Spot and evaluate operational processes worth automating or redesigning - weighing impact, feasibility, risk, and scalability.
Partner with functional teams to map current processes, pain points, business rules, data needs, and desired outcomes.
Design, build, test, and deploy AI-enabled solutions and automations.
Integrate AI models and tools with operational workflows through APIs, scripts, databases, forms, and automation platforms.
Develop appropriate testing and validation approaches for solution accuracy, reliability, exception handling, data privacy, and operational readiness.
Support user testing, rollout, training, and adoption with functional owners and frontline users.
Leverage SQL and other analytical tools to explore data sets, establish performance baselines, diagnose issues, and measure solution performance alongside business impact
Structure and deliverer presentations with a clear storyline to both business and technical audiences
Requirements:
Bachelor's degree in Engineering, Computer Science, Information Technology, Data Science, Business Analytics, or related quantitative field - other backgrounds welcome with demonstrated technical skill.
Hands-on experience with at least one workflow automation or low-code tools such as n8n, Make, Zapier, Power Automate, or equivalent platforms
Demonstrate working knowledge of at least one programming or scripting language, with a strong preference for Python or JavaScript.
Practical understanding of generative AI/LLMs - prompting, limitations, hallucination risk, context management, structured outputs, and evaluation.
Experience with APIs, JSON, webhooks, databases, Git, or cloud tools preferred.
Experience with automation/low-code tools (n8n, Make, Zapier, Power Automate, or similar) is a plus.
Exposure to AI patterns like RAG, embeddings, document processing, classification, extraction, agents, or model evaluation is a plus.
SQL capabilities, encompassing data extraction, joins, aggregation, validation, and performance analysis
