and workflows.
• Create interactive dashboards using R Shiny, incorporating AI insights.
• Automate manual processes across business tools and documents.
• Build supervised automations with user review before deployment.
• Design data pipelines and integrations for reliable insights.
• Write tested, version-controlled code and document tools.
• Collaborate with senior engineers and compliance teams for regulated use cases.
• Conduct user testing, train users, gather feedback, iterate for adoption.
• Maintain live tools and troubleshoot as source systems evolve.

Skills

Python

R Shiny

SQL

REST APIs

Git

Docker

AWS

Snowflake

LangGraph

AI Agents

Prompt Design

BI/Data Prep

Tools

Docker

AWS

Git

LangGraph

REST API tooling

Job description

Excited by the opportunity to design and deploy AI applications that drive smarter decision-making?

Proclinical is seeking an AI Automation - Application Engineer to join a dynamic team focused on building innovative AI solutions that streamline business operations. In this role, you will work closely with cross-functional teams to design, develop, and maintain tools that automate processes, enhance decision-making, and improve efficiency. This position offers the opportunity to create impactful solutions while collaborating with experts in data science, IT, and compliance.

Responsibilities:

• Develop and maintain AI skills and agents to automate repetitive tasks such as report generation, document checks, and workflows.
• Create interactive dashboards using R Shiny or Shiny for Python, incorporating AI assistants to provide insights and flag issues.
• Automate manual processes across business tools, documents, and spreadsheets.
• Build supervised automations where outputs are reviewed and approved by users before implementation.
• Design and implement data pipelines and integrations to ensure reliable insights from business systems.
• Write tested, version-controlled code and produce clear documentation for tools and processes.
• Collaborate with senior engineers and compliance teams to validate tools for regulated use cases.
• Conduct user testing, provide training, gather feedback, and iterate on solutions to improve adoption and usability.
• Maintain and troubleshoot live tools, ensuring functionality as source systems evolve.

Key Skills and Requirements:

• Proficiency in Python for scripting, automation, and data processing (e.g., pandas, requests).
• Experience with R and Shiny for developing and deploying applications.
• Strong SQL skills and familiarity with integrating systems via REST APIs.
• Practical experience with generative AI tools, including LLM APIs and prompt design.
• Familiarity with Git and version control, and ability to work iteratively with non-technical users.
• Experience with cloud data warehouses like Snowflake.
• Knowledge of building AI agents, agent skills, or connectors to business systems.
• Familiarity with agent frameworks such as LangGraph.
• Proficiency in business intelligence and data preparation tools.
• Experience deploying applications and scheduled jobs using containers (e.g., Docker) in a cloud environment like AWS.
• Background in pharmaceutical R&D or other regulated environments (e.g., GxP).
• A portfolio or GitHub profile showcasing relevant work is a plus.