2 Backend Java Engineers

🏢 Summary: Build and scale a central policy repository and web-based management tooling that powers content detection, enforcement, and compliance systems. The role combines backend API development, data pipeline engineering, and frontend application development to support policy versioning and regulatory requirements at scale. You will collaborate across safety, legal, and compliance teams to deliver reliable, user-friendly internal tools. 🗂️ Requirements: Experience building and operating backend services and APIs in production at scale, Proficiency in Java, Kotlin, Go or similar backend language, Experience building web frontends with React, TypeScript or similar framework, Understanding of API design, schema evolution and backward compatibility, Experience with data pipelines, real-time and batch processing, Ability to design and build user-friendly interfaces, Experience working in regulated or compliance-sensitive environments, Ability to collaborate across teams and communicate with non-technical stakeholders 📃 Skills: Java, Kotlin, Go, React, TypeScript, APIs, Data, Pipelines, Real-time, Batch 🏢 Description: About the Team We design the consumer experience end-to-end, across every screen, platform, and partner integration. Our goal is to make listening feel effortless, personal, and joyful for hundreds of millions of users around the world. The Policy & Safety group builds the infrastructure that keeps that experience safe at scale. This includes the rule engines, enforcement pipelines, policy configuration systems, and compliance data platforms behind content moderation. We work at the intersection of backend platform engineering, machine learning systems, and regulatory compliance, partnering closely with trust and safety, legal, and content protection teams. Because we sit on the path of every new content type and feature, our work makes safety a default part of the company experience while supporting global regulatory requirements and ongoing product innovation. The Policy Catalog team owns the central policy repository, the single source of truth for how content policies are defined, versioned, and used across detection, enforcement, and compliance. We are building and scaling this system to be the reliable foundation that the entire safety enforcement chain depends on, bringing policies from many areas of the business into one well-structured system. A core part of this work is building the web-based tooling that lets teams manage the policy registry directly, ensuring our systems are as strong on the frontend as they are on the backend. What You'll Do You will build and maintain the APIs and services that expose policy logic consistently across detection, enforcement, and compliance surfaces. You will contribute to the design and development of the central policy repository, expanding its capabilities to cover new use cases including detection, and build data pipelines that feed structured policy data into downstream machine learning models and enforcement systems. Develop and maintain backend services and APIs. Design and implement the internal web application for policy management by non-technical stakeholders. Ensure the full experience is responsive, reliable, and user-friendly. Ingest, structure, version, and ensure the reliability of policies across the business. Collaborate with detection, enforcement, and compliance partners to align on policy definitions. Translate regulatory and compliance requirements into engineering constraints. Write clean, well-tested, and well-documented code across the stack. Key Requirements Solid experience building and operating backend services and APIs in production at scale. Proficiency in a backend language such as Java, Kotlin, Go, or similar. Hands-on experience building web frontends with a modern framework such as React, TypeScript, or similar. Understanding of API design, schema evolution, and backward compatibility. Experience with data pipelines, real-time, and batch processing. Ability to build user-friendly interfaces that simplify complex workflows. Experience in regulated or compliance-sensitive environments. Effective collaboration across teams and clear communication with non-technical partners. Nice to Have Experience in developing internal tooling for non-technical audiences. Familiarity with data modeling for auditability, versioning, and querying. Other Details Start: ASAP/August - 6 months with possibility to extend Workplace: Stockholm, Sweden

🏢 Summary: Full-time remote Middle DevOps Engineer role combining DevOps and backend development in Kotlin to support and operate security-sensitive, Dockerized backend services on AWS. The position focuses on designing, automating, and maintaining scalable cloud infrastructure and CI/CD pipelines while contributing directly to production Kotlin code. You will collaborate with engineering teams to enhance deployment, observability, and operational reliability. 🗂️ Requirements: 3–5 years of DevOps experience, Bachelor’s degree in Computer Science, Engineering, or equivalent experience, Hands-on Kotlin development in production services, Strong scripting skills in Python or Bash, Experience with infrastructure and packaging tools, Experience with SQL or NoSQL databases, Hands-on Docker experience, Experience with Kubernetes or Swarm, Strong AWS DevOps and IAM knowledge, Experience with CI/CD platforms, Experience implementing observability solutions, Advanced Docker knowledge (multi-stage builds, image hardening, runtime tuning), Experience in security-sensitive environments 📃 Skills: Kotlin, Docker, Kubernetes, Swarm, AWS, IAM, Terraform, CloudFormation, Ansible, JFrog, Python, Bash, SQL, Postgres, Elasticsearch, Redis, TeamCity, GitLab, GitHub, CI/CD, Observability 🏢 Description: Svitla Systems Inc. is looking for a DevOps Engineer with Kotlin for a full-time remote position (40 hours per week) in Europe. Our client is a global leader in mobile security, providing AI-driven, on-device protection for enterprise and government mobile applications and devices worldwide. The platform defends against mobile-targeted phishing (mishing), malware, application vulnerabilities, and zero-day exploits. This role partners with the client's research team and supports the "download and decrypt" services that underpin the platform. You'll partner with the research engineering team to design, build, and operate the infrastructure behind a security-sensitive backend service. The role blends classic DevOps work (CI/CD, automation, observability, cloud) with hands-on contributions to the service code written in Kotlin. It is a hybrid DevOps and backend engineering role with Docker experience on top of a Kotlin/DevOps foundation. This position consists of approximately 70% DevOps work and 30% backend development using Kotlin Requirements: Minimum 3–5 years of strong experience with DevOps. Bachelor's degree in Computer Science / Engineering, or equivalent practical experience. Hands-on experience in Kotlin development, including comfortable reading, extending, and shipping production Kotlin services, not just deploying them. In-depth understanding of scripting in Python and/or Shell/Bash. Knowledge of infrastructure and packaging tools, including JFrog, Ansible, Terraform, and CloudFormation. Knowledge of databases such as SQL, Postgres, Elasticsearch, or Redis. Hands-on experience with container technologies such as Docker (required) with Swarm or Kubernetes. Strong understanding of AWS DevOps efforts and management. Experience with Cloud IAM Groups, Roles, IAM policies, and STS. Familiarity with CI/CD platforms such as TeamCity, GitLab CI, or GitHub Actions. Practical experience implementing one or more observability platforms. Willingness to continuously learn and improve. Advanced knowledge of Docker (multi-stage builds, image hardening, runtime tuning). The services run as Dockerized backends on the client's infrastructure. Exposure to security-sensitive engineering environments. Responsibilities: Design, develop, and support cloud and locally hosted solutions that make service deployment, availability, and operations straightforward. Continuously improve processes and infrastructure to be easy to deploy, scalable, secure, and fault-tolerant. Automate operational, testing, installation, and other processes to increase efficiency and stability. Collaborate with the service development team to resolve complex operational issues and deliver value. Document how to diagnose and resolve issues in complex systems. Build CI/CD solutions to improve developer productivity and enable rapid deployments. Support and extend existing service software written in Kotlin. Collaborate with the team to establish and uphold DevOps best practices. We offer: US and EU projects based on advanced technologies. Competitive compensation based on skills and experience. Flexibility in workspace, either remote or our welcoming office. Bonuses for article writing, public talks, and other activities. Free tech webinars and meetups organized by Svitla. Regular corporate online activities. Awesome team, friendly and supportive community!

🏢 Summary: Hands-on DevOps Engineer role focused on building and operating automation, deployment, and reliability standards for large-scale GPU infrastructure supporting AI training and inference. The position involves Infrastructure as Code, CI/CD, observability, security, and low-level automation across bare-metal servers, networking, storage, and Kubernetes-based platforms. The role emphasizes reliability, scalability, and automation in complex, high-performance environments. 🗂️ Requirements: 4–7 years in DevOps, SRE, or Platform Engineering, Experience with infrastructure automation in production environments, Hands-on experience with Terraform or Ansible, Experience building and maintaining CI/CD pipelines, Knowledge of GitOps practices, Understanding of infrastructure security and vulnerability management, Experience with security tools (e.g., Snyk, CrowdStrike), Practical experience with Kubernetes, Experience with GPU technologies (e.g., NVIDIA GPU Operator, MIG), Scripting or programming skills in Python, Go, or Bash, Experience with bare-metal provisioning or low-level infrastructure automation, Knowledge of observability tools (Prometheus, Grafana, Loki, OpenTelemetry) 📃 Skills: Terraform, Ansible, Kubernetes, Python, Go, Bash, Prometheus, Grafana, Loki, OpenTelemetry, Snyk, CrowdStrike, NVIDIA, MIG, CI/CD, GitOps 🏢 Description: About the role We are looking for a DevOps Engineer to help build and operate automation, deployment, and reliability standards for large-scale GPU infrastructure used for AI training and inference workloads. In this role, you will work on software-defined infrastructure supporting GPU clusters, high-performance networking, storage platforms, and internal AI services. This is a hands-on position for someone who is comfortable working close to infrastructure, improving operational processes, and building reliable automation in a complex technical environment. Responsibilities Design, implement, and maintain Infrastructure as Code solutions for provisioning and managing bare-metal GPU servers, networking, storage, and cluster orchestration components Build and improve CI/CD pipelines for infrastructure, platform services, and internal tooling Develop and maintain monitoring, logging, alerting, and observability solutions for large-scale GPU environments Support reliability initiatives by defining and tracking SLIs/SLOs , automating incident response, and contributing to post-incident analysis Automate operational tasks such as cluster scaling, firmware and BIOS updates, hardware validation, diagnostics, and capacity planning Work closely with Infrastructure, Networking, Facilities, and AI/ML teams to ensure stable and scalable platform operations Support DevSecOps practices, including infrastructure hardening, vulnerability management, and compliance automation Identify repetitive manual work and replace it with efficient automation Evaluate new tools and solutions related to GPU infrastructure, orchestration, and cloud-native operations Requirements 4–7 years of experience in DevOps, SRE, Platform Engineering , or a similar role Strong practical experience with infrastructure automation in complex production environments Good hands-on knowledge of Terraform, Ansible , or similar Infrastructure as Code tools Experience building and maintaining CI/CD pipelines and working with GitOps practices Good understanding of infrastructure security, vulnerability management, and security best practices Experience with security tools such as Snyk, CrowdStrike , or similar solutions Practical experience with Kubernetes Experience working with GPU-related technologies such as NVIDIA GPU Operator, device plugins, MIG, or time-slicing Good scripting or programming skills in Python, Go, or Bash Experience with bare-metal provisioning, low-level infrastructure automation, or data center operations Good knowledge of observability tools such as Prometheus, Grafana, Loki, and OpenTelemetry Ability to work independently, prioritize tasks, and communicate effectively with technical teams English proficiency at least at a communicative level is required, as you will be working in an international team Nice to have Experience in AI infrastructure, HPC environments, hyperscale infrastructure, or data center operations Familiarity with orchestration and scheduling tools such as Slurm, Ray, Run:ai, KServe , or Kubernetes-based schedulers Experience integrating telemetry from power, cooling, or environmental systems Experience building internal platforms or self-service tools for engineering teams Understanding of compliance and audit requirements in security-sensitive environments What we offer Benefits package Opportunity to work on advanced infrastructure supporting large-scale AI workloads Real impact on the reliability and scalability of next-generation compute environments Collaboration with experienced engineers across infrastructure, platform, and AI domains A fast-moving environment with space for ownership, technical input, and professional growth

🏢 Summary: The role focuses on building and owning reliable data pipelines and MLOps infrastructure for a retail loss prevention project using Spark, Airflow, and Azure. You will develop production-grade Python solutions, automate CI/CD processes, and provision cloud infrastructure as code while enhancing monitoring and observability. The position bridges data science and engineering to deliver robust, scalable ML systems in production. 🗂️ Requirements: Strong experience with Python in production environments, Hands-on experience with PySpark and Spark clusters, Experience with workflow orchestration using Airflow, Experience with Azure or equivalent cloud platforms, Practical experience with Infrastructure as Code, Experience automating CI/CD pipelines with GitHub Actions, Knowledge of data validation and monitoring practices, Experience with Kubernetes in production, Experience with observability and monitoring tools, Upper-intermediate English (B2/C1) 📃 Skills: Python, PySpark, Spark, Airflow, Azure, Terraform, GitHub, CI/CD, Kubernetes, Grafana, Prometheus, MLOps 🏢 Description: We foster a dynamic culture rooted in strong engineering, a sense of ownership, and transparency, empowering our team. As part of the expanding VirtusLab Group, we offer a compelling environment for those seeking to make a substantial impact in the software industry within a forward-thinking organization. About the role You will be responsible for building and owning data pipelines on a Spark Kubernetes cluster orchestrated with Airflow using PySpark. You will improve and introduce data validation and monitoring to ensure trustworthy data at every stage. Tasks will include provisioning and managing Azure resources using a mature Infrastructure as Code approach, as well as automating everything with GitHub Actions and maintaining CI/CD workflows. You will enhance monitoring to further improve the reliability and stability of deployed ML solutions using the Grafana/Prometheus stack. Additionally, you will collaborate with cross functional teams to ensure the seamless deployment and serving of ML models and actively shape the project’s technical roadmap and direction. Project: Loss Prevention Project Scope Loss prevention in retail involves the strategic implementation of processes and technologies designed to identify, mitigate, and prevent the disappearance of inventory. To achieve that an Engineering and a Data Science team within a major UK retailer partner to bridge the gap between experimental ML models and robust, production-grade systems. By embedding engineering excellence into the data science lifecycle, the team ensures that loss prevention insights are delivered with high reliability. In this project you will not only develop high-quality Python code, but also implement trustworthy data pipelines on a big Spark cluster orchestrated with Airflow, setup highly automated CI/CD pipelines with Github Actions, and provision Azure infrastructure as code with Terraform. Tech Stack Python, PySpark, Airflow Azure, IaC (Terraform), CI/CD (Github Actions), Observability (Grafana/Promotheus), MLOps, Kubernetes Challenges Establish a resilient MLOps Ecosystem by integrating robust observability, experiment tracking and automated deployment to model serving infrastructure. Improve the reliability and observability of data pipelines to guarantee trust-worthy data. Advancing DevOps Maturity through the implementation of standardized pipelines, enabling rapid iteration and minimizing manual intervention. Team 3 Engineers What we expect in general: Strong experience in writing high-quality Python code and deploying production-level projects. Proactiveness and a strong sense of ownership, taking full responsibility of project outcomes. Significant experience in Data Engineering, specifically with PySpark, data quality monitoring and workflow orchestration. Proficiency in Azure (or equivalent cloud providers) and hands-on experience with Infrastructure as Code principles. Robust DevOps mindset with practical experience automating CI/CD pipelines via GitHub Actions. A dedicated team player with excellent communication skills who thrives within a cross-functional, collaborative environment. Good command of English (B2/C1 level), comfortable utilizing the language daily. A hybrid model is preferred (2-3 days per week in the Kraków office); alternatively, candidates must be available for on-site collaboration as required (approx. once a month). Seems like lots of expectations, huh? Don’t worry! You don’t have to meet all the requirements. What matters most is your passion and willingness to develop. Apply and find out! A few perks of being with us Building tech community Flexible hybrid work model Home office reimbursement Language lessons MyBenefit points Private healthcare Training Package Virtusity / in-house training And a lot more!

🏢 Summary: The role focuses on building and scaling production-grade infrastructure and APIs to serve machine learning models, enabling data scientists to deliver robust, automated solutions to millions of users. You will design CI/CD pipelines, manage cloud infrastructure, and implement MLOps best practices to ensure reliable and scalable ML deployments. This position bridges data science and engineering, emphasizing DevEx, automation, and production readiness. 🗂️ Requirements: Extremely proficient in Python, Deep experience building and scaling APIs for ML model serving, Production experience with AWS, Proficiency in Docker and container orchestration, Experience with CI/CD tools (GitHub Actions, Jenkins), Proficiency with Terraform, Experience with Airflow or similar workflow tools, Familiarity with Tensorflow or similar ML frameworks, Experience in data science or data-focused software engineering, BA/BS in Computer Science, Math, Physics, Engineering, Statistics or related field, Fluency in SQL, Legal right to work in Poland 📃 Skills: Python, FastAPI, Flask, AWS, Docker, Kubernetes, GitHub, Jenkins, Terraform, Airflow, Tensorflow, PyTorch, SQL, CI/CD, MLOps, APIs 🏢 Description: We are looking for a technical powerhouse to bridge the gap between complex data science and scalable engineering . You will supercharge our Data Science team by building the automated infrastructure and APIs that deliver our models to millions of members, ensuring our recommendations are not just smart, but production-ready and bulletproof. About Secret Escapes Secret Escapes is the world's leading, members-only travel and experiences company. We inspire the world to escape by bringing hand-picked offers at unbeatable prices to millions of members worldwide. We’re backed by some of the smartest investors out there, including Google Ventures. Operating in 10 countries across Europe, Secret Escapes continues to grow and establish itself as a world-class business, dedicated to giving our members the best range and value in luxury travel deals at low prices. Secret Escapes operates a hybrid working policy and we are all in the office 3 days a week. This role will be based in our Travelist office in Poland. We offer flexible working with core hours between 10 am to 4 pm, and you have the freedom to schedule the remaining hours to suit your routine. In keeping with being an inspirational travel brand, we also have a ‘Work from Anywhere’ policy, so you can work from anywhere in the world for up to 4 weeks each year! This benefit is designed both to feed our travel passion and support parents and carers, especially during school holidays. We’re a diverse and inclusive bunch of individuals from different backgrounds and with varied interests, but the one thing we all have in common is that we’re good people (even if we do say so ourselves!). We are growing our Product, UX, and Engineering teams significantly. Come and grow with us. The Role & what you'll do Your main responsibility is to support a team of data scientists and ML Ops engineers to offer relevant inferences as an internal service. While our Data Scientists focus on experimentation, you focus on the Developer Experience (DevEx)—building the rails that allow them to ship value faster. You will act as the vital link, liaising with key stakeholders in Engineering, Data, and Product teams to ensure our machine learning capabilities are robust, scalable, and integrated seamlessly into the Secret Escapes platform. Day to day, you will be working on... Architecting and maintaining the CI/CD pipelines for our data products using GitHub Actions and Jenkins. Building, hosting, and scaling high-performance APIs (using frameworks like FastAPI or Flask) to serve ML models to our website and apps. Containerizing machine learning applications using Docker to ensure consistent deployment across our AWS environment. Orchestrating complex data workflows and pipelines using Airflow (or similar tools) to ensure data consistency and accuracy. Managing our Infrastructure as Code (IaC) using Terraform to ensure reproducible and scalable environments. Identifying opportunities to build and improve machine learning models , specifically focusing on the engineering challenges of deploying Tensorflow (or similar) models for recommendation and anomaly detection. Keeping yourself updated on new developments in your field of expertise, specifically regarding modern MLOps best practices and API design. The Team The team consists exclusively of Good Eggs. We care deeply about our customers, but also about each other. We are a creative bunch who prioritize ruthlessly. We work hard and have fun in equal measure. Must haves Extremely proficient in Python (development, scripting, and packaging). Deep experience building, hosting, and scaling APIs for ML model serving . Production experience with Cloud Infrastructure, specifically AWS. Proficiency in Containerization (Docker) and Orchestration. Solid experience with CI/CD tools, specifically GitHub Actions and Jenkins. Proficiency in Infrastructure as Code tools, specifically Terraform. Experience working with workflow management tools like Airflow. Familiarity with ML frameworks like Tensorflow (or PyTorch/similar). Solid experience in the data science field or software engineering with a data focus. BA/BS in Computer Science, Math, Physics, Engineering, Statistics or other technical fields. Fluency in SQL. And you are... Detail oriented Analytical Pragmatic Able to communicate the results of analyses in a clear and effective manner Obsessed with automation and code quality A champion of "DevOps culture" within Data Science Insatiably curious We are an equal opportunity employer: Diversity and inclusion are important to us at Secret Escapes and we encourage a culture where everyone can be themselves at work. We value and actively seek out a richly diverse range of talent and our policies ensure that every job application and employee is treated fairly, with equal opportunity to succeed. All applicants will be considered for employment without regard to any characteristic protected by law. We love building diverse teams and welcome applications from talent across the globe. However, for this specific position, we are unable to sponsor work permits in Poland. We strongly encourage you to apply if: You already hold the legal right to work in Poland. You are eligible to secure your own independent right to work (e.g. through a non employer sponsored visa or residence title) If you need to explore independent visa routes, we recommend checking the official website of the Polish Office for Foreigners or your local Polish Consulate for the most accurate, up to date information.

🏢 Summary: Engineering role focused on building and modernizing large-scale settlement and cash processing systems that power financial operations and regulatory reporting. The position involves designing scalable backend and data platforms processing millions of daily transactions, while collaborating closely with Finance and Product stakeholders. Key initiatives include revamping the historical settlement system and expanding into payment fees analytics. 🗂️ Requirements: Deep expertise in backend engineering (Java) or data engineering, Experience processing large-scale transactional and financial data, Experience with batch or streaming frameworks (Spark, Flink, or Beam), Proficiency in Scala for data engineering, Experience building scalable backend systems in Java, Strong understanding of system design, data structures, and algorithms, Experience with cloud-native development, preferably Google Cloud Platform, Ability to design reliable, maintainable, and auditable systems 📃 Skills: Java, Scala, Spark, Flink, Beam, GCP, SQL, Algorithms, DataStructures, Cloud, Backend, DataEngineering 🏢 Description: Our team is building the settlement and cash processing systems that drive how cash from our customers is processed and accounted for — enabling reliable, scalable financial operations across every market, product line, and partner. Our systems are essential to our stakeholders’ ability to track and report revenue and taxes, supporting all of our core business lines. As engineers on this team, we design and maintain the backend and data platform capabilities that power millions of transactions each day with precision. We build services that handle settlement and bank transactions, produce compliant financial records, and support regulatory requirements across global markets — all while staying agile to keep up with our evolving business model and staying in sync with our many payment partners. We build robust services that provide clarity over what’s happening under the hood of millions of daily transactions, enabling quick action to any disruption. Our modular, process-oriented components simplify the development, maintenance, and scaling of the critical Order to Cash enterprise process that underpin the financial operations. We are starting two major initiatives: a revamp of our historical settlement system in order to align with our modularity strategy as well as expanding into the adjacent domain of payment fees, which is a massive cost center in need of good data for analytics in order to optimize the space. We’re looking for engineers passionate about building complex, high-impact systems. You’ll work closely with stakeholders in Finance (Accounting and Payments), Product, and Engineering to design solutions that are scalable, auditable, and robust. If you’re energized by the challenge of transforming intricate business processes into clean, extensible platforms we’d love to have you on the team. What You’ll Do - Gain deep expertise in client’s revenue and settlement systems, understanding how it enables financial operations, compliance, and strategic decision-making across the company. - Design and implement scalable backend and data systems that process millions of transactions daily to enable the cash-application process and financial reporting. - Build intuitive, self-serve tools that empower Finance teams to define and manage product-specific revenue and settlement configuration independently, without requiring engineering involvement. - Develop and enhance modular platform capabilities that encodes critical enterprise workflows, promoting consistency, reusability, and ease of maintenance across financial systems. - Partner closely with Engineers, Product and Finance stakeholders to design systems that are scalable, auditable, and highly reliable. - Champion engineering best practices, strong architectural design, and operational excellence across backend and data platforms. - Foster a collaborative team culture rooted in shared ownership, constructive feedback, and continuous improvement. Who You Are - You possess a T-shaped engineering skill set — deep expertise in either data or backend engineering (Java), while growing the ability to work effectively across both. For this role, experience or familiarity with processing large-scale transactional and financial data, using batch/streaming frameworks like Spark, Flink, or Beam (with Scala for data engineering), and building scalable backend systems in Java is a strong advantage. - You possess a foundational understanding of system design, data structures, and algorithms, coupled with a strong desire to learn quickly, embrace feedback, and continuously improve your technical skills. - You’re familiar with cloud-native development and deployment, ideally within the Google Cloud Platform. - You think critically about system design and strive to build solutions that are reliable, maintainable, and auditable at scale. - You have good communication skills and can articulate your ideas and ask clarifying questions. - You love collaborating with others. - You thrive in ambiguous and fast-changing environments, and know how to make progress even when requirements are evolving. - You approach platform engineering with empathy for your users — prioritizing usability, configurability, and long-term sustainability. - You care deeply about code quality, testing, and documentation, and you aim to build systems that are easy to understand and operate. - You enjoy collaborating across functions and bring clarity and alignment when working with engineering, finance, and product partners. - You’re naturally curious, self-motivated, and always looking for ways to grow your technical skills and improve how things are done. Other Details Start: Asap or August Length: 6 months Workplace: Sweden

🏢 Summary: Lead and grow the Source Security team, driving the roadmap for securing code contributions through static analysis and LLM-based review systems. The role combines hands-on technical work with team leadership to ensure secure source code management, CI environments, and scalable supply chain security. You will collaborate cross-functionally to embed robust security controls into development workflows and coding agent ecosystems. 🗂️ Requirements: Experience managing distributed engineering teams, Proficiency in modern programming languages (Python, Go, or JavaScript), Experience with continuous security scanning and SAST rule tuning, Experience with LLM-based coding tools, Experience with source code management platforms, Experience integrating security into CI pipelines, Ability to contribute hands-on to security engineering initiatives, Experience with incident response and on-call processes 📃 Skills: Python, Go, JavaScript, SAST, LLM, GitHub, GitLab, CI, DevSecOps, Fuzzing, Sandboxing, DevOps, SCM 🏢 Description: About Datadog We're on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at a high scale - trillions of data points per day — providing always-on alerting, metrics visualization, logs, and application tracing for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. The Opportunity We are looking for a manager to lead the Source Security team within our broader SDLC Security org. This team is responsible for evaluating the security properties of every single commit at Datadog using a combination of static analysis and LLM based review systems, as well as the governance of our source code and third party dependency ecosystem. You will own the roadmap for growing our existing agentic reviewers (you can read more about this work here and here), working to maintain the safety and reliability of our systems while the volume of contributions scales dramatically with our adoption of coding agents. You’ll partner with our developer experience organizations on securing our source code and CI environments, and our product teams on making sure that our security controls scale and that the best practices we develop internally are reflected for our customers as well. You’ll join at an ideal time to make a big impact as the need for robust supply chain security is higher than it’s ever been. Datadog as a platform is growing fast and is used very widely, and the continued and exciting expansion of our product portfolio requires agile thinkers with a deep grounding in security fundamentals. 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: Lead a small team, working as a hands on technical contributor while building out the roadmap for evaluating the safety of coding agent output using a combination of static analysis and LLM evaluations. Partner with our Developer Experience teams on the configuration of our source code management solutions, ensuring secure guardrails are in place by default. Explore solutions in the coding agent security space such as sandboxing and hook based monitors. Guide and mentor a team of security and software engineers, emphasizing career development, inclusivity, and high performance. Take a pragmatic, risk-based approach to complex technical problems and work with your team to produce well-defined and actionable plans. Balance your time between management and hands-on technical work. Participate in Datadog’s oncall and incident response efforts. Have a direct impact on users and the overall trust of our platform. Who You Are: Experienced managing an engineering team distributed across multiple timezones. Fluent in one or more modern coding languages (Python, Go, JavaScript, etc.) Familiar with continuous security scanning and fine-tuning SAST rules and methodology, as well as AI based coding tools such as Claude, Codex, and Cursor Familiar with Github, Gitlab, or other modern source code management and CI solutions You are able to work closely with engineering and DevOps teams to integrate security seamlessly into the development process. An excellent communicator and collaborator, able to work effectively through complex technical problems with a diverse group of stakeholders. Comfortable working in a fast paced, high growth environment, and able to adapt strategies and solutions in response to emerging challenges and opportunities. Bonus Points: Passionate about building products that engineers love and believe in the true outcome of DevSecOps Familiar with formal verification, fuzzing, or code correctness methodologies Experience productionizing LLM based or agentic workflows Familiar with product workflows, and building security into the user experience 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 skills, we encourage you to apply. Benefits and Growth: New hire stock equity (RSUs) and employee stock purchase plan (ESPP) Continuous professional development, product training, and career pathing Intradepartmental mentor and buddy program for in-house networking An inclusive company culture, ability to join our Community Guilds (Datadog employee resource groups) Access to Inclusion Talks, our internal panel discussions Free, global mental health benefits for employees and dependents age 6+ Competitive global benefits Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog. #LI-HybridDatadog offers a competitive salary and equity package, and may include variable compensation. Actual compensation is based on factors such as the candidate's skills, qualifications, and experience. In addition, Datadog offers a wide range of best in class, comprehensive and inclusive employee benefits for this role including healthcare, dental, parental planning, and mental health benefits, a 401(k) plan and match, paid time off, fitness reimbursements, and a discounted employee stock purchase plan.The reasonably estimated yearly salary for this role at Datadog is:$240,000—$305,000 USD About Datadog: Datadog (NASDAQ: DDOG) is a global SaaS business, delivering a rare combination of growth and profitability. We are on a mission to break down silos and solve complexity in the cloud age by enabling digital transformation, cloud migration, and infrastructure monitoring of our customers’ entire technology stacks. Built by engineers, for engineers, Datadog is used by organizations of all sizes across a wide range of industries. Together, we champion professional development, diversity of thought, innovation, and work excellence to empower continuous growth. Join the pack and become part of a collaborative, pragmatic, and thoughtful people-first community where we solve tough problems, take smart risks, and celebrate one another. Learn more about #DatadogLife on Instagram, LinkedIn, and Datadog Learning Center. Equal Opportunity at Datadog: Datadog is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and other characteristics protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Here are our Candidate Legal Notices for your reference. Datadog endeavors to make our Careers Page accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please complete this form. This form is for accommodation requests only and cannot be used to inquire about the status of applications. Privacy and AI Guidelines: Any information you submit to Datadog as part of your application will be processed in accordance with Datadog’s Applicant and Candidate Privacy Notice. For information on our AI policy, please visit Interviewing at Datadog AI Guidelines.

🏢 Summary: Design and build a modern data platform from scratch for an insurance client, covering architecture, data ingestion, modelling, and production operations. The role focuses on establishing a governed, scalable Snowflake-based environment to enable reliable reporting and AI capabilities. You will take ownership across the full data lifecycle, from requirements definition to deployment and maintenance. 🗂️ Requirements: Hands-on experience with Python, Proven experience with data warehouse solutions (BigQuery, Redshift or Snowflake), Experience with Databricks or data lakehouse platforms, Strong expertise in data modelling and ETL/pipeline design and maintenance, Experience with AWS, GCP or Azure cloud services, Ability to design and build data ingestion and processing pipelines, Experience working in Agile environment, Understanding of data governance and data quality concepts 📃 Skills: Python, SQL, Snowflake, BigQuery, Redshift, Databricks, Azure, AWS, GCP, Terraform, dbt, PowerBI, Spark, ETL, CI/CD 🏢 Description: We are #VLteam – tech enthusiasts constantly striving for growth. The team is our foundation, that’s why we care the most about the friendly atmosphere, a lot of self-development opportunities and good working conditions. Trust and autonomy are two essential qualities that drive our performance. We simply believe in the idea of ​​“measuring outcomes, not hours”. Join us & see for yourself! About the role The majority of these roles will be at the forefront of client collaboration and building VL positions in the industry (spearheading projects). You will work closely and directly with a different specialist from the client side. Collaborate with stakeholders to define requirements, develop data pipelines and data quality metrics. You will participate in defining the requirements and architecture for the new platform, implement the solution, and remain involved in its operations and maintenance post-launch Your work will also introduce data governance and management, laying the foundation for accurate and comprehensive reporting that was previously impossible. Build data ingestion & processing pipelines. All of the above with a strong focus on the customer’s needs. Flexibility in action and the ability to overcome obstacles are highly valued in this role. View available projects: Project Data Foundation & AI Enablement Project Scope We are architecting a modern Data Platform for a fast-scaling client in the Insurance sector. Our work consolidates fragmented legacy systems, organises data from a vast number of sources, and establishes a standardised, governed, and future-proof data foundation. We aim to unlock the full value of the company’s data, enabling faster, informed decision-making and providing the backbone for business growth and AI readiness. Tech stack SQL, Python, Snowflake, dbt, Data modelling, Data quality, Power BI, Azure, Terraform Challenges The primary objective is to deliver a robust data foundation and enable AI capabilities for a client that has grown organically. The work focuses on several key areas: Establishing a production-ready, fully operational Snowflake environment and driving operational excellence. Translating complex business logic into accurate data models to ensure the platform truly reflects business reality. Integrating diverse data sources to build reliable data products and comprehensive data dictionaries. Managing the full Data Engineering and Data Science lifecycle to support production ML and AI experimentation. Taking ownership from concept to deployment. Cultivating an engineering mindset by promoting automation, CI/CD, and rigorous standards. Team We are building a small (4-6 people), agile, cross-functional team capable of delivering the complete data platform, from initial architecture to production operations. Roles involved: DevOps, Data Engineer, Snowflake Specialist, MLOps/AI Engineer, Business Analyst (BA). The team will collaborate closely with business stakeholders to ensure effective knowledge transfer and strict alignment with strategic goals. Team The team is small but highly motivated, taking on a broad scope of responsibilities as the platform is built and expanded. What we expect in general A proactive approach and flexibility in action were a must Very good command of English (written and spoken) Hands-on experience with Python Proven experience with data warehouse solutions (e.g., BigQuery, Redshift, Snowflake) Experience with Databricks or data lakehouse platforms Strong background in data modelling, data catalogue concepts, data formats, and data pipelines/ETL design, implementation and maintenance Ability to thrive in an Agile environment, collaborating with team members to solve complex problems with transparency Experience with AWS/GCP/Azure cloud services, including: GCS/S3/ABS, EMR/Dataproc, MWAA/Composer or Microsoft Fabric, ADF/AWS Glue Experience in ecosystems requiring improvements and the drive to implement best practices as a long-term process Experience with Infrastructure as Code practices, particularly Terraform, is an advantage Proactive approach Don’t worry if you don’t meet all the requirements. What matters most is your passion and willingness to develop. Apply and find out! A few perks of being with us Building tech community Flexible hybrid work model Home office reimbursement Language lessons MyBenefit points Private healthcare Training Package Virtusity / in-house training And a lot more! Apply now

🏢 Summary: Design and build a modern Data Platform from scratch for an insurance client, establishing a governed, production-ready Snowflake environment and enabling AI capabilities. The role covers full lifecycle ownership from architecture and data modelling to pipeline implementation and post-launch operations. You will develop scalable data ingestion and processing solutions while promoting best practices, automation, and CI/CD standards. 🗂️ Requirements: Hands-on experience with Python, Proven experience with data warehouse solutions (Snowflake, BigQuery or Redshift), Experience with Databricks or data lakehouse platforms, Strong expertise in data modelling and ETL/pipeline design, Experience with cloud platforms (AWS, GCP or Azure), Experience with cloud data services (S3, GCS, ABS, EMR, Dataproc, MWAA, Composer, ADF or AWS Glue), Ability to design and maintain data quality and governance standards, Experience working in Agile environments 📃 Skills: Python, SQL, Snowflake, Databricks, BigQuery, Redshift, Azure, AWS, GCP, Terraform, dbt, Spark, PowerBI, ADF, Glue, EMR, Dataproc, MWAA, Composer 🏢 Description: We are #VLteam – tech enthusiasts constantly striving for growth. The team is our foundation, that’s why we care the most about the friendly atmosphere, a lot of self-development opportunities and good working conditions. Trust and autonomy are two essential qualities that drive our performance. We simply believe in the idea of ​​“measuring outcomes, not hours”. Join us & see for yourself! About the role The majority of these roles will be at the forefront of client collaboration and building VL positions in the industry (spearheading projects). You will work closely and directly with a different specialist from the client side. Collaborate with stakeholders to define requirements, develop data pipelines and data quality metrics. You will participate in defining the requirements and architecture for the new platform, implement the solution, and remain involved in its operations and maintenance post-launch Your work will also introduce data governance and management, laying the foundation for accurate and comprehensive reporting that was previously impossible. Build data ingestion & processing pipelines. All of the above with a strong focus on the customer’s needs. Flexibility in action and the ability to overcome obstacles are highly valued in this role. View available projects: Project JetBrains Projectt scope The client is introducing Atlan as a new internal Data Catalogue solution and uses Glean as a company-wide unified search platform for thousands of employees. To ensure a smooth transition from our existing Knowledge Base and OpenMetadata setup, we need to index Atlan assets into Glean so that metadata for databases, tables, metrics, and reports is easily discoverable through search. Tech stack Python,  System & Data Integration, Kubernetes, System design, Infrastructure mindset Skills We’re looking for a Data Platform Engineer with experience in data platforms and system design at scale. We expect a track record in designing integration architectures for external systems and streamlining data migration/ingestion. As a Data Platform Engineer, you will design and implement a solution that: Periodically indexes Atlan metadata assets into Glean, runs on a configurable schedule (hourly/daily), is production-ready, observable, and maintainable by our DevOps team after handover. Moreover, ensure compliance and data governance at the appropriate level in line with the company’s standards. What we expect in general A proactive approach and flexibility in action were a must Very good command of English (written and spoken) Hands-on experience with Python Proven experience with data warehouse solutions (e.g., BigQuery, Redshift, Snowflake) Experience with Databricks or data lakehouse platforms Strong background in data modelling, data catalogue concepts, data formats, and data pipelines/ETL design, implementation and maintenance Ability to thrive in an Agile environment, collaborating with team members to solve complex problems with transparency Experience with AWS/GCP/Azure cloud services, including: GCS/S3/ABS, EMR/Dataproc, MWAA/Composer or Microsoft Fabric, ADF/AWS Glue Experience in ecosystems requiring improvements and the drive to implement best practices as a long-term process Experience with Infrastructure as Code practices, particularly Terraform, is an advantage Proactive approach Don’t worry if you don’t meet all the requirements. What matters most is your passion and willingness to develop. Apply and find out! A few perks of being with us Building tech community Flexible hybrid work model Home office reimbursement Language lessons MyBenefit points Private healthcare Training Package Virtusity / in-house training And a lot more! Apply now

🏢 Summary: 6-month on-site contract for a Platform Software Engineer to build and operate a production-grade application platform for a global AI product. The role covers the full lifecycle from deployment to runtime, ensuring reliability, scalability, and performance of distributed systems. You will evolve infrastructure and core platform services into a modular, high-performing architecture. 🗂️ Requirements: 6+ years in software engineering or platform/infrastructure roles, Strong experience with distributed systems, Experience with platform engineering, SRE, or infrastructure operations, Experience with multitenant environments, Experience with container orchestration, Experience working with external vendors and managed services, Experience operating production systems with focus on uptime and scalability 📃 Skills: Kubernetes, AWS, GCP, Cloudflare, Go, Rust, React, TypeScript, ClickHouse, BigQuery, Firestore, Spanner, Terraform, CI/CD, DNS, SSL 🏢 Description: emagine is looking for a Platform Software Engineer to one of the most exciting AI companies in Stockholm. Start: ASAP Length: 6 months with possible extension Location: Stockholm on-site 5 days per week About the role You will play a key role in building and operating the platform that runs applications in production. This includes the full lifecycle from deployment to runtime, ensuring reliability, scalability, and performance across a global user base. The platform handles everything behind the scenes when an application is launched: infrastructure provisioning, authentication, storage, logging, usage metering, and domain management. As part of a growing team, you will help evolve this platform into a more modular, scalable, and high-performing architecture. Key responsibilities Own and improve the application hosting and deployment pipeline Build and operate the runtime that serves applications in production Manage and evolve core platform services such as storage, logging, and workflows Design and maintain infrastructure for custom domains, including DNS and SSL at scale Evaluate, onboard, and migrate third-party services as part of a move towards best-of-breed architecture Ensure operational excellence through monitoring, alerting, incident management, and capacity planning Collaborate with vendors and ensure high service quality and SLA adherence What we are looking for Strong experience building and operating distributed systems Around 6+ years of experience in software engineering or platform/infrastructure roles Background in platform engineering, SRE, or infrastructure operations Experience with multitenant environments, container orchestration (e.g. Kubernetes), or edge runtimes Experience working with external vendors and managed services Strong operational mindset with focus on uptime, performance, scalability, and cost efficiency Nice to have Experience building large-scale multitenant control planes Experience with modern edge platforms (e.g. Cloudflare ecosystem) Contributions to cloud infrastructure or CNCF-related technologies Experience with log analytics platforms such as ClickHouse Familiarity with managed database services Proven track record of cost optimization in infrastructure Tech stack (examples) Frontend: React, Typescript Backend: Go, Rust Cloud: AWS, GCP, Cloudflare Data: ClickHouse, BigQuery, Firestore, Spanner DevOps: Kubernetes, Terraform, CI/CD, observability tooling