Infrastructure Solutions Architect in Amsterdam

P-1325 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. Modern data analysis employs sophisticated methods such as machine learning that go well beyond the roll-up and drill-down capabilities of traditional SQL query engines and require speed and reliability. As a software engineer on the Storage and IO team at Databricks, you will be building the next generation of our cloud storage I/O platform supporting fast and reliable reads and writes against cloud storage systems. This specialized and highly optimized platform boosts the performance and reliability of the query processing system so it can outperform even specialized query engines. What we look for: BS (or higher) in Computer Science, related technical field or equivalent practical experience. Comfortable working towards a multi-year vision with incremental deliverables. Motivated by delivering customer value and impact. 8+ years of production level experience in either Java, Scala or C++. Experience with low level systems (OS, network stacks, CPU optimizations). Strong foundation in algorithms and data structures and their real-world use cases. Experience with distributed systems, databases, and big data systems (Apache Spark, Hadoop). About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70%

P-1125 Summary At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high-value challenges that are central to their missions. Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security, and scale that is critical to making customers successful on our platform. Customers trust Databricks with their most valuable data and Trust & Safety has the mission to build the most trusted data analytics and ML platform in the world. Security Engineering is an integral part of Trust & Safety and has a critical role to play in keeping customer data from bad actors. We are looking for senior leaders such as yourselves to create the vision and define the strategy for this space. The impact you will have: Make Databricks safer for our customers by identifying and plugging key gaps in our infrastructure and services Attract top talent from across the industry. Represent the security engineering discipline throughout the organization, having a powerful voice to make us more data-driven Represent Databricks at academic and industry conferences & events What we look for: 9+ years of experience in Data Security or related areas and expertise in two or more of the following--Cryptography, Kubernetes Security, Web Security, Governance, Privacy, Trust, Safety, Authentication, Identity Management, Access Control, Key Management, Inter-Service Authentication, Secure Application Frameworks, Detection & Response. Experience building systems at large scale internet companies is a huge plus. 15+ years of experience building large scale distributed systems with high availability Le

P-969 At Databricks, we are passionate about helping data teams solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. As a Software Engineering Intern, you will join a team of engineers to build features that contribute directly to the Databricks platform. We're hiring across all of our teams, including full stack, backend, infrastructure, systems, tools, cloud, databases, and customer-facing products. You will have a dedicated mentor and will join our 2027 intern cohort where you'll connect with engineers, other interns, and leaders from across the company. We are hiring Software Engineering Interns across multiple offices. Please apply for the single location that you're the most interested in, and we will discuss more with you as you move through the process. We can only consider one application in 30 days. The impact you will have: Work with a team to build features for the Databricks platform Manage your project end-to-end, including design, code, and feedback Learn about building a platform that scales quickly while maintaining quality and security What we look for: You will graduate between fall 2027 and Summer 2028 with a degree in Computer Science, Engineering, or related subject You have implementation skills with a general purpose program language, such as Python, Java, or C++ You have good knowledge of algorithms, data structures, and OOP principles You are excited to solve ambiguous problems with a collaborative team This is a Summer 12-week internship. Co-ops are only available to students enrolled in a co-op program. About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of

Ready to Get Shit Done? At bunq, we're building a bank that lives in the cloud, handles billions of transactions, and now integrates AI into our operations—all while keeping our user's data and trust intact. To operate at this scale and speed without compromising security, we need an Internal Auditor focused on Data Security & AI to audit our security controls, validate our AI governance, and ensure every system we build is resilient and trustworthy. As an Internal Auditor – Data Security & AI, your mission is to strengthen bunq's security and AI governance posture by auditing data protection controls, assessing AI model risks, identifying vulnerabilities before attackers do, and ensuring our security practices evolve as fast as our technology. Take Ownership As an Internal Auditor - Data Security & AI, you'll own: Audit security controls across infrastructure, applications, and operations, assessing access controls, encryption, monitoring, incident response, and third-party security effectiveness. Build an AI governance audit program that evaluates model development, bias testing, monitoring, transparency, and regulatory alignment (AI Act, NIS2). Identify and prioritize security and AI risks, conducting vulnerability assessments, pen test reviews, and model audits to surface gaps before they're exploitable. What You'll Work on Right Away Security Control Assessment: Audit bunq's critical security infrastructure (cloud environment, API security, data encryption, access management) and validate the effectiveness of controls; deliver a risk-prioritized remediation roadmap. AI Model Governance Program: Design and execute bunq's first AI audit program, evaluating model development practices, data quality controls, bias testing, monitoring, and transparency, identifying governance gaps and building a scalable AI audit framework. Data Protection & Privacy Audit: Conduct a comprehensive audit of bunq's data handling practices across all systems, assessing compliance with G

Ready to Get Shit Done? At bunq, we're not just building a banking app, we are reshaping how people experience financial freedom globally. To sustain that mission while protecting our users and our business, we need an Internal Auditor focused on Regulatory Compliance to ensure we meet every regulatory requirement, manage compliance risks, and keep our operations audit-ready at all times. As an Internal Auditor - Regulatory Compliance, your mission is to safeguard bunq's regulatory standing by identifying and mitigating compliance gaps, ensuring adherence to evolving regulations across all markets we operate in, and building the audit infrastructure that keeps our business resilient. Take Ownership As an Internal Auditor - Regulatory Compliance, you will own: Conduct compliance audits across all business lines (AML, KYC, data protection, market conduct) and identify gaps with concrete remediation recommendations. Build and execute the audit roadmap, prioritizing high-risk regulatory domains and ensuring systematic coverage across our markets. Drive remediation tracking with business teams, ensuring findings are addressed and root causes fixed, not just symptoms. What You'll Work on Right Away Compliance Audit Program: Design and execute the first multi-domain compliance audit program, covering AML/KYC, data protection, market conduct, and operational risk, delivering findings and a forward remediation roadmap. High-Risk Compliance Assessment: Conduct a deep-dive audit into bunq's highest-risk regulatory areas (likely payment services directives, data governance, or market-specific regulations depending on your markets), identifying systemic gaps and building a remediation plan. Regulatory Change Impact Assessment: Analyze recently enacted or upcoming regulations across our markets and assess operational readiness, working with stakeholders to ensure bunq remains compliant before enforcement deadlines. Do You Have What It Takes? Regulatory audit expertise: Proven exp

At bunq , users trust us with their money across 30+ countries, and that trust is only worth something if the legal framework behind it is airtight, proactive, and scales as fast as we do. We're heading towards our North Star and entering new markets, that doesn't happen without someone owning the legal infrastructure behind it: the strategy, the team, the AI-first operating model, and the accountability that makes all of it run without the Head of Legal in the loop every day. Take Ownership. As our Head of Trust & Transparency, you will: Be the layer between legal strategy and the team that executes it , translating quarterly priorities into clear ownership, running the accountability cycle, and making sure only real decisions reach the Head of Legal. Take bunq's AI tooling for contract review, T&C management, and regulatory monitoring to the next level , building an operating model that handles 5x the volume without 5x the headcount. Give the business a clear, honest picture of T&T health across the pillar, so risks get caught early, quality stays high, and the function scales as fast as bunq does. You are a qualified lawyer with a Master's degree in Law and a strong background in financial services. You've independently run a compliance or legal function across multiple jurisdictions, not just supported one. You've had direct dialogue with regulators and know how to represent a legal position without a script. You've managed a small specialist legal team, set their KPIs, and held them to it. You can challenge senior leadership with data and translate complex regulatory risk into something a decision-maker can act on in two minutes. You design AI systems, not just use them, you've eliminated manual legal work at scale and built workflows others now rely on. You know the difference between work that's on time and work that's good, and you've built the frameworks that make that distinction measurable. You make judgment calls on what gets automated, what stays human,

At bunq, we're on a mission to Make Life Easy for our users by creating the most user-centric banking experience out there. To deliver on that promise, our services must be reliable 100% of the time. That's where you come in. We're looking for a Technology Risk Officer who takes ownership of making sure our ICT infrastructure can withstand and recover from disruption. As second line of defense, you'll test whether our controls actually work, not just whether they exist on paper, so weaknesses are found before they become incidents, protecting user's trust and letting bunq scale without operational risk growing alongside it. Take Ownership 🚀 As a Technology Risk Officer, you'll show bunq's excellence both inside and out by keeping our critical systems resilient and our controls effective. This role is yours to own, we'll show you the tools and the end goal, but how you get there is up to you. Here's how you'll do it: Continuously test and challenge bunq's ICT infrastructure to surface weaknesses before they affect our users, going beyond "are we compliant" to verify controls actually work, and use AI to automate testing, monitoring, and evidence collection at scale. When something goes wrong, dig into what really happened in the engineering process, interpret results to separate meaningful risk from noise, and prioritize remediation accordingly. Lead business continuity and disaster recovery testing, designing realistic drills for technology, business processes, and critical suppliers. Coordinate across technical and business teams, challenging control owners and driving weaknesses through to resolution, this role is yours to own end to end. You have deep knowledge of operational and ICT resilience, and you think like an engineer, you want to understand what actually happened in a system, not just whether a checkbox was ticked. You have proven skills in automated control testing and monitoring, and can design continuous tests and alerts that catch control failures e

About BlockTech BlockTech is a fast-paced algorithmic trading firm facilitating global cryptocurrency derivatives and spot trading while expanding into new markets. As we continue to grow rapidly, we are looking for a Software Engineer to join our Foundation team amid our exciting scale-up phase! You will Build & optimize: Design, develop, and maintain high-reliability, low-latency, and high-throughput foundational systems that enable our trading and technology teams to scale efficiently. Ingest & aggregate: Collect trading business data with minimal latency impact and ingest both public and private exchange information into our trading system. Store & stream: Develop and maintain infrastructure for real-time data aggregation and long-term storage, as well as our Kafka-based messaging systems. Collaborate & support: Work closely with multiple teams, assisting them in integrating with and making the most of our foundational systems. Innovate: Drive projects from concept to deployment with full ownership, and explore new tools, frameworks, and approaches to keep our infrastructure best-in-class. The Foundation team develops core software infrastructure (libraries, frameworks, and systems) for BlockTech, solving common problems and lending its expertise to enable other teams to stay focused on their respective domains. They own, develop, and configure a wide variety of critical, high-reliability software, ranging from low-level ultra-low-latency shared memory IPC libraries to high-throughput data buses and data aggregation systems including Kafka, NATS, PostgreSQL, and Iceberg. They work primarily in Rust, but also use Python and SQL. If you thrive on low-level problem-solving, building robust frameworks from scratch, and enabling others to move faster, this role is for you. What We're Looking For Essential: 5+ years of experience as a Software Engineer, with a strong focus on systems-level optimisation and awareness of hardware constraints Proficiency

About BlockTech BlockTech is an algorithmic trading firm operating at the frontier of global crypto derivatives and spot markets. We trade 24/7 across some of the fastest-moving, most data-rich venues in finance. Crypto is one of the few markets where the gap between a good model and live PnL comes down to how fast and how reliably you can ship it. Abundant data, novel microstructure, and a short path to production mean the quality of our infrastructure directly moves the edge. We're looking for a Quantitative Developer to build that infrastructure and get our models into production. The role This is a hands-on engineering seat on our trading floor. You'll own the infrastructure that turns research models into production trading systems, working primarily in Python and Rust, the language our models and systems are written in. You'll build the frameworks and tooling that let quants ship their code to production and keep those systems running once they're live. You'll work shoulder-to-shoulder with researchers, traders, and fellow engineers, building the tooling, pipelines, and standards that let good ideas reach production quickly and safely, and helping raise the engineering bar across the floor. You will Build and own the infrastructure that takes models from research to production - data pipelines, backtesting, deployment, and monitoring. Turn research prototypes into robust, performant, production-grade code that runs reliably in live trading Work closely with quantitative researchers and traders to get new models live quickly and safely Own the systems you ship in production: monitor performance, diagnose issues, and keep latency and reliability high Improve the tools, standards, and pipelines the team relies on, raising the engineering bar across the floor What we're looking for 2+ years of software engineering experience, with a track record of shipping production-grade systems A strong academic foundation in a STEM discipline (computer science, mathematics, p

About BlockTech BlockTech is an algorithmic trading firm operating at the frontier of global crypto derivatives and spot markets. We trade 24/7 across some of the fastest-moving, most data-rich venues in finance. Crypto is one of the few markets where the gap between a good model and live PnL comes down to how fast and how reliably you can ship it. Abundant data, novel microstructure, and a short path to production mean the quality of our infrastructure directly moves the edge. We're looking for a Quantitative Developer to build that infrastructure and get our models into production. The role This is a hands-on engineering seat on our trading floor. You'll own the infrastructure that turns research models into production trading systems, working primarily in Python and Rust, the language our models and systems are written in. You'll build the frameworks and tooling that let quants ship their code to production and keep those systems running once they're live. You'll work shoulder-to-shoulder with researchers, traders, and fellow engineers, building the tooling, pipelines, and standards that let good ideas reach production quickly and safely, and helping raise the engineering bar across the floor. You will Build and own the infrastructure that takes models from research to production - data pipelines, backtesting, deployment, and monitoring. Turn research prototypes into robust, performant, production-grade code that runs reliably in live trading Work closely with quantitative researchers and traders to get new models live quickly and safely Own the systems you ship in production: monitor performance, diagnose issues, and keep latency and reliability high Improve the tools, standards, and pipelines the team relies on, raising the engineering bar across the floor What we're looking for 2+ years of software engineering experience, with a track record of shipping production-grade systems A strong academic foundation in a STEM discipline (computer science, mathematics, p

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

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.

At Graviton, we don't believe the best trading strategies come from following established playbooks. They come from asking better questions. Why does a pattern exist? What is driving it? Is it real or just noise? Can it be explained, modelled and turned into an edge? As a Quantitative Researcher, you'll work on those questions every day. You'll investigate market behaviour, develop quantitative models, build and test hypotheses and turn insights into trading strategies, working alongside researchers and technologists in an environment where an idea on a whiteboard can reach live trading quickly. This isn't a role where the answers are in a textbook. The problems are open-ended, the data is enormous, and finding the answers is the job. Ideal candidates are rigorous thinkers who genuinely enjoy mathematics, programming and figuring out things that aren't obvious, based in our Singapore, London, Amsterdam or US offices. What You'll Work On You'll work across quantitative research and systematic trading, taking ideas through the full lifecycle: question, hypothesis, experiment, model, validation, strategy, production. Depending on your team and research interests, your work would include: Discovering predictive patterns and sources of alpha from billions of market events Formulating hypotheses about market behaviour and designing experiments to test them Applying probability, statistics, optimization and machine learning to build predictive models and quantitative signals for systematic trading Designing robust backtests and statistical tests to distinguish genuine signals from noise Working with large and complex datasets to uncover patterns that aren't immediately visible Investigating market microstructure and how markets behave at different timescales Evaluating strategy performance, identifying weaknesses and continuously refining models Developing research infrastructure and AI-powered tools and agents that make experimentation faster and analysis deeper Working c

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