Infrastructure Support Engineer in Amsterdam

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 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

Responsibilities: Build and cultivate lasting, meaningful relationships with the Talkdesk channel partner community, including SaaS SIs, telecom master agents, VARs, and other consultants / resellers Focus 70% of your efforts on driving growth with current partners (Telecom, Reseller, GSI, SI, BPO) and 30% on expanding our footprint through new partner recruitment. Meet and exceed pipeline quota through the management and execution of the Talkdesk sales process via partner referrals Understand and internalize the Talkdesk vision, solution set, product roadmap, and go-to-market activities and effectively communicate these to partner constituents Collaborate with our Sales, Marketing and Customer teams to generate channel pipeline and partner / customer satisfaction Conduct web-based demos and develop materials necessary to accelerate partner and customer acquisition Provide feedback to the product team concerning partners’ requests for product enhancements Use Salesforce.com to maintain excellent records and report on Channel activity and metrics Recommend Talkdesk partner infrastructure improvements (e.g., partner portal, marketing collateral) as partner needs dictate Requirements : BA/BS degree required; MBA is appreciated 3-5 years of experience in channel sales 3+ years experience working in the SaaS or telecom industry Fluency in Dutch is required Creative and passionate about partnering; exceptional ability to develop relationships Engaged personality, polished verbal and written communication skills and meticulous attention to detail “Hunter” mindset with the ability to generate partner referral opportunities while also developing longer term partner relationships Highly organized self-starter who runs toward opportunities Proficient with web-based demo software and tools Comfortable operating in a fast-paced, dynamic startup environment Willingness to travel (70%) as needed Talkdesk is pioneering a new era of Customer Experience Automation (CXA), redefi

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

(FEQ427R544) Role Summary As a Field Engineering Manager, you will lead a high-performing team of technical pre-sales Solutions Architects (SAs) dedicated to enterprise Named Accounts across the Benelux region. You will operate at the intersection of deep technology and business strategy, driving platform adoption and enterprise AI initiatives. As a technically credible coach and AI builder , you will spend meaningful time in the field (~30-40%) partnering with customer executives and internal Sales counterparts. You will lead by example to instil an AI-Builder Mindset across your team, establish rigorous operational inspection cadences, coach SAs through complex architecture designs without taking the pen, and decisively build an elite pre-sales organisation. The Impact You Will Have Build & Scale Elite Teams: Hire, mentor, and retain exceptional Solutions Engineers/Architects in the Benelux region, establishing high standards for technical excellence, inclusive leadership, and decisive performance management. Drive AI Adoption & Capabilities: Lead by example as an AI practitioner, embedding AI tools into team workflows and driving scalable capability across the organisation. Act as a Customer Advisor: Build trusted relationships with C-level and senior technical executives across customer accounts. Translate complex platform capabilities into measurable business ROI (e.g., predictive maintenance, yield optimisation, supply chain resilience). Drive Operational Execution: Co-own regional consumption and growth targets with Sales partners. Maintain rigorous inspection cadences across pipeline health, technical validation, and account strategy. Technically Coach the Field: Serve as an architectural sounding board for your team. Diagnose platform designs, spot failure modes in distributed systems or AI infrastructure, and coach SAs to refine architectures independently. Expand Benelux Presence: Serve as a key regional leader helping build Databricks' brand and

About BlockTech BlockTech is a fast-paced algorithmic trading firm trading crypto derivatives and spot across global venues, 24/7, with our own capital. Crypto is one of the few markets where a researcher can still move the edge. The data is abundant, the microstructure is novel, and the loop between an idea and live PnL is short. High-frequency options trading is where we're strongest, and we're widening our scope to include more mid-frequency work. We're looking for a senior Quantitative Researcher with a mid-frequency background to join our Amsterdam trading floor. The role You'll be in charge of developing our mid-frequency capabilities, owning the research agenda end to end, from hypothesis and dataset construction through model training and backtesting to live deployment. You'll sit with traders, researchers, and analysts, and raise the bar for research across the floor. You will: Own price-prediction, signal, execution, and anomaly-detection models across crypto derivatives and spot markets from idea to live PnL Shape our research, backtesting, and trading infrastructure together with engineers, so good ideas reach production quickly and safely Own models in production: monitor live performance, diagnose decay, and iterate on what you ship Set research direction alongside traders, deciding which trades are worth making and why Raise the research bar by mentoring colleagues, reviewing work, and setting standards for rigour What we're looking for 3+ years of quantitative research experience at a hedge fund, trading firm, or similar, with mid-frequency models you've taken live A strong academic foundation in a quantitative discipline (mathematics, physics, statistics, or computer science) Fluency in Python and the modern ML stack (PyTorch and/or TensorFlow, scikit-learn, NumPy, pandas) A deep grasp of overfitting, validation design, and feature engineering. You can explain why a model works, not just that it does Software engineering instincts: you write product