AI Automation / Application Engineer

Proclinical; Schweiz; On-site; CHF 110,000 - 160,000; Full time

Job summary

Proclinical is seeking an AI Automation - Application Engineer in Switzerland to join a dynamic team building AI solutions that automate business processes. You will design, develop, and maintain tools that streamline operations, deliver insights, and ensure compliant deployment.

The role focuses on creating AI-powered automation, dashboards with R Shiny, and integrating systems through APIs and data pipelines, collaborating with data science, IT, and compliance teams.

Qualifications

• Experience designing and deploying AI-powered automation tools.
• Strong Python, SQL, and REST API skills.
• Experience with R Shiny and dashboards.
• Familiarity with cloud data warehouses (Snowflake) and AWS.
• Experience with AI agents and LangGraph framework.
• GxP or regulated environment exposure is a plus.

Responsibilities

• Develop and maintain AI agents to automate tasks such as report generation and document checks.
• Create dashboards using R Shiny to provide insights and flag issues.
• 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 to validate tools.
• Conduct user testing, provide training, gather feedback, iterate for adoption.
• Maintain and troubleshoot live tools as source systems evolve.

Skills

Python scripting

R Shiny

SQL

REST APIs

LLM APIs

Prompt design

Git version control

AI agents

LangGraph

Tools

Docker

AWS

Snowflake

Shiny (R)

Pandas

Requests

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.