Senior Data Architect

About Us

Auditoria is an AI-driven SaaS automation provider for corporate finance that automates back-office business processes involving tasks, analytics, and responses in Vendor Management, Accounts Payable, Accounts Receivable, and Planning. By leveraging natural language processing, artificial intelligence, and machine learning, Auditoria removes friction and repetition from mundane tasks while automating complex functions and providing real-time visibility into cash performance. Corporate finance and accounting teams use Auditoria to accelerate business value while minimizing heavy IT involvement, improving business resilience, lowering attrition, and accelerating business insights.

Founded in 2019 and backed by Venrock, Workday Ventures, Neotribe Ventures, Engineering Capital, and Firebolt Ventures, we build intelligent automation by combining fine-grained analytical orchestration of a company’s typical financial and audit workflows with conversational AI, delivering rapid value to the finance/audit back office.

In 2021, Auditoria earned industry recognition by being named to the Intelligent Apps Top 40 List, SSON’s Shared Services & Outsourcing Impact Awards, the Constellation Research ShortList for AI-Driven Cognitive Applications, HFS Research Hot Vendors, 2021 CRN Emerging Vendors List, TiE50 Award, and the winner of the inaugural Pitch Event by Constellation Research.

Since then, Auditoria was again named to the Constellation Shortlist for a record four consecutive years (‘20, ‘21, ‘22, ‘23). In 2022, Gartner named Auditoria a “Cool Vendor in Finance,” a curated list of solutions that challenge the traditional finance software market. In 2023, CRN once again recognized Auditoria as a Finalist for the CRN Tech Innovators Award. The SaaS Awards named Auditoria as a 2023 SaaS Awards Finalist for Best SaaS for Improved Productivity (USA). Most recently, Auditoria was named a finalist for the 2023 SSON Impact Awards for Technology of the Year.

The Opportunity for You

We are scaling an AI/ML enabled Enterprise SAAS solution to help manage cash performance of large enterprises, including multiple Fortune-500 companies. You would be owning the architecture responsibility during the 1-10 journey of the product in the FinTech AI space.

Key Responsibilities

• Data Architecture Leadership: Architect and design key features of Auditoria’s product using modern AI-native data patterns, leveraging the latest tech stack hosted on AWS and other cloud service providers.
• AI-Optimized Data Fabric: Design and implement a robust Data Abstraction Layer (Auditoria Data Fabric) that provides consistent data access to heterogeneous storage layers while being optimized for AI/ML workloads, including vector embeddings, semantic indexing, and multi-modal data.
• Governance & Compliance: Develop and enforce comprehensive data governance policies, ensuring data security, quality, and compliance across all systems, with special attention to financial data regulations and AI ethics considerations.
• Technical Leadership: Work with tech leads to guide the team on architecture, design patterns, and complex problem-solving for AI-enhanced data systems.
• Cross-Functional Collaboration: Partner with product managers and tech leaders across time zones to align data strategy with business objectives and AI innovation roadmap.
• Performance Optimization: Design and implement performance optimization strategies for data systems that support both traditional analytics and AI/ML operations at scale.
• Business Value Delivery: Partner with business teams to translate advanced data capabilities into measurable client value across financial workflows.
• Cultural Leadership: Champion Auditoria’s values, tech culture, and best practices in modern data management and AI-native architecture.
• Technology Foresight: Continuously evaluate emerging trends in data technology and AI/ML applications for finance, recommending strategic adoption paths.Qualifications

Required Qualifications

• Experience: 10+ years of overall experience with at least 5 years as an Architect for Large Scale SaaS Enterprise Applications.
• Enterprise SaaS Background: Deep experience designing and implementing enterprise-level data infrastructure in a SaaS environment, with knowledge of modern AI/ML data requirements.
• Business Application Integration: Experience building and running highly available SaaS enterprise business applications like Workday, NetSuite, Oracle, SAP, Salesforce and integrating these with AI/ML capabilities.
• Data Architecture Expertise: Extensive knowledge of data architecture principles, data governance frameworks, security protocols, and performance optimization techniques for both traditional and AI workloads.
• AWS Proficiency: Hands-on experience with AWS services such as RDS, Redshift, S3, Glue, DocumentDB, Step Functions, Cassandra, Kinesis, ELK, and AWS AI/ML services (SageMaker, Bedrock).
• Data Modeling: Strong understanding of advanced data modeling approaches spanning relational, unstructured, semi-structured, and vector data for AI applications.
• Data Processing Systems: Experience with data integration, ETL processes, and big data technologies (e.g., Hadoop, Spark) with an understanding of how they support AI/ML pipelines.
• Technical Proficiency: Strong programming skills in Node.js and familiarity with Python for data engineering and AI/ML workloads.
• Modern Infrastructure: Experience with multi-tenant SaaS, CI/CD environments, monitoring tools, Kubernetes, containers, Istio, workflow engines, and heterogeneous data stores optimized for AI operations.
• Communication Skills: Excellent ability to translate complex technical and AI concepts to non-technical stakeholders and executive leadership.

Preferred Qualifications

• AI/ML Experience: Hands-on experience with Generative AI, Large Language Models (LLMs), vector databases, and semantic search implementations in enterprise solutions.
• Data Mesh Architecture: Experience implementing Data Mesh principles and domain-oriented data ownership in large organizations.
• Real-time AI Systems: Background in designing real-time AI systems that combine streaming data with model inference.
• Financial Domain Knowledge: Familiarity with financial back-office operations, FinTech domain, and regulatory requirements.
• Vector Database Systems: Experience with vector databases (e.g., Pinecone, Weaviate, Milvus) and retrieval-augmented generation (RAG) architectures.
• Startup Excellence: Experience working in a high-growth startup environment, balancing immediate delivery with strategic architectural vision.
• Semantic Data Modeling: Experience with semantic data modeling, knowledge graphs, and ontologies for finance applications.
• AI Observability: Knowledge of AI observability systems and approaches to monitor, explain, and improve AI model performance in production.

What We Offer

• Competitive startup compensation package
• Early-stage equity options
• Comprehensive health benefits
• Unlimited PTO
• Flexible work environment
• Opportunity to shape the future of AI in enterprise finance
• Collaborative, innovation-driven culture

Auditoria.AI is an equal opportunity employer committed to building a diverse and inclusive team. We welcome candidates of all backgrounds passionate about combining cutting-edge AI with practical business solutions.