We are looking for a technically strong Software & Systems Engineer to join our growing team.
In this role you will design and build the software infrastructure that powers our business
operations developing robust data pipelines shipping AI-driven applications and engineering
custom integrations and automations across our core platforms. You will work closely with
Finance Operations and other business teams to translate complex requirements into reliable
well-engineered solutions.
Key responsibilities
Data engineering & infrastructure
Design build and maintain scalable data pipelines that ingest transform and deliver data from
multiple sources
Own and evolve the enterprise data warehouse writing clean well-documented data models
that serve reporting and analytics needs
Instrument pipeline health monitoring automated data quality checks and alerting; investigate
and resolve issues proactively
Partner with stakeholders to translate business requirements into reliable tested data solutions
AI application development
Build deploy and iterate on AI-powered applications and automation workflows that reduce
manual effort across the business
Engineer integrations between LLM-based agents and internal systems with a strong focus on
output reliability and data integrity
Identify and prototype opportunities where applied AI can meaningfully improve process
efficiency
Implement monitoring logging and guardrails to ensure responsible and auditable use of AI in
production
Platform engineering & integrations
Develop and maintain custom scripts APIs and workflows within NetSuite (SuiteScript) Arena
PLM and other business applications
Design and build API integrations between internal and third-party platforms including REST
and webhook-based patterns authentication flows and error handling Engineer system integrations between platforms ensuring data consistency and resilience
across the stack
Triage and resolve bugs in integrations custom scripts and automated workflows; write
regression tests to prevent recurrence
Maintain thorough technical documentation of all customizations configurations and integration
contracts
Qualifications
3 years in a software engineering data engineering or business systems engineering role
Strong proficiency in Python and SQL; comfort with JavaScript a plus
Proven experience building and operating data pipelines and ETL/ELT workflows in production
Solid understanding of data warehousing and experience with tools such as Snowflake
BigQuery Redshift
Hands-on experience with NetSuite (SuiteScript) or similar ERP/PLM customization and
scripting
Experience designing and consuming REST APIs including authentication patterns (OAuth API
keys) pagination and error handling
Engineering best practices mindset: version control code review testing and documentation
Preferred
Experience shipping AI/ML applications or integrating LLM-based agents into production
systems
Familiarity with Arena PLM or comparable product lifecycle management platforms
Exposure to workflow automation tools such as Zapier Make or similar
Background working with Finance or Operations data domains
Required Experience:
Manager
Business Systems Software EngineerAbout the roleWe are looking for a technically strong Software & Systems Engineer to join our growing team.In this role you will design and build the software infrastructure that powers our businessoperations developing robust data pipelines shipping AI-driven appl...
Business Systems Software Engineer
About the role
We are looking for a technically strong Software & Systems Engineer to join our growing team.
In this role you will design and build the software infrastructure that powers our business
operations developing robust data pipelines shipping AI-driven applications and engineering
custom integrations and automations across our core platforms. You will work closely with
Finance Operations and other business teams to translate complex requirements into reliable
well-engineered solutions.
Key responsibilities
Data engineering & infrastructure
Design build and maintain scalable data pipelines that ingest transform and deliver data from
multiple sources
Own and evolve the enterprise data warehouse writing clean well-documented data models
that serve reporting and analytics needs
Instrument pipeline health monitoring automated data quality checks and alerting; investigate
and resolve issues proactively
Partner with stakeholders to translate business requirements into reliable tested data solutions
AI application development
Build deploy and iterate on AI-powered applications and automation workflows that reduce
manual effort across the business
Engineer integrations between LLM-based agents and internal systems with a strong focus on
output reliability and data integrity
Identify and prototype opportunities where applied AI can meaningfully improve process
efficiency
Implement monitoring logging and guardrails to ensure responsible and auditable use of AI in
production
Platform engineering & integrations
Develop and maintain custom scripts APIs and workflows within NetSuite (SuiteScript) Arena
PLM and other business applications
Design and build API integrations between internal and third-party platforms including REST
and webhook-based patterns authentication flows and error handling Engineer system integrations between platforms ensuring data consistency and resilience
across the stack
Triage and resolve bugs in integrations custom scripts and automated workflows; write
regression tests to prevent recurrence
Maintain thorough technical documentation of all customizations configurations and integration
contracts
Qualifications
3 years in a software engineering data engineering or business systems engineering role
Strong proficiency in Python and SQL; comfort with JavaScript a plus
Proven experience building and operating data pipelines and ETL/ELT workflows in production
Solid understanding of data warehousing and experience with tools such as Snowflake
BigQuery Redshift
Hands-on experience with NetSuite (SuiteScript) or similar ERP/PLM customization and
scripting
Experience designing and consuming REST APIs including authentication patterns (OAuth API
keys) pagination and error handling
Engineering best practices mindset: version control code review testing and documentation
Preferred
Experience shipping AI/ML applications or integrating LLM-based agents into production
systems
Familiarity with Arena PLM or comparable product lifecycle management platforms
Exposure to workflow automation tools such as Zapier Make or similar
Background working with Finance or Operations data domains