Senior Full-stack Software Engineer

Who you are

• Minimum of 5 years of experience building applications using a modern stack built with .NET
• Hands-on experience with TypeScript and a modern front-end framework
• Proficiency with AI-assisted engineering tools
• Experience with relational and document-based databases
• Strong experience building, deploying, and maintaining APIs
• Experience with Azure and Docker is required
• Knowledge of Event-Driven Architecture and DDD principles
• Passionate about high-quality coding standards and testing of code
• Entrepreneurial mindset with the ability to work effectively in an ever-changing scale-up environment
• Strong communication and collaboration skills in English, both written and verbal
• Experience building or integrating with AI agentic applications in production (LLM orchestration, RAG, evals, prompt engineering)
• Experience with document processing (OCR, PDF extraction, Azure Document Intelligence, layout parsing)
• Domain experience in audit, accounting, or fintech
• Exposure to Event-Driven Architecture and Domain-Driven Design principles

What the job involves

• We are looking for a Senior Full-Stack Engineer to join the Integrations team at DataSnipper.
• The Integrations team builds the connectors that let people and AI agents work directly with the systems a business runs on — ERPs, accounting systems, general ledgers.
• We make that access simple, secure, and reliable, so our customers spend their time on the work itself rather than on getting data out of their systems
• You will work across the stack, C#/.NET on the server side, TypeScript/React on the front end, and Python for AI-powered services, building features that auditors trust with their most critical work
• This is a delivery-focused role for an engineer who is excited to make impact and grow in a team that ships fast, holds a high quality bar, and uses AI to accelerate development
• Build and maintain the connectors and services that pull data from ERPs, accounting systems, and general ledgers into DataSnipper, in C# / .NET, TypeScript, and Python
• Design the data models and mappings that turn each source system's schema into a consistent shape our product and AI agents can rely on
• Own new connector integrations end to end: research the source system's API and auth, build the connector and its agent tools and MCP surface, test against real customer data, and support it after launch
• Build the tooling and observability that keeps connectors reliable as source systems change their APIs underneath us
• Implement authentication and data handling controls that meet customer security expectations for access to their financial systems
• Write robust, well-tested, production-ready code, unit, integration, and end-to-end tests are part of the deliverable, not an afterthought
• Participate in code reviews as both author and reviewer, help maintain coding standards and design patterns across the team
• Participate in on-call rotation
• Use AI-assisted engineering effectively and responsibly, critically evaluating AI output
• Partner with product managers, designers, ML engineers, and QA to refine requirements, surface edge cases, and ship features
• Break down stories, estimate work realistically, and deliver against sprint commitments with limited supervision
• Contribute to technical design discussions, propose pragmatic solutions and challenge assumptions when it helps the team

The application process

• Recruiter screen
• Hiring Manager interview
• Peer programming session
• System design interview
• Final interviews with Engineering leadership