Vacancy description

Imported 2026-11-06 16:15:32.987866+00:00

About the Role As a Technical Support Specialist at DataSnipper, you'll be a key player on our AI-first support team, helping customers resolve complex technical issues while actively shaping how we scale and improve our support systems. This isn't a traditional support role. You'll work hands-on with our agentic AI infrastructure, helping to improve its resolution rate and answer quality, while independently handling escalated tickets that require real technical depth - think log analysis, API debugging, and coordinating with Engineering on code-level investigations. Beyond the day-to-day, you'll help build the foundation that makes our team better: maintaining our technical knowledge base, identifying recurring issue patterns to feed back into Product and Engineering, and contributing to the onboarding and development of new team members. You'll be joining a small, fast-moving global team based across Amsterdam, New York, and Kuala Lumpur, where curiosity, ownership, and a bias for systemic thinking are as valued as technical ability. Why DataSnipper? The hardest AI problems aren't about getting an answer fast. They're about getting one people can trust. We believe trust is essential to how society works. Every day, we rely on information that's been independently verified, from financial statements to the products we buy, to the sustainability claims companies make. Behind that trust are audit and finance professionals who examine evidence, verify information and hold organizations accountable. At DataSnipper, we build AI solutions that empower those professionals. By making evidence easier to trace and verify, we help them focus on the judgment and expertise that make their work so important. For our product and engineering team, this is where things get exciting. In audit, a plausible answer isn't good enough. Every output has to be explainable and traceable back to its source. We've just launched a brand new agentic platform, Alwin by DataSnipper. AI agents running in the cloud across hundreds of documents at once, reasoning across PDF, Word and Excel, with a full audit trail behind every step. There are lots of greenfield problems ahead, and real room to shape what we build and how we build it. And we build at scale. More than 600,000 professionals across 3,000+ organizations in 175 countries rely on DataSnipper, including Fortune 500 companies, government agencies and all Big Four audit firms. In 2025 alone, the DataSnipper platform delivered more than $1.4 billion in productivity savings to is customers. Backed by a $100 million Series B led by Index Ventures, at a $1 billion valuation, and as proud members of 1% for the Planet, we care about how we grow, not just how fast. If you want to build AI that professionals trust with work that really matters, this is your chance to help shape the future of audit and finance and do the best work of your career along the way. What You Will Do Work closely with our agentic AI infrastructure to continuously improve its resolution rate and the quality of the answers it produces Independently resolve escalated technical support tickets, diagnosing root causes using logs, scripts, and internal tooling, and coordinating with Engineering for code-level investigation when needed Partner with Customer Success and Engineering to drive timely resolution of customer-impacting bugs and incidents Maintain and improve the technical knowledge base, creating troubleshooting guides that reduce repeat issues. Track recurring issues, feeding patterns into Product and Engineering to drive systemic improvements Contribute to onboarding and training of new support team members What You Bring 2–4 years of experience in a technical support or application support role in a B2B SaaS environment Strong diagnostic and troubleshooting skills, comfortable working with logs, APIs, and browser developer tools Strong all-round technical aptitude across computers, software, and AI, able to navigate systems such as Windows and Azure, run basic networking checks, inspect the registry, and quickly pick up new software and technical concepts to get things done in unfamiliar environments Solid understanding of SaaS product architecture concepts (APIs, integrations, data flows) Experience with CRM and ticketing systems such as Intercom, Zendesk, Jira, or similar AI tool fluency, able to use AI to increase productivity, analyze data, and actively contribute to support AI agent improvement loops Adaptability to flex across priorities as needed, from strategy and AI improvement work to hands-on ticket crunching during peak-volume periods Committed, self-driven attitude with strong ownership, urgency, and follow-through, able to work independently, manage multiple open tickets, and prioritize effectively Clear and professional communication skills, both written and verbal, for customer-facing interactions Proficient in English, both spoken and written Experience with Excel, audit tools, or financial software is a strong plus Open-minded and adaptive to changing conditions, always looking for opportunities to scale our systems rather than just working through the queue What We Offer Be part of one of the fastest-growing, profitable unicorn scale-ups in the Netherlands with a global impact Equity (Stock Appreciation Rights) to share the company's success and growth Pension plan with a 6% contribution on top of your base salary 28 vacation days per year (full-time) to support your work-life balance Hybrid work model with at least 3 days onsite in our dynamic Amsterdam office Daily, freshly prepared lunches by our in-house chef to keep you energized NS business card for easy commuting to the office if applicable Access to continuous learning and development initiatives to grow your skills Engage with a vibrant international team spread across five global offices Company-wide events like DataSnipper GO, where global teams come together Access to a mental health and wellness platform supporting your wellbeing Recruitment Process Recruitment Screen (30 minutes, online) Hiring Manager Interview (30 minutes, online) Assessment Round (60 minutes, online) Final Interview (30 minutes, on-site) At DataSnipper, we believe great ideas come from different perspectives, experiences, and backgrounds. We are committed to building an inclusive workplace and providing every candidate with a fair and equitable hiring experience. Our hiring decisions are merit-based and grounded in the skills, experience, potential, and capabilities relevant to the role. We welcome applicants regardless of age, race, ethnicity, nationality, gender, gender identity or expression, sexual orientation, religion, disability, or any other characteristic that makes you, you. What matters to us is what you can bring to the role, the team, and DataSnipper. 🚀

Full-text baseline

Classified 2026-11-07 12:47:23.898866+00:00

AISuggestion

Explicit role/task wording or requested domain skills support the proposed scope; LTA review remains required.

Skills suggested

  • LLM application engineering
    Source passage

    You'll work hands-on with our agentic AI infrastructure, helping to improve its resolution rate and answer quality, while independently handling escalated tickets that require real technical depth - think log analysis, API debugging, and coordinating with Engineering on code-level investigations.

Proposed e-CF links

Suggested links for review. They do not assess skill levels.

Other source passages

You'll work hands-on with our agentic AI infrastructure, helping to improve its resolution rate and answer quality, while independently handling escalated tickets that require real technical depth - think log analysis, API debugging, and coordinating with Engineering on code-level investigations.

AI suggestion

Classified 2026-11-07 16:23:57.397258+00:00

AINeeds review

AI improvement and answer-quality work establish AI scope, but the text does not state whether these requirements are mandatory or preferred. Data analysis is mentioned as AI-assisted productivity, not as a distinct professional data task.

Skills suggested

  • AI application use
    Source passage

    AI tool fluency, able to use AI to increase productivity, analyze data, and actively contribute to support AI agent improvement loops

  • AI system evaluation
    Source passage

    Work closely with our agentic AI infrastructure to continuously improve its resolution rate and the quality of the answers it produces

  • Needs and results communication
    Source passage

    Clear and professional communication skills, both written and verbal, for customer-facing interactions

Proposed e-CF links

Suggested links for review. They do not assess skill levels.

Other source passages

Work closely with our agentic AI infrastructure to continuously improve its resolution rate and the quality of the answers it produces

AI tool fluency, able to use AI to increase productivity, analyze data, and actively contribute to support AI agent improvement loops