About Preql
Preql is building the AI-powered financial data platform for the modern enterprise. We're developing agentic AI workflows that help finance teams clean, transform, and structure their data without writing code. Think "Lovable.com for data pipelines" - just as website builders help users refine ideas into working apps, Preql helps users refine messy, fragmented financial data into production-ready workflows using natural language.
Our customers include media companies, media networks, retailers, and manufacturers who need reliable metrics and automated reporting. The company is backed by tier 1 venture firms and previous data company founders.
The RoleWe're seeking a Product Engineer to own the core of our agentic workflows, starting with a data cleaning agent. You'll architect and implement an MVP that transforms how finance teams interact with their data - moving from manual Excel workflows to AI-powered, auditable data transformations.
What You'll Build:
Agentic AI workflows that convert natural language instructions into structured data transformations
Interactive data cleaning pipelines where users can refine transformations through conversational feedback
Audit-ready transformation engines that show their work and generate reproducible scripts (backed by code)
Web-based workflow builders that feel as intuitive as drag-and-drop but generate production code
Integration harnesses for Excel, CSV, and eventually ERP systems like NetSuite and QuickBooks
Key Responsibilities:
Design and implement the core agentic workflow engine from POC to MVP
Build user interfaces that make complex data transformations accessible to non-technical finance users
Create the technical foundation for LLM-powered data cleaning that maintains auditability and compliance
Develop APIs and integrations for financial data sources
Collaborate directly with customers to validate technical approaches and gather product feedback
Own the full stack from data ingestion to transformation output
Technical Foundation:
4+ years building production software with modern web technologies (TypeScript, Python, etc.)
Experience with LLM APIs (OpenAI, Anthropic) and agentic workflow patterns
Familiarity with data processing frameworks, ETL/ELT workflows, and data transformation tools and techniques
Understanding of cloud infrastructure (AWS, GCP, or Azure)
Product Mindset:
Track record of taking features from concept to production in fast-moving environments
Experience gathering user feedback and translating it into technical requirements
Understanding of data workflows and analytics concepts
Comfort working directly with enterprise customers
Finance/Compliance Awareness:
Understanding of audit requirements and data lineage needs
Familiarity with financial data formats and common transformation patterns
Appreciation for regulatory compliance in enterprise environments
Nice-to-haves, but not strict requirements.
0→1 Experience: Evidence of manifesting ideas into product
AI/ML Experience: Building products with LLMs, prompt engineering, or agentic workflows
Data Platform Experience: Working with Snowflake, Databricks, or similar modern data stacks
Financial Software: Hands-on experience with NetSuite, QuickBooks, HubSpot, or ERP systems
Enterprise Sales: Customer-facing experience with technical sales or solution engineering
Compliance Background: SOC 2, audit trail requirements, or regulatory data handling
You'll be building the foundational technology that defines how AI transforms enterprise data workflows. This isn't about incremental improvements to existing tools - you're creating entirely new interaction patterns between humans and data systems.
Impact: Your code will directly determine whether finance teams can trust AI with their most critical data Growth: Join as a founding engineer with significant equity and leadership opportunities Innovation: Work at the cutting edge of agentic AI applied to real business problems
Next StepsReady to build the future of data transformation? Send us a 50-word note introducing yourself and why this role is interesting to you. Additionally, include a resume/LinkedIn and, if available for sharing, include a portfolio highlighting relevant projects, especially any work with AI agents, data pipelines, or enterprise software.
Skills Required
- 4+ years building production software with modern web technologies
- Experience with LLM APIs such as OpenAI or Anthropic and agentic workflow patterns
- Familiarity with data processing frameworks, ETL/ELT workflows, and data transformation techniques
- Understanding of cloud infrastructure such as AWS, GCP, or Azure
- Track record of taking features from concept to production in fast-moving environments
- Experience gathering user feedback and translating it into technical requirements
- Understanding of data workflows and analytics concepts
- Comfort working directly with enterprise customers
- Understanding of audit requirements and data lineage needs
- Familiarity with financial data formats and common transformation patterns
- Appreciation for regulatory compliance in enterprise environments
- 0-to-1 experience bringing ideas into products
- AI/ML experience, including LLM products, prompt engineering, or agentic workflows
- Data platform experience with Snowflake, Databricks, or similar technologies
- Hands-on experience with NetSuite, QuickBooks, HubSpot, or ERP systems
- Enterprise sales experience, including technical sales or solution engineering
- Compliance background involving SOC 2, audit trails, or regulatory data handling
What We Do
Preql is an agentic data-cleaning platform for complex enterprise environments. Its AI agents transform fragmented ERP, CRM, HR, and expense data into structured, auditable, AI-ready pipelines that scale across the enterprise. The company serves AI and data teams, CIOs, CFOs, and CEOs, helping organizations automatically catch costly data errors where legacy infrastructure, disparate systems, and rigorous compliance requirements increase operational risk.
