Cloud Platform Engineering Jobs

MongoDB is bolstering its hiring, focusing on creating tools that guide customers in transitioning their applications from relational databases to MongoDB. As businesses evolve their application development frameworks, they're increasingly drawn to the versatility of the document model. The Relational Migrator team, already instrumental in this area, aids developers in making the shift from relational databases to MongoDB. Now, they're broadening their toolkit and are keen on refining code using a mix of AI and traditional text processing. MongoDB is seeking a Software Engineer with solid software engineering skills and a machine learning background. Joining this team, you'll be pivotal in a product engineering group dedicated to helping users navigate code conversion challenges with AI's support. This role will be based out of North America in the PST and MST zones only. The ideal candidate for this role will have 2+ years of professional software development experience in Java or another programming language Experience with generative AI and specifically LLMs is highly desirable Experience with text processing engines such as ANTLR is highly desirable Strong understanding of software engineering, system design, data engineering and/or cloud architecture Have experience with compiler design, code parsing or related areas Familiarity with concepts like abstract syntax trees (AST), lexical analysis, and syntax analysis Curiosity, a positive attitude, and a drive to continue learning Actively engages in emerging trends and research relevant to product features Excellent verbal and written communication skills Position Expectations Collaborate with stakeholders to define and implement a code modernisation strategy, ensuring that transformed code aligns with modern software practices while preserving original functionality Develop and maintain a robust code parser to accurately interpret legacy code structures, converting them into a standardised format like an abstract

MongoDB is bolstering its hiring, focusing on creating tools that guide customers in transitioning their applications from relational databases to MongoDB. As businesses evolve their application development frameworks, they're increasingly drawn to the versatility of the document model. The Relational Migrator team, already instrumental in this area, aids developers in making the shift from relational databases to MongoDB. Now, they're broadening their toolkit and are keen on refining code using a mix of AI and traditional text processing. MongoDB is seeking a Software Engineer with solid software engineering skills and a machine learning background. Joining this team, you'll be pivotal in a product engineering group dedicated to helping users navigate code conversion challenges with AI's support. This role will be based out of North America in the PST and MST zones only. The ideal candidate for this role will have 2+ years of professional software development experience in Java or another programming language Experience with generative AI and specifically LLMs is highly desirable Experience with text processing engines such as ANTLR is highly desirable Strong understanding of software engineering, system design, data engineering and/or cloud architecture Have experience with compiler design, code parsing or related areas Familiarity with concepts like abstract syntax trees (AST), lexical analysis, and syntax analysis Curiosity, a positive attitude, and a drive to continue learning Actively engages in emerging trends and research relevant to product features Excellent verbal and written communication skills Position Expectations Collaborate with stakeholders to define and implement a code modernisation strategy, ensuring that transformed code aligns with modern software practices while preserving original functionality Develop and maintain a robust code parser to accurately interpret legacy code structures, converting them into a standardised format like an abstract

As a Manager, Commercial Sales, you will provide strategy, mentorship, and guidance for a team of Commercial Account Executives. This role impacts one of the largest lines of business in the company, ultimately bringing a proven product to a multi-billion dollar market. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Motivate your team to exceed objectives Develop and maintain accurate team forecasts Hire, oversee, and train a team of Account Executives Drive lead generation, high activity standards, and pipeline management Facilitate the ramp up for all new team members, coaching them to success Monitor the sales funnel from prospect to close and create metrics to improve performance Who You Are: Experienced in hi-tech direct sales Familiar with SaaS/Cloud and Salesforce Able to accurately forecast team performance Passionate about coaching, mentorship, and team management Motivated by helping people grow with a desire to continue learning A self-starter who thrives in a high-growth, rapidly changing marketplace Proven in overseeing an outbound sales team in all areas of the sales cycle Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your experience, we encourage you to apply. Benefits and Growth: High income earning opportunities based on performance Opportunity for Presidents Club New hire stock equity (RSU) and employee stock purchase plan (ESPP) Continuous professional development, product training, and career pathing Sales training in MEDDIC and Command of the Message Intra-departmental mentor and buddy program for in-house networking An inclusive company culture, opportu

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role The Security Engineering team's mission is to safeguard our AI systems and maintain the trust of our users and society at large. Whether we're developing critical security infrastructure, building secure development practices, or partnering with our research and product teams, we are committed to operating as a world-class security organization and keeping the safety and trust of our users at the forefront of everything we do. Responsibilities: Build security for large-scale AI clusters across multiple clouds and bare-metal data centers, including IAM, network segmentation and encryption controls Design and implement network security controls: default-deny ingress and egress, segmentation between research, training and production environments, private connectivity across clouds and data centers, cloud firewall policy and mTLS with service identity Ship these controls as secure defaults using infrastructure as code and GitOps workflows, so new clusters, VPCs and data center links inherit the right boundaries Build visibility into network traffic and boundary drift, with detection for exfiltration paths and automated remediation where it is safe to do so Design secure-by-design development workflows and CI/CD pipelines across our services, with expertise in Kubernetes security, container orchestration and identity management Threat model and assess risk for complex multi cloud and networked environments, and join infrastructure networking, cluster and data center teams at design time so topology, routing and firewall decisions carry our security requirements from day one Mentor engineers and contribute to hiring and growt

Why RoboForce RoboForce is an AI robotics company developing Physical AI–powered Robo-Labor for dull, dirty, and dangerous work. The company's robots are engineered for demanding industrial environments, with a focus on real-world deployment and scalability. We are looking for a Senior / Staff AI Research Engineer, Data Infrastructure to build the data and learning engine behind RoboForce's Physical AI stack. In this role, you will own the full pipeline — from raw teleoperation and UMI device data collection through curation, annotation, and storage, to post-training infrastructure that scores demonstrations, identifies failure patterns, and closes the loop back into model retraining. Responsibilities Design and maintain end-to-end data collection pipelines ingesting multimodal demonstration data from teleoperation devices and UMI hardware, including synchronization, versioning, and distributed storage at scale. Build annotation tooling and data curation workflows — quality filtering, deduplication, episode scoring, and domain reweighting — to produce high-quality training datasets for robot policy learning. Develop post-SFT reinforcement learning infrastructure: implement reward scoring on demonstrations, mine and categorize failure patterns, and feed curated failure data back into the retraining loop. Build evaluation and test infrastructure to log policy rollouts on-robot, capture structured results, and surface actionable diagnostics for the research team. Collaborate with ML researchers to define data schemas, episode formats, and pipeline interfaces that support rapid iteration on VLA and manipulation policy training. Architect scalable storage and retrieval systems for heterogeneous robot data (vision, proprioception, action, language) across both cloud and on-prem environments. Requirements Bachelor's or Master's degree in Computer Science, Robotics, or related field with 5+ years of experience. Strong proficiency in Python and experience build

DevOps Engineer As a DevOps Engineer at Particle41, you will play a crucial role in enhancing our software development and IT operations processes. The ideal candidate will have a strong background in both software development and IT operations, with a focus on automating and streamlining processes to achieve efficient and reliable software delivery for our customers. You will work closely with the development and operations teams of our customers to build, deploy, and maintain critical systems, ensuring the reliability and scalability of the customers' infrastructure. In This Role, You Will: Collaboration and Communication: Work closely with software developers, system administrators, and other stakeholders to understand the requirements and objectives of projects. Collaborate on the design, implementation, and maintenance of continuous integration and delivery pipelines. Create and maintain comprehensive documentation for systems, processes, and configurations. Automation and Tooling: Design, implement, and manage automation processes for software build, deployment, and configuration. Evaluate, select, and implement tools and technologies to enhance the efficiency of the development and deployment processes. Infrastructure Management: Manage and maintain cloud-based infrastructure (AWS, Azure, GCP, and other cloud providers) to ensure scalability, reliability, and security. Implement infrastructure as code (IaC) using tools such as Terraform, Pulumi, and others. Establish and maintain CI/CD pipelines to automate the software delivery process, including build, test, and deployment phases. Monitoring and Performance: Develop and implement monitoring solutions to ensure the health and performance of systems and applications. Proactively identify and address issues related to system performance, reliability, and scalability. Security and Compliance: Implement and maintain security best practices in infrastructure and application deployment. This would include vulnerab

The Fleet team at OpenAI supports the computing environment that powers our cutting-edge research and product development. We oversee large-scale systems that span data centers, GPUs, networking, and more, ensuring high availability, performance, and efficiency. Our work enables OpenAI’s models to operate seamlessly at scale, supporting both internal research and external products like ChatGPT. We prioritize safety, reliability, and responsible AI deployment over unchecked growth. About the Role The Software Engineer, Operating Systems & Orchestration will focus on building systems to manage hardware, configurations, vendors, and the people interacting with our infrastructure. You will design and develop solutions that integrate individual nodes and servers into unified clusters, directly contributing to advancing AI research by streamlining the overall research user experience. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design and build systems to manage both cloud and bare-metal fleets at scale. Develop tools that integrate low-level hardware metrics with high-level job scheduling and cluster management algorithms. Leverage LLMs to coordinate vendor operations and optimize infrastructure workflows. Automate infrastructure processes, reducing repetitive toil and improving system reliability. Collaborate with hardware, infrastructure, and research teams to ensure seamless integration across the stack. Continuously improve tools, automation, processes, and documentation to enhance operational efficiency. You might thrive in this role if you: Have strong software engineering skills with experience in large-scale infrastructure environments. Possess broad knowledge of cluster-level systems (e.g., Kubernetes, CI/CD pipelines, Terraform, cloud providers). Have deep expertise in server-level systems (e.g., systems, containerization, Chef,

센드버드는 옴니채널 AI와 세계 최고 수준의 검증된 커뮤니케이션 API를 결합하여, 기업이 AI 에이전트를 구축하고 의미 있는 고객 연결을 대규모로 만들어갈 수 있도록 돕습니다. 센드버드는 엔터프라이즈 수준의 안정성, 보안성, 규정 준수를 갖춘 솔루션을 제공합니다. DoorDash, Match Group, Noom, Yahoo Sports를 포함한 4,000개 이상의 글로벌 선도 앱이 센드버드를 신뢰하고 있으며, 매월 70억 건 이상의 대화가 센드버드 플랫폼을 통해 이루어지고 있습니다. 현재까지 실리콘밸리 최정상 투자사로부터 (ICONIQ, SoftBank, Tiger Global, Y Combinator) 누적 총 2억2천만달러 (약 2,450억 원)의 투자를 유치하였으며 국내 최초 기업가치 1조원 이상의 글로벌 유니콘 기업입니다. 캘리포니아 산 마테오의 본사와 서울의 R&D센터 및 APAC 오피스 그리고 뉴욕, 런던, 싱가포르, 인도, 캐나다 등에 오피스를 두고 있습니다. Intern, AI Agent Engineering AI 에이전트 엔지니어링 인턴은 엔지니어링 및 제품 팀과 협력하여 지능형 에이전트를 구축, 통합 및 배포합니다. 최신 웹 프레임워크, LLM API 및 툴링 파이프라인을 사용하여 프로토타입부터 프로덕션까지 실무 경험을 쌓게 됩니다. 인턴십 기간은 8~12주 입니다.(기간 논의 가능) 이런 일을 하실 수 있어요 에이전트 프로토타이핑 및 개발 프롬프트 엔지니어링으로 Hallucination 탐지, 대화 Resolution 등 마이크로 API 개발업무를 합니다. 내부 데이터셋과 도구를 활용해 AI Agent의 정확도를 테스트하고 검증합니다. 검색 증강 생성(RAG), 지식 기반 및 맞춤형 툴체인을 지원하는 백엔드 API를 통합합니다. 프롬프트 엔지니어링 및 툴링 다양한 사용 사례에 맞는 프롬프트를 제작, 테스트 및 세부 조정합니다. 프롬프트 버전 및 에이전트 배포를 위한 CI/CD 파이프라인을 설정합니다. 통합 및 배포 웹, 채팅 및 API 중심 환경에 에이전트를 임베드합니다. 실시간 성능 지표를 모니터링하고 로그, 대시보드 등의 관측 기능을 구현합니다. 협업 및 문서화 팀이 시니어 엔지니어, 제품 관리자 및 UX 디자이너와 긴밀히 협력할 수 있도록 지원합니다. 이런 분과 함께 하고 싶어요 Python: 깔끔하고 유지 관리가 용이한 Python 코드 작성 경험 Backend: Django, FastAPI, Express 등 서버 측 프레임워크를 사용한 백엔드 개발 실무 경험 협업: 뛰어난 의사소통 능력, 문서화 기술, 그리고 애자일한 팀에서의 협업 경험 산업기능요원 보충역 지원 가능 이런 점이 있으시면 더 좋아요 프롬프트 엔지니어링 프레임워크(예: LangChain) 사용 경험 클라우드 플랫폼(AWS Lambda, Vercel, GCP Cloud Functions)에 대한 이해도 AI 제품 관련 UX 디자인 또는 제품 관리 경험 Django 또는 유사한 Python 웹 프레임워크 사용 경험 이런 점을 얻을 수 있어요 첨단 에이전트 기반 AI 개발 및 시스템 배포에 대한 심층 분석 엔지니어링, 제품 및 디자인 전문가와의 교차 기능 협업 시니어 AI 엔지니어의 멘토링 실제 고객 사용 사례, 성능 튜닝 및 프로덕션급 툴 활용 경험 유연근무제 정책 Sendbird는 유연한 근무 일정을 지원합니다. 협업과 팀워크의 중요도가 높기에, 모든 구성원은 주 3일 이상 사무실에서 함께 모여 일하고 있어요. 일부 역할은 사무실 출근이 더 자주 필요할 수 있으니, 구체적인 요건은 매니저와 상의해 주세요. 센드버드가 생각하는 다양성과 포용 위 요구사항에 100% 부합하지 않으셔도 괜찮습니다. 센드버드는 모두가 배우고 성장할 수 있는 곳이기에 다양한 배경, 경험 및 기술 스택을 가진 누구든 최고의 직원이 되실 수 있다고 생각합니다. 우리는 평등한 고용 기회를 위해 다양성을 존중하고 장려하고 있습니다. 이 포지션이 여러분의 가슴을 뛰게 만든다면 지원해주세요! Flexible Work

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role At Anthropic, we are pioneering new frontiers in AI that have the potential to greatly benefit society. However, developing advanced AI also comes with risks if not properly safeguarded. That's why we are seeking an exceptional Detection and Response engineer that will be on the frontlines to build solutions to monitor for threats, rapidly investigate incidents, and coordinate response efforts with other teams. In this role, you will have the opportunity to shape our security capabilities from the ground up alongside our world-class research and security teams. Responsibilities: Lead cybersecurity Incident Response efforts covering diverse domains from external attacks to insider threats involving all layers of Anthropic’s technology stack Develop and deploy novel tooling that may leverage Large Language Models to enhance detection, investigation, and response capabilities Create and optimize detections, playbooks, and workflows to quickly identify and respond to potential incidents Review Incident Response metrics and procedures and drive continuous improvement Work cross functionally with other security and engineering teams Note: This position will require participation in an on-call rotation You may be a good fit if you: 3+ years of software engineering experience, with security experience a plus and/or 5+ years of detection engineering, incident response, or threat hunting experience A solid understanding of cloud environments and operations Experience working with engineering teams in a SaaS environment Exceptional communication and collaboration skills An ability to lead projects with little guidance

AI Engineer Role Overview: As an AI Engineer at Particle41 you will design, develop and deploy machine-learning and deep-learning models/solutions (including generative-AI) that address complex business problems. You will collaborate with data scientists, data engineers, software engineers and client stakeholders. You will also build scalable pipelines, ensure production readiness, monitor performance and iterate proactively. In This Role, You Will: Lead end-to-end development of AI/ML models: from data ingestion & preprocessing to model training, evaluation, deployment and monitoring. Build generative-AI solutions (RAG, Agentic Workflows, MCP Servers, Conversation AI Agents) aligned with business goals. Work closely with data engineering teams to build/maintain data pipelines, feature stores and orchestration frameworks. Develop and integrate AI models into production systems (APIs, microservices, cloud deployments). Optimize models/solutions for performance, scalability, robustness and cost-efficiency. Monitor models/ solutions’ performance in production (drift, bias, fairness, reliability) and implement remediation. Document model design, experiments, data provenance and solution rationale. Stay abreast of latest AI/ML research, frameworks, tools (e.g. LangChain, LangGraph, MCP Clients/Servers, Agents SDKs, LiveKit etc.) and propose innovative ideas. Work directly with clients to understand problem statements, translate business requirements into AI solutions, and clearly communicate results. Skills and Experience We Value: Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field. 3+ years of hands-on experience in AI/ML model development and deployment. Strong programming skills in Python and experience with major ML/AI frameworks (TensorFlow, PyTorch, scikit-learn, LangChain, LangGraph). Experience with vector databases (e.g., Pinecone, FAISS), RAG and Agentic workflows. Experience building or fine-tuning Large Language

About Cubist Cubist Systematic Strategies, an affiliate of Point72, is one of the world’s premier investment firms. The firm deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures, and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. Job Description The Central Research Technology team, which builds strategic solutions for research and live trading of quantitative strategies across multiple frequencies and products, is seeking a highly talented intern to work with the team in January. This is a unique opportunity to help design and build the next generation of research and quant trading systems for Cubist. Desirable Candidates Undergraduate or graduate candidates in computer science or engineering Significant experience in Python and/or C++ Interest in open source research tools for data science and machine learning Basic knowledge of linux, git, conda, and CI processes Knowledge of cloud, databases and distributed or streaming compute is a plus Reasonable quantitative and statistical skills Experience with Finance preferred Clear, concise, and proactive communicator Detail oriented and quick learner in a fast-paced environment Team player with strong pride of ownership Commitment to the highest ethical standards

Data Science Manager Location: London (Hybrid) | Practice Area: Data & Analytics | Type: Permanent Shape intelligent solutions. Lead with insight. Drive data innovation. The Role We’re looking for a Data Science Manager to lead innovative projects that apply data, AI, and machine learning to solve complex challenges across financial services. You’ll guide talented data professionals, collaborate closely with business stakeholders, and drive impactful, scalable solutions that deliver measurable business value. You'll champion AI-enabled ways of working, encouraging the responsible use of approved AI tools and automations to improve delivery quality, productivity, and insight while maintaining appropriate human oversight and governance. What You’ll Do Lead data science teams to design, develop, and deploy advanced machine learning and AI solutions. Drive the adoption of cutting-edge technologies including generative AI, LLMs, and agentic AI frameworks, while promoting responsible AI practices, governance, and appropriate human review throughout the delivery lifecycle. Collaborate with business and technology teams to align technical outcomes with strategic goals, leveraging AI-enabled workflows where appropriate to accelerate insight and delivery. Provide thought leadership and best practices across the data science lifecycle, from exploration to deployment, including scalable MLOps, model governance, and responsible AI implementation. Mentor and develop data professionals, fostering a culture of innovation, continuous learning. What We’re Looking For Proven experience leading the delivery of data science or AI projects from concept to production. Strong knowledge of Python and core ML libraries (e.g., spaCy, NumPy, SciPy, Transformers). Understanding of big data and cloud technologies (Spark, Hadoop, Azure, AWS, or GCP). Deep expertise in MLOps principles, scalable model deployment, model governance, and the practical application of responsible AI within enterpri

About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Security team protects OpenAI’s technology, people, and products. We are technical in what we build but are operational in how we do our work, and are committed to supporting all products and research at OpenAI. Our Security team tenets include: prioritizing for impact, enabling researchers, preparing for future transformative technologies, and engaging a robust security culture. About the Role We’re seeking an exceptional Principal-level Offensive Security Engineer focused on deep, hands-on penetration testing of OpenAI’s agent-powered products, infrastructure, and model-integrated application surfaces. You’ll assess complex systems end to end, identify realistic vulnerabilities, validate exploitability and impact, and partner closely with engineering teams to drive durable fixes. This role will be primarily focused on continuously testing our agent-powered products like Codex and Operator. These systems are uniquely valuable targets because they’re rapidly evolving, can perform sensitive actions on behalf of users, and have large, diverse attack surfaces. You will play a crucial role in securing our agents by finding vulnerabilities that emerge from the interactions between the applications, infrastructure, tools, and models that power them. You’ll have the chance to not only find vulnerabilities, but actively drive their resolution, build reusable testing approaches, automate offensive security workflows with cutting-edge technologies, and use your attacker perspective to improve the security of OpenAI’s products. In this role you will: Conduct deep penetration tests of OpenAI’s agent-powered products, including web applications, APIs, cloud services, identity and authorization flows, CI/CD systems, and model-integrated product surfaces. Continuously hunt for exploitable vulnerabilities in the interactions between the appli

Our Security team keeps Asana's employees, users, and customers safe by proactively addressing threats and fostering a culture of security across our product and operations. We're looking for a Staff Detection Engineer to join our Threat Response team in our Warsaw innovation hub. You'll own how we find threats: the detection logic, the telemetry it runs on, and the pipeline that ships it. Detection here is software. Rules are written as code, tested against real and synthetic attacker behavior, reviewed in pull requests, and deployed through CI/CD. You'll partner with our incident responders, infrastructure, and product teams to make sure that when something bad happens, we see it fast and with high signal. We offer a Contract of Employment (UoP) for our employees in Poland. What you'll achieve Design, build, and maintain high-fidelity detections across cloud infrastructure (AWS/GCP), identity providers (e.g., Okta), SaaS environments, endpoints, and the software supply chain. Own our detection-as-code pipeline in Panther: rule structure, unit and integration tests, review standards, and CI/CD deployment, so detection logic is treated as production code. Map and close coverage gaps against MITRE ATT&CK and the threat model for our environment, prioritizing the techniques most likely to be used against a SaaS company. Onboard and normalize new telemetry sources , working with infrastructure and IT to make sure the right logs exist, are complete, and are queryable. Measure and improve alert quality , tracking precision, time-to-triage, and false-positive rates, and tuning or retiring detections that don't earn their keep. Validate detections against real attacker behavior through purple-team exercises, atomic tests, and emulation, and feed findings back into rule development. Turn incidents and threat intelligence into detections , partnering with incident responders to convert lessons learned and emerging TTPs into durable coverage. Build enrichment and automati

P-256 We are looking for experienced pre-sales professionals with a proven track record of helping large enterprises become more data-driven. Working with the Account Executive (AE), the Retail and CPG Sr. SA defines and directs the technical strategy for our largest and most important accounts, leading to more widespread use of our products and wider and deeper adoption of ML & AI. You will lean upon your solid background in value selling, technical account management, and technical leadership to maximize success in these accounts. While you work with a team that includes hands-on resources who will build proofs of concept and demonstrate Databricks' products, you need to be technical and must understand the relevance and application of ML & AI within a range of use cases important to the target accounts in the Retail and CPG space. The impact you will have: You will work with 1-5 clients as the main technical voice for Databricks You will lead your customers on a transformational journey, helping them to evaluate and adopt Databricks as part of their strategy You will implement the technical strategy in the account, with a close understanding of the strategy Build a movement of technical champions within the account Align technical strategies around Databricks solutions You will provide structured mentorship for other team members What we look for: 8+ years of experience working in very large (> $1m ARR), from the Retail and CPG-related space 4+ years working in a pre-sales capacity or supporting sales activity Technical in big data, data science, and cloud An ability in data-driven business transformation and driving change with data 4+ years of experience with design and implementation experience in big data technologies such as Hadoop, NoSQL, MPP, OLTP, and OLAP, or full lifecycle data science solutions Maintain and extend production data systems to evolve with complex customer needs Production programming experience in Python, R, Scala, or Java Nice