AI Automation Engineer
Build and deploy AI-powered automation, integrations, data pipelines, and analytics solutions embedded within the Finance team. The role requires strong programming, data engineering, systems integration, stakeholder collaboration, and a bachelor's degree in computer science or a related field.
About the job
Responsibilities
- Identify opportunities within Finance and implement AI-powered solutions for complex business problems.
- Guide finance professionals in using AI tools and technologies for data analysis and decision-making.
- Design, build, and maintain AI-enabling infrastructure, including custom tools, server-side logic, system integrations, and data pipelines.
- Develop and manage data acquisition processes, including sourcing, cleaning, and preparing data for AI models and analytics.
- Conduct data analysis, validate data integrity, and support strategic finance initiatives.
- Translate Finance team needs into robust technical solutions and serve as a technical bridge to other engineering groups.
- Improve team productivity by automating or optimizing key Finance workflows with AI solutions.
Requirements
- Experience working closely with business stakeholders, preferably in finance or business operations.
- Experience designing and building integrated solutions using REST APIs, databases, and related data flows.
- Strong programming skills for data acquisition, cleaning, and preparation.
- Experience with data warehousing and a solid understanding of data modeling.
- Bachelor's degree in Computer Science or a related field.
Benefits
- Flexible paid time off and annual company-wide closure.
- Sponsored benefits for US-based employees and supplemental international coverage.
- Professional development opportunities and annual learning subsidy for US and EMEA-based employees.
- Monthly productivity stipend for US and EMEA-based employees.
- Team off-sites and annual company-wide meet-up.
- Paid parental leave and bereavement leave.
Skills
Artificial Intelligence, REST APIs, Databases, Data Pipelines, Data Warehousing, BigQuery, Snowflake, Data Modeling, Data Analysis, Data Cleaning, Server-Side Logic, System Integrations
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