Senior Technical Product Manager – Agent Runtime

DataSnipper

Technical PM managing agent runtime architecture and non-functional requirements at DataSnipper. Engaging with infrastructure and ML engineers to build high-performance AI products.

Posted 6/29/2026full-timeAmsterdam • 🇳🇱 NetherlandsSeniorWebsite

Tech Stack

Tools & technologies

Distributed Systems

About the role

Key responsibilities & impact

Own the agent runtime architecture.
Provide technical direction for our agent runtimes: agent orchestration and multi-step loops, context and memory management, retrieval strategy, tool execution and orchestration, model routing and fallbacks, guardrails, caching, streaming, and concurrency.
Define and own the non-functional requirements of the platform including how well the platform runs: latency, throughput, reliability, graceful degradation, scalability under concurrent agent load, token-cost economics, security, and observability/telemetry.
Own the creation and running of product evals that prove our agents are accurate and reliable.
Oversee the model strategy including model selection, swaps, and provider decisions; cost/performance trade-offs; staying current as frontier models move.
Track market intelligence and provide thought leadership on agentic systems to differentiate the company.

Requirements

What you’ll need

4+ years in product management, with 2+ years on technical/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's the right tool
Background in distributed systems or infrastructure - you understand how runtimes behave under scale and how a change ripples across the stack
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 (not correctness) and prototype with code to validate hypotheses; comfortable with architecture trade-offs (latency vs. accuracy, cost vs. capability)

Benefits

Comp & perks

Equity (Stock Appreciation Rights) to share in 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 energised.
NS business card for easy commuting to the office.
A structured onboarding programme designed to set you up for success, including dedicated time to learn our product and customers before you hit the ground running.
Access to continuous learning and development initiatives to grow your skills.
Engage with a vibrant international team spread across seven global offices.
Company-wide events like DataSnipper GO, where global teams come together.
Access to OpenUp, a mental health and wellness platform supporting your wellbeing.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Product ManagementTechnical SpecificationsModel SelectionMulti-Agent SystemsContext and Memory ManagementLatency OptimizationScalability AssessmentTool ExecutionConcurrency ManagementEvaluation Creation