GenAI Process Automation Engineer (POC & API Workflows)

About the team

The Process Automation Engineer is responsible for scoping, prioritizing, and building proof-of-concept (POC) process automations using LLM and generative AI technologies. This role partners closely with stakeholders to evaluate feasibility and expected impact, push back when requests are not viable, and rapidly prototype solutions that integrate across multiple web applications and data sources. Outputs are intended for validation and handover, not long-term production ownership.

What you'll do

• Exercise strong business judgment in scoping and prioritizing automation use cases—challenge assumptions, define clear MVPs, and build feasibility studies.
• Partner with stakeholders to translate ambiguous problems into clear POC requirements, success criteria, and test plans.
• Build rapid POCs that leverage LLM/generative AI capabilities to automate or augment business processes.
• Develop and iterate lightweight automation scripts/workflows that integrate across multiple web applications and tools (primarily via APIs and scripted interactions).
• Develop, maintain, and optimize data workflows sourced from existing, often poorly documented data marts and operational data sources. 
• Use SQL and scripting (e.g., Python) to extract, transform, and validate data needed for POCs and workflow execution.
• Conduct quality checks on data and POC outputs to ensure results are directionally correct for validation decisions. 
• Document POC approach, assumptions, limitations, and handover notes to enable downstream engineering/product teams to productionize if needed.

Requirements

• Bachelor’s Degree in Computer Science, Data Science, Statistics, or related field.
• Nice to have: Certification in Data Analytics, Machine Learning, or similar
• 2+ years in roles involving building prototypes/automations/workflows using scripting and data (not limited to BI).
• Proven experience in delivering scripts and/or data workflows from various data sources to drive business outcomes.
• Some experience working with large language models (LLMs) or AI technologies.
• Strong communication and collaboration skills to effectively interact with cross-functional teams.
• Strong proficiency in SQL, Python, and data workflow automation tools.
• Solid understanding (or willing to learn) of large language models (LLMs) and their applications in data analytics.
• Excellent analytical, problem-solving, and critical thinking skills.
• Ability to manage multiple tasks concurrently and prioritize effectively.