Production Support And Incident Commander in Amsterdam

About BlockTech BlockTech is a fast-paced algorithmic trading firm facilitating global cryptocurrency derivatives and spot trading while expanding into new markets. Positions, PnL, and hedging all run through our Mid-Office team. When the numbers our traders and risk team rely on are wrong, this is where it gets found and fixed. The role We're looking for a Software Engineer to join our Mid-Office team in this role, you'll own the systems that keep positions, PnL, and hedging correct across every venue we trade. You build and run the platform, and you're the one who notices when a number looks wrong and follows it until you know why. You will: Own the books. Maintain and evolve our position, trade, and PnL systems so they stay accurate across every venue. Do the quant work. Build and refine our hedging, Greeks, margin models, and early exercise premium calculations. Surface the risk. Build the risk views and calculations that show traders and the risk team what exposure we're carrying. Support the desk. Work side by side with traders and researchers, making sure the data they rely on is correct and available. Deliver reporting. Provide the data that internal stakeholders and regulators require, PnL breakdowns, trade surveillance, treasury accounting, and compliance. Own it in production. Spot discrepancies in live data, trace the root cause, and maintain what you ship. What we're looking for An engineer at heart with a strong quantitative background. Real enthusiasm for the engineering work. A relevant educational background, ideally in a quantitative field such as Mathematics, Econometrics or Computer Science. Professional work experience with Python, Grafana and PostgreSQL. Strong Debugging skills. You can trace problems to their source even in unfamiliar systems A critical mind that follows things until completion, high ownership, and clear communication in English Nice to have Experience in finance (ideally trading), on the systems behind positions, PnL, risk, a

(FEQ427R351) Senior Specialist Solutions Engineer - Platform Security and Cloud Infrastructure As a Senior Specialist Solutions Engineer, you will guide customers in building big data solutions on Databricks that span a large variety of use cases. This is a customer-facing role that works with and supports the Field Engineering pre-sales teams and requires hands-on production experience with cloud infrastructure and big data technologies. Specialist Solutions Engineers help customers through the design and successful implementation of essential workloads while aligning their technical roadmap to expand the use of the Databricks Data Intelligence Platform. As a deep go-to-expert reporting to the Specialist Field Engineering Manager, you will continue to strengthen your technical skills through mentorship, learning, and internal training programs to continuously consolidate the skills in your area of speciality. The impact you will have: Technical thought leader : Provide technical leadership to guide strategic customers to successful implementations on big data projects, ranging from architectural and security design to development and deployment best practices, including automation Assist Solution Architects with more advanced aspects of the technical sale, including custom proof of concept content, workload sizing, and custom architectures Cloud Infra & Security Expertise Architect production-level cloud native governed workloads Provide technical expertise in cloud infrastructure and security relating to our Databricks Lakehouse Platform Community & Adoption : Enable adoption by leading workshops, hackathons, and conference presentations, while actively contributing to the broader Databricks community. What we look for: Pre-sales or post-sales experience working with external customers (or internal clients/stakeholders) across industries 4+ years of experience designing Cloud infrastructure/Security and services, s

This is Adyen Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H&M, and Microsoft - making us the financial technology platform of choice. At Adyen, everything we do is engineered for ambition. For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster. Staff Java Engineer - Merchant Fraud Prevention As a Staff Software Engineer in the Merchant Fraud Prevention group, you will serve as the core architect and strategic engineering partner for our fraud detection and mitigation ecosystems. You will define the long-term technical vision across 2–3 engineering teams, ensuring our Platforms can detect and prevent evolving fraud vectors at scale. Beyond technical leadership, you will be a key force multiplier, acting as a strategic advisor to engineering leadership, bridging the gap between business strategy and execution, and actively mentoring and growing our senior Individual Contributors (ICs). What you'll do Technical Strategic & Architecture: Own the multi-year technical north star vision for the group, together with the technical leads of each team in the group. Design and evolve high-throughput, low-latency distributed systems capable of processing real-time merchant transactions, integrating complex machine learning models, and handling massive big data pipelines. Leadership Partnership: Partner closely with the Director of Engineering to assess organizational health, surface systemic engineering bottlenecks, and align long-term technical investments with Merchant protection goals. Product Strategy: Shape the strategic roadmap alongside the Director of Engineer

This is Adyen Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H&M, and Microsoft - making us the financial technology platform of choice. At Adyen, everything we do is engineered for ambition. For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster. Business Analyst - Payments Pricing As a Business Analyst - Pricing in the Global Payments Pricing team, you'll be central to Adyen's financial performance in global card payments. This role goes beyond traditional pricing - you'll be our team's expert on interchange and scheme fee charges for Card Networks such as Mastercard and Visa in the EMEA region, and ensure the financial stability of Adyen’s transactional cost prediction engine. Your responsibilities include optimizing our fee structure, contributing to reconciliation of costs, improving our processes and tooling, and generating insights that provide a holistic understanding of complex fee dynamics. You will reinforce Adyen’s commitment to fee transparency and reduce our customer’s total cost of payment. As the go-to expert within the Global Payments Pricing team, you’ll work closely together with global teams, including Product, Engineering, Finance, and Partnerships. What You'll Do Ensure merchants are charged the most accurate and optimal cost price for payment transactions, leveraging data and insights to refine fee passthrough predictions. Analyze and identify the necessary data to address questions, extract the required data, and perform analysis. Implement fee change rollouts to maintain our cost infrastructure and manage the merchant experience. Optimize, build

About the Role Together AI runs one of the largest GPU fleets in the world. The Infra Agent Systems team builds the software systems that power and automate that infrastructure. We develop production AI agents that diagnose hardware failures, investigate incidents, correlate signals across the fleet, and automate operational workflows. Alongside these agents, we build the platform they run on, including knowledge graphs, retrieval systems, orchestration frameworks, and developer tooling. You’ll work across two areas: Infrastructure Agent Systems — Build production AI agents that help operate our GPU fleet by diagnosing failures, investigating incidents, gathering evidence from live systems, and assisting with remediation. These agents are used every day by our infrastructure and datacenter teams through APIs, CLI, dashboards, and Slack. Core Agent Platform — Build the platform that powers these agents, including knowledge graphs, search and retrieval, orchestration, evaluation, and the tooling that enables agents to reason, act, and continuously improve. We’re working on something that hasn’t really been done before: building knowledge graphs and self-improving AI agents that understand, operate, and continuously improve large-scale AI infrastructure. This is an opportunity to work at the intersection of AI agents, distributed systems, infrastructure, and automation , solving challenging engineering problems with real production impact. There’s an enormous amount to build, learn, and shape as we define the future of autonomous infrastructure. responsible for delivering the software but also for operating and supporting it in production. Why this Role You’ll work on two hard problems at the same time: making AI agents trustworthy enough to operate production infrastructure, and building the knowledge, retrieval, and distributed systems that make those agents effective. You’ll have the opportunity to build foundational systems from the ground up, work on infrastructur

Altana is the network for trusted trade. Our AI-powered product network empowers governments and businesses to build a more resilient and secure global economy while keeping trade flowing. The Opportunity at Altana The AI Deployment team is the tip of the spear in getting Altana's platform into production inside our customers' businesses. We own the path from signed contract to realized value: standing up integrations, deploying agentic AI into the customer's existing business processes, and making sure the insight we deliver actually changes decisions on the customer's side. We are a delivery organization with a technical core. We work directly with customer stakeholders — from trade compliance analysts to enterprise IT — and we work just as closely with Altana's engineering, data science, and product teams to translate what we learn in the field into what gets built next. This role leads that team. You Will Lead and grow a team of AI Deployment Engineers Hire, coach, and grow a team of AI Deployment Engineers — set expectations, give direct feedback, and develop careers Own team capacity and staffing across a portfolio of customer implementations, matching engineers to accounts by skill, delivery risk, and development goals Establish the team’s operating rhythm — planning, reviews, and retrospectives that keep multiple implementations on track at once Build a culture of ownership, technical rigor, and adoption-focused delivery, where “done” means the customer is using it in their process, without us in the room Create the conditions for the team to move fast safely: shared playbooks, reusable tooling, and clear standards for deploying agentic systems in production Own the mission across your portfolio Own delivery outcomes across every account your team touches: agentic AI in production, adoption, and changing decisions on the customer's side Set and defend the roadmap across implementations — sequencing by customer value and delivery risk, and making explicit cal

About Us At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. About the Role We’re looking for an experienced Account Executive to join our growing GTM team and drive the next wave of growth at LangChain. In this role, you’ll own the full sales cycle helping technical teams at cutting-edge enterprise companies discover, evaluate, and adopt LangChain’s products. This is a high-impact, high-visibility role where you’ll collaborate closely with engineering, product, and customer success teams to shape how GenAI is adopted across different domains. If you're a relationship-driven seller who thrives in fast-paced, unstructured environments and wants to be part of building the go-to-market motion from the ground up, we’d love to hear from you

(FEQ128R2) The Role As a Specialist Solutions Architect (SSA) – Data Engineering, you are a hands-on technical authority who guides strategic customers in designing, building, and optimizing production-grade data workloads on the Databricks Data Intelligence Platform. Partnering closely with Account Teams and Solution Architects, you translate complex big data challenges into high-performance, scalable architectures using Apache Spark™ and modern streaming frameworks. In this role, you will drive successful implementations, align technical roadmaps to accelerate platform adoption, and establish deep domain specialization; whether in real-time streaming, performance optimization, or operational data layers, while expanding your impact across Field Engineering. The impact you will have: Drive Technical Wins & Scope: Lead end-to-end technical design, proof of concepts (PoCs), and workload sizing for strategic customer engagements, acting as a trusted advisor to front-line technical stakeholders to secure technical wins. Architect Production Data Systems: Design, build, and optimize scalable, high-performance batch and streaming pipelines, operational data layers (Lakebase), and end-to-end performance load testing on Databricks. Deploy Interactive Data Applications: Build and operationalize custom user-facing data applications using Databricks Apps, transforming data pipelines and AI models into interactive tools. AI-Native Engineering: Leverage AI coding assistants, LLMs, and agentic workflows (e.g., Genie Code, Cursor) as a force multiplier to rapidly prototype, debug, and deliver architectural assets with full ownership of outputs. Enablement & Domain Leadership: Mentor peers, contribute reusable architecture assets, and deliver technical workshops and community presentations to scale expertise across accounts and field teams. What we look for: Deep Data Engineering Expertise: 5+ years in data or software engineering with hands-on proficiency in distrib

About Us At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. About the Role: We're looking for a Deployed Architect to join our Professional Services team. You'll work directly with enterprise customers to design, deploy, and optimize production-grade AI infrastructure and agent systems. You'll be responsible for architecting scalable, secure infrastructure deployments and building reliable, well-evaluated agent applications that solve real business problems. This role combines software development, infrastructure/platform engineering, and customer-facing skills. You'll work on everything from Kubernetes cluster design to multi-agent system architecture, requiring deep technical expertise across both infrastructure and agent engineerin

About the Role Lead a team of AI Infra (Systems Engineers) at Together based out of our office in Amsterdam, you and the SRE team are responsible for keeping all user-facing services and production systems running smoothly. You are a blend of a pragmatic operator and a software engineer that applies sound engineering principles, operational discipline, and mature automation to our operating environments and codebase. You specialize in systems (operating systems, storage subsystems, networking), while implementing best practices for availability, reliability and scalability, with varied interests in algorithms and distributed systems. Responsibilities Be on an on-call (PagerDuty) rotation to respond to incidents that impact availability Manage, develop and coach the SRE Team. Build and run our infrastructure with Ansible, Terraform, and Kubernetes to enable scaling to a massive number of concurrent users Build monitoring systems to ensure the highest quality service for our customers Design and implement operational processes (such as deployments and upgrades) Debug production issues across all services and levels of the stack Identify improvements for the product architecture from the reliability, performance and availability perspectives Plan the growth of Together AI’s infrastructure Requirements 7+ years of professional SRE or related experience Ideally 2 years as a Lead SRE Bachelor's degree in Computer Science or a related field or equivalent work experience Expert knowledge of Ansible (roles, playbooks), Terraform, and Kubernetes Proficiency in programming/scripting languages Direct experience in monitoring and observability practices Advanced knowledge of cloud services Ability to thrive in a collaborative environment involving different stakeholders and subject matter experts About Together AI Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tu

About the Role Together AI is looking for a Senior Network Engineer to design, deploy, and operate the global network infrastructure supporting our production services and high-performance AI compute environments. This is a hands-on engineering role for someone with deep networking expertise who can also troubleshoot across Linux, Kubernetes, automation, and application boundaries. You will work on large-scale, multi-vendor data center networks and help ensure they remain highly available, reliable, scalable, and performant. The ideal candidate has strong networking fundamentals, experience operating complex networks at scale, and a structured, evidence-based approach to troubleshooting. You should be comfortable owning problems from initial investigation through root cause and resolution, including situations where the issue may extend beyond the network itself. Requirements 8+ years of professional experience designing, building, and supporting large-scale production data center, cloud, service-provider, or high-performance computing networks (excluding enterprise networks). Deep understanding of TCP/IP and strong experience with technologies such as BGP, OSPF, VXLAN, EVPN, ECMP, and QoS. Experience designing and supporting multi-tenant network environments using technologies such as VRFs, VLANs, overlays, and policy-based segmentation. Hands-on experience deploying and troubleshooting network platforms from vendors such as Arista, Cisco, Juniper, and NVIDIA. Strong troubleshooting skills using tools such as Wireshark, tcpdump, MTR, curl, nmap, and standard Linux networking utilities. Ability to diagnose connectivity, latency, packet-loss, routing, and performance issues across the network, host, and application layers. Experience developing or maintaining network automation using Python, Ansible, or similar tools. Experience working through a Git-based software development lifecycle, including branching, code review, validation, linting, testing, CI/CD, de

At Graviton, every strategy, model and edge begins not with instinct, but with someone asking a better question than everyone else. As a Quantitative Research Intern, you'll spend 10-12 weeks working on research that directly shapes how we understand markets and build trading strategies. You'll collaborate with researchers and technologists to investigate market behaviour, test hypotheses, build predictive models and solve problems where the answers aren't obvious. This isn't an internship where you observe from the sidelines. Outstanding work has the potential to shape production strategies and generate real, measurable returns. Ideal candidates are quantitatively sharp, practically minded problem solvers, programmers, mathematicians and scientists who are excited to solve the hardest problems in our field, across our offices in the US, Singapore, Amsterdam and London. What You'll Work On You'll work on real research problems, not simulated exercises, discovering predictive patterns from billions of market events, designing statistical models, and applying machine learning to open research problems. Your work would include: Discovering predictive patterns from billions of market events Designing statistical models that identify trading opportunities Applying probability, optimization and machine learning to open research problems Building AI-powered research agents that accelerate experimentation Developing infrastructure for rapid, large-scale research Designing experiments and backtests to evaluate hypotheses Translating research into production-ready trading signals Exploring new ML, AI and quant finance techniques to find the next source of alpha What You'll Learn Beyond the technical exposure, you'll learn how experienced researchers approach hard problems: breaking them down, questioning assumptions, and deciding based on evidence rather than intuition. You'll be paired with a mentor, reporting manager and buddy, with regular code reviews and feedback through

At Graviton, every strategy, model and edge begins not with instinct, but with someone asking a better question than everyone else. As a PhD Quantitative Research Intern, you'll spend 10-12 weeks pointing the research skills you've spent years building at markets. You'll collaborate with researchers and technologists to investigate market behaviour, test hypotheses, build predictive models and solve problems where the answers aren't obvious. This isn't an internship where you observe from the sidelines, or re-run someone else's experiment. Outstanding work has the potential to shape production strategies and generate real, measurable returns. Ideal candidates are researchers who want to see their methods meet live markets: mathematicians, physicists, statisticians and computer scientists who are excited to solve the hardest problems in our field, across our offices in the US, Singapore, Amsterdam and London. What You'll Work On You'll work on real research problems, not simulated exercises. Your work would include: Discovering predictive patterns from billions of market events Designing statistical models that identify trading opportunities Applying probability, optimization and machine learning to open research problems Running large-scale simulations and experiments on high-performance research infrastructure Designing experiments and backtests to evaluate hypotheses Building AI-powered research agents that accelerate experimentation Developing infrastructure for rapid, large-scale research Translating research into production-ready trading signals Exploring new ML, AI and quant finance techniques to find the next source of alpha What You'll Learn Beyond the technical exposure, you'll learn what changes when research meets live markets: why a result that would survive peer review can still fail as a trading signal, how costs and capacity constrain an idea that looks clean on paper, and how to tell a model that is right from one that is right for the wrong reason.

Req ID: FEQ327R410 The Role As a Solutions Architect in the Benelux Strategic Accounts team, you will play a lead role in driving the technical strategy for your customers — owning architecture discussions, driving platform adoption, and serving as a trusted advisor to customer technical leads and architects. You combine deep technical expertise with strategic thinking to position Databricks as the foundation of your customers’ data and AI strategy. You are developing a technical specialisation (archetype) and are recognised within your team for depth in a specific domain. The Impact You Will Have Own the end-to-end technical strategy with customer accounts, from initial discovery through production deployment and consumption growth Lead complex architecture discussions — designing scalable, production-grade solutions spanning data engineering, ML/AI, and real-time analytics Serve as a trusted technical advisor to customer architects, engineering leads, and Directors Drive technical wins in competitive scenarios by demonstrating Databricks’ differentiation through custom-built solutions Develop and declare an emerging technical specialisation (archetype) — becoming a go-to resource for your team in that domain Orchestrate cross-functional resources (Delivery, Specialist & Partner Solution Architects) to deliver comprehensive solutions for complex customer needs Influence product direction by providing structured feedback on customer requirements and competitive gaps What We Look For 6+ years in solutions architecture, data engineering, technical pre-sales and/or a senior hands-on technical role Strong coding proficiency in Python and SQL — you must demonstrate live coding, debugging, and solution-building skills Deep expertise in distributed data systems architecture: designing scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms Proficient on the Databricks Platform (or demonstrated ability to achieve proficiency rapi

Req ID: FEQ327R409 The team The Fungible team is the “rapid-response squad” within the Field Engineering organisation that engages with customers on the most strategic, highest-potential opportunities across Benelux and the Nordics to accelerate critical use cases, land technical wins, and drive successful Databricks adoption. If you enjoy working on novel use cases across a variety of industries on highly visible engagements, this is the right home for you! The role As a Fungible Solutions Architect, you lead the technical strategy on time-boxed, targeted engagements - typically one to five months - aimed at accelerating a specific set of critical customer workloads from evaluation to a production-grade technical win. You own the architecture conversation, drive platform adoption, and act as a trusted advisor to customer architects and engineering leaders, then transition the momentum you've built to the core account team. You bring technical depth and the judgment to apply it fast, in situations that require strong ownership and are highly visible . Where a specialisation helps you contribute quickly, great — but on this team, breadth, adaptability, and a bias for impact matter just as much as your area of depth. The impact you will have Accelerate what matters most: parachute into strategic, high-profile opportunities and own a clearly defined technical area, moving critical workloads and use cases from evaluation toward production and consumption. Lead the architecture: design scalable, production-grade solutions across data engineering, ML/AI, and real-time analytics, and lead the whiteboarding, design reviews, and trade-off decisions with senior customer stakeholders. Win the technical decision : demonstrate Databricks' differentiation through custom-built solutions in competitive, must-win scenarios. Move fast while maintaining the bar: establish momentum quickly in ambiguous situations and compress timelines without cutting corners. Hand off, don't hold on :