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We are seeking a detail-oriented and experienced Regional Asset Manager to oversee the management of our Data Center IT infrastructure assets. You will play a crucial role in ensuring efficient utilization, tracking, and management of IT equipment to support operational excellence in IT department.

Key Responsibilities:
Be responsible for an inventory database for all IT assets, including servers, storage systems, networking equipment including data center IT components like GPUs, transceivers and many more.

Conduct regular audits of physical and virtual assets to ensure accuracy and compliance with company policies.

Manage the entire lifecycle of IT assets from procurement through deployment, maintenance, and eventual disposal.

Manage RMA process for GPUs, Motherboard, Power supplies, and many more data centre components.

Generate regular reports on asset utilization, performance metrics, and financial analysis related to the IT infrastructure.

Analyze trends and provide recommendations for optimizing asset performance and reducing costs.

Establish and enforce policies regarding asset management practices, including security, compliance, and risk management.

Ensure adherence to industry standards and regulations concerning IT asset management.

Work closely with IT departments, project managers, and other stakeholders to support projects and initiatives requiring asset allocation.

Communicate asset status and potential issues to senior management and relevant teams effectively.

Identify opportunities for process improvements in asset tracking, reporting, and life cycle management.

This role focuses on designing and implementing secure architectures across corporate networks and cloud environments. You will play a key role in defining secure solutions, reviewing system designs, and ensuring security is embedded across enterprise infrastructure.

The ideal candidate brings strong hands-on expertise in network and cloud security, along with the ability to work closely with IT, Infrastructure, DevOps, and Engineering teams to drive secure and scalable implementations.

Youre welcome to work in our offices in Amsterdam.

Your responsibilities will include:

Design and implement secure architectures across corporate networks, cloud platforms, and hybrid environments.
Define and maintain security standards, guidelines, and reference architectures aligned with organizational requirements.
Review and approve architecture and design of new systems, infrastructure, and network changes.
Design and support secure enterprise network architectures, including segmentation, Zero Trust, and remote access solutions.
Define and implement controls for firewalls, ZTNA, proxies, and network access control (NAC).
Design secure cloud architectures including IAM, networking, and workload protection.
Ensure proper implementation of cloud security controls such as segmentation, encryption, and monitoring.
Define and support identity and access management controls, including SSO, MFA, and privileged access.
Contribute to endpoint security architecture, including EDR/XDR and device hardening standards.
Identify security risks and architectural gaps and recommend mitigation strategies.
Participate in architecture reviews, risk assessments, and security design discussions.
Collaborate with SOC, Vulnerability Management, IT, and Engineering teams to improve overall security posture.
Support implementation of security architecture initiatives and improvements across the organization.

We are looking for a skilled Security Automation Engineer to join our SOC Automation team and play a key role in building and scaling automation across Security Operations. This is a hands-on role - you will design, develop, and integrate automation solutions across SIEM, EDR, and other security platforms, contributing to our SOAR capabilities from the ground up.

You will work in a technologically rich environment, integrating with a wide range of security and infrastructure systems across the network - a unique opportunity to build automation at scale in a greenfield setting, with real influence over the architecture and tooling decisions.

We are especially interested in candidates who are curious about leveraging AI and intelligent agents to help evolve next-generation automation and response workflows - and who want to be a driving voice in how we apply those technologies.

Your responsibilities will include:

Automation development

Design and develop automation workflows for incident response and SOC operations
Identify and eliminate manual processes through scalable automation
Build reusable components and maintainable automation patterns
Engineering & integration

Develop integrations using REST APIs, webhooks, and event-driven architectures
Write high-quality, maintainable Python for automation and orchestration
Implement data parsing, enrichment, and transformation across multiple systems
SOAR & platform buildout

Lead or actively contribute to the evaluation, selection, and implementation of SOAR/automation platforms
Design the automation architecture and integration strategy for the team
Build automation capabilities in a greenfield environment - your decisions will shape the foundation
SOC collaboration

Work closely with SOC analysts and incident responders to translate operational needs into automation solutions
Improve end-to-end detection and response workflows through close partnership with the team
AI & innovation

Actively build and evaluate AI/LLM and agent-based workflows applied to security automation
Prototype AI-assisted enrichment, triage, and response solutions and drive them toward production

Were looking for a Senior Backend Software Engineer to help develop our hyperscaling platform.
We have a lot of tasks on Golang and little less on Java and Python.
Youre welcome to work from our office in Prague, Berlin, London or in Amsterdam, hybrid or remotely. 

In this position, your responsibility will be to:
Developing fault-tolerant, reliable cloud services: cloud infrastructure, managed databases, managed Kubernetes, billing, monitoring systems, ML service and more.

We are currently looking for senior- and staff-level ML engineers to work on research in areas such as:

Guided search and reinforcement learning for agentic systems
Reinforcement learning for reasoning models
Web-scale problem collection for training agents
Efficient model distillation
Some examples of what your responsibilities might include are:

Conducting experiments to figure out efficient ways to train a large language model on traces of interactions with various environments
Exploring methods of guided generation and search in the trajectory space
Coming up with ways to mine relevant data at web scale and figuring out efficient ways to use this data in model post-training
Conducting experiments with different reinforcement learning configurations in verifiable domains
Exploring methods to train AI agents on tasks with non-verifiable reward signals

Some directions we currently working on and which you can be a part of:
Advanced Fine-Tuning: Enhancing fine-tuning methodologies - both LoRA-based and full-parameter - for cutting-edge LLMs (e.g., GPT-OSS, Kimi K2.5, DeepSeek V3.1/V3.2, GLM-4.7), focusing on both model quality and training efficiency.

Inference Optimization: Identifying LLM inference bottlenecks to drive production speedups. This involves building model training and evaluation pipelines in JAX for speculative decoding, experimenting with architectures (dense/MoE, auto-regressive/parallel), and deriving scaling laws to guide resource allocation.
Low Precision Training & Inference: Investigating low-precision (FP8, NVFP4/MXFP4) methodologies for supervised fine-tuning and reinforcement learning - spanning both inference and training - optimized for modern hardware

We are building a high-performance inference and fine-tuning platform designed to push foundation models to their hardware limits. Our mission is to maximize throughput, minimise latency, and optimise cost-per-token across tens of thousands of GPUs.



Some directions we are currently working on, and which you can be a part of:

Inference Optimization: Identifying LLM inference bottlenecks to drive production speedups. Squeezing the maximum performance for a wide range of LLM architectures at scale (e.g., GPT-OSS, Kimi K2.5, DeepSeek V3.1/V3.2, GLM-5).
Inference engines support: Implement novel speculative decoding architectures, optimise components of various LLM designs (dense/MoE, autoregressive/parallel), and contribute to open-source inference engines.
Low Precision Training & Inference: Design and productionise low-precision (FP8, NVFP4/MXFP4) training and inference pipelines with measurable gains in throughput and cost-efficiency.

We're hiring an exceptional Applied AI Scientist to join our team!
In this role, you'll design and deploy enterprise-grade AI agents that drive real business impact across core functions - Sales, Marketing, Customer Success, Customer Support, Risk, and Finance. You'll be building agentic systems that execute complex, multi-step business workflows end-to-end. The ideal candidate is a hands-on builder with deep AI expertise who thrives on turning complex business problems into reliable, production-grade AI systems.
In This Role, You Will Be Responsible For:
Enterprise AI Agent Development: Designing, building, and deploying AI agents that automate and augment high-value workflows across business functions - including lead qualification and outreach (Sales & Marketing), churn reduction(Customer Success), and Ticket deflection (Support).
Agentic Architecture & Orchestration: Owning the end-to-end agent stack - from tool use, memory management, and multi-step planning to human-in-the-loop escalation patterns, guardrails, and audit trails suited for an enterprise fintech environment.
Knowledge Systems: Building and maintaining RAG pipelines that ground agents in proprietary knowledge - product documentation, customer data, financial records, and internal playbooks - using vector databases, hybrid search, and re-ranking.
Evaluation & Continuous Improvement: Defining agent evaluation frameworks that measure task completion, accuracy, hallucination rates, latency, and business impact - then iterating on agent behavior based on real usage data and stakeholder feedback.
Cross-Functional Collaboration: Partnering with stakeholders across the company to define agentic use cases, translate business requirements into technical features, and deliver products that create measurable ROI - from data preprocessing through product deployment.

We're looking for an Engineering Tech Lead to join the AI Core team and lead the technical direction of one of the core capabilities in AI Platform.
This role combines hands-on development with technical leadership, including architecture design, technical decision-making, mentoring engineers, and close collaboration with Product, Architecture, and cross-functional engineering teams.
This is an opportunity to help shape AI Platform, influence key technical decisions, and build the infrastructure that powers AI capabilities across the company. You'll work on challenging technical problems, collaborate with exceptional engineers, and have a significant impact on the future of AI .
In This Role, You Will Be Responsible For
Provide technical leadership and mentorship to the team.
Design scalable, reliable, and maintainable solutions.
Lead architecture discussions and drive technical decisions.
Conduct design and code reviews to ensure high engineering standards.
Lead end-to-end delivery of complex features and initiatives.
Collaborate closely with Product, Architecture, and other engineering teams.
Drive improvements in system quality, performance, security, and scalability.

We are looking for a Senior Product Manager to join our Agentic Search team, building the search and retrieval infrastructure that powers AI agents and LLM-based applications at scale.

This is a hands-on IC role with real ownership. You will take full end-to-end responsibility over a core product area, from defining strategy through shipping and iterating based on real usage data. You will work within a small PM team reporting to the Director of Product, alongside engineering, design, and go-to-market, shaping how AI agents discover, retrieve, and act on web information in real time.

The product serves both a developer-facing PLG motion and a growing enterprise customer base, so you will need to be equally comfortable digging into API design and search quality as you are running customer discovery calls and informing competitive positioning. We are looking for someone who can operate as a senior strategic partner, not just an executor, and who has the potential to grow into a principal-level PM over time.

Youre welcome to work hybrid from Tel Aviv, Israel.

Your responsibilities will include:

Own a core product area end-to-end: strategy, roadmap, execution, and iteration based on real usage signals and customer feedback.
Drive search quality and relevance improvements by working closely with engineering and research to define evaluation frameworks, benchmarks, and release criteria.
Engage directly with enterprise customers and developer users to validate ideas, understand pain points, and shape product-market fit across both PLG and enterprise motions.
Monitor the competitive landscape in agentic search and AI-powered retrieval, identifying shifts, threats, and opportunities that should inform product decisions.
Collaborate with go-to-market teams (sales, solutions, growth) to ensure product positioning, ICP definitions, and enablement materials reflect product reality.
Contribute to product strategy as a senior voice on a small, high-impact team, challenging assumptions and bringing independent judgment to key decisions.
Lead product experiments and rapid iteration cycles, moving from hypothesis to prototype to production with clear success criteria.

We're looking for a hands-on Engineering Manager to lead a team of senior engineers owning this space end-to-end, from integration design through production ownership. You'll have real autonomy, a direct line from your team's work to customer outcomes, and room to shape how a technically deep domain is built and run.
What you'll own:
Lead and grow a team of engineers, creating clarity on priorities, raising the technical bar, and building real domain ownership
Own execution end-to-end: integration architecture, technical design, delivery predictability, and the operational health of systems that sync critical financial data at scale
Drive reliability and data correctness, strong debugging and sound judgment around sync semantics, idempotency, error handling, and recovery, plus calm decision-making when something breaks in production
Make sure your engineers understand the business and the ERPs behind the systems, the financial flows and edge cases, not just the code
Translate business goals and the realities of messy, heterogeneous ERP systems into pragmatic technical plans
Partner closely with Product, Operations, Support, and other engineering teams to deliver integrations that balance customer impact, time-to-value, and quality
Coach engineers through feedback, mentoring, and high standards

we are looking for a Senior Site Reliability Engineer (DevTools)
Your responsibilities will include:

Improving services based on user feedback

Building fault-tolerant, self-healing architecture

Finding ways to speed up our systems and reduce user friction

Modifying well-known closed- and open-source solutions Supporting our users

Ensure fault-tolerance, scale, and uninterrupted operations for the service.
Use cutting-edge cloud technology to solve a variety of infrastructure problems.
Implement and improve CI/CD processes.

We're looking for a Software Engineer to join our core engineering team and help build the infrastructure behind one of the fastest-growing AI APIs. You'll work on systems that handle massive scale across a distributed microservices architecture running on AWS. You'll ship fast, take ownership of critical systems, and solve hard infrastructure problems as we grow.

This is a great role for an engineer who loves building ambitious systems from scratch, and wants to tackle the kind of scale and complexity challenges typically reserved for much larger companies.

What Youll Do

Design and build high-performance distributed systems

Design and implement backend infrastructure and API endpoints

Build and optimize real-time data pipelines that process billions of events per day across distributed queues and stream processors

Improve performance, monitoring, and reliability across the stack

Own core systems and contribute to key architectural decisions

Help shape a strong engineering culture focused on velocity and quality