Senior Technical Product Manager — Agent Runtime

Stack

Responsibilities

• ▹Define the runtime architecture: agent orchestration and multi-step loops, context and memory management, retrieval strategy, tool execution, model routing and fallbacks, guardrails, caching, streaming and concurrency
• ▹Own the platform's non-functional requirements: latency, throughput, reliability, graceful degradation, scalability under concurrent agent load, token-cost economics, security and observability
• ▹Create and run the product evals that prove agents are accurate and reliable, defining the quality bar before shipping, in partnership with the LLM Ops team
• ▹Drive model strategy: model selection, swaps and provider decisions, cost/performance trade-offs
• ▹Market intelligence and thought leadership: track how the field builds agentic systems, own a point of view and evangelize it internally and externally (talks, writing, customer and industry conversations)
• ▹Partner cross-functionally: technical peer to engineering managers and tech leads, translating experience-team needs into runtime capability and working with go-to-market on scale, stability and reliability

Requirements

• ▹4+ years in product management, with 2+ years on technical or platform products (APIs, infrastructure, ML systems or developer tools)
• ▹Deep understanding of LLM-based systems and agent architectures: prompting, tool use, planning, multi-step agent loops, context and memory, multi-agent systems, with enough grasp of retrieval/vector search to judge when it fits
• ▹Background in distributed systems or infrastructure, and how runtimes behave at scale
• ▹Treats non-functional requirements as a first-class product surface: latency, reliability, scalability, cost, observability
• ▹Hands-on experience creating and running evals that measure and improve agent accuracy and reliability at scale
• ▹Fluency in model operations: model selection and swaps, provider trade-offs, token cost/performance optimization
• ▹Can write technical specs that engineers review for feasibility and prototype with code to validate hypotheses
• ▹Experience writing prompt chains, debugging pipelines, reasoning about token cost or designing evals

Nice to have

• ▹Former software engineer, ML engineer or data scientist who moved into product
• ▹A public point of view on AI and agents (writing, talks, OSS) or the appetite to build one
• ▹Experience in audit, accounting or financial services

Soft skills

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)
• ▹Pension plan with a 6% contribution on top of base salary
• ▹28 vacation days per year (full-time)
• ▹Hybrid work model with at least 3 days onsite in the Amsterdam office
• ▹Daily freshly prepared lunches by an in-house chef
• ▹NS business card for commuting
• ▹Structured onboarding programme with dedicated time to learn the product and customers
• ▹Continuous learning and development initiatives
• ▹International team spread across seven global offices
• ▹Company-wide events like DataSnipper GO
• ▹Access to OpenUp, a mental health and wellness platform

About the company

DataSnipper is a bootstrapped unicorn with 600,000+ users across 180+ countries, used by top audit and accounting firms. Its Excel Agent brings AI directly into Excel, working with real documents and audit evidence with full traceability.