We're an AI-driven SaaS automation provider for corporate finance that automates back-office business processes involving tasks, analytics, and responses in Accounts Payable and Accounts Receivable. By leveraging natural language processing, artificial intelligence, and machine learning, based on proprietary small language models and commercial LLMs, 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 KPMG, Workday Ventures, Dell Technologies, Venrock, Innovius Capital, Sentinel Global, NeoTribe Ventures, Engineering Capital, and Firebolt Ventures, we build AI Team Mates that drive 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.
Best AI-Powered Financial Automation Solution of 2026 by Acquisition International Magazine's Global Excellence Awards.
CBInsights Fintech 100 - 2025.
Global Excellence Awards - Best AI-Driven Finance Automation Platform - 2025 Winner.
The Gartner Emerging Tech Impact Radar: Artificial Intelligence Report 2024 named Auditoria as a sample vendor for Composite AI.
Named a sample vendor for intelligent applications in finance in the Hype Cycle for Autonomous Accounting, 2024, the Hype Cycle for Finance AI and Advanced Analytics, 2024, and the Hype Cycle for the Future of Enterprise Applications, 2024 reports.
AI to transform financial back-office operations using advanced AI and ML. We are seeking an experienced Engineering Manager to lead our talented team of engineers building state-of-the-art, generative AI-powered SaaS solutions for enterprise finance. You'll manage a team of full-stack engineers working at the intersection of cutting-edge AI technology and practical enterprise solutions, driving both technical excellence and business impact in the FinTech space.
Technical Leadership: Lead, mentor, and grow a high-performing team of 6-10 full-stack engineers. Provide technical guidance on architecture, design, and development of cloud-native SaaS applications integrating advanced AI/ML features.
Champion engineering best practices, code quality, CI/CD, DevOps, and the use of modern development methodologies (Agile, TDD, code reviews, etc.), Operational Excellence: Ensure reliable operations, monitoring, and maintenance of cloud services (AWS), with an emphasis on security, multi-tenancy, and high availability.
Provide mentorship, feedback, and growth opportunities to team members.
Clearly communicate project status, technical direction, and risks to leadership and cross-functional partners. 2+ years of experience managing engineering teams delivering SaaS products, ideally in B2B/enterprise software.

10+ years of hands-on software development work, including leading complex projects.
Bachelor's or Master's degree in Computer Science, Engineering, or a related field from a reputed institute.
Proven experience with modern full-stack (https://jobeax.com/link/JSd7UYCSg572jJDY, https://jobeax.com/link/SobyZg7iaoMGy2or Python) and AI/ML-enabled solutions (LLMs, generative AI, prompt engineering, RAG, agentic workflows).
Hands-on experience integrating LLMs and embedding-based retrieval into production SaaS products, including prompt design, evaluation, and guardrails.
Strong Python programming skills, data structures, OOP, REST APIs (FastAPI), JSON, and shell scripting.
Expertise integrating with AWS services (or any other commercial Cloud services).
Strong background in system design, data modeling (RDBMS/NoSQL), and scalable microservices architectures.
Demonstrated ability to attract, mentor, and lead high-performing and geographically distributed engineering teams.
Strong project management, agile processes, and product delivery track record.
Experience with agent orchestration frameworks such as LangGraph, LangChain, CrewAI, or equivalent.

Experience in FinTech or Financial domain.
Track record of building and scaling engineering organizations at startup/growth-stage companies.

Engineering Manager - AI & ML

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