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Location: Hong Kong Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. Your future role within QRT Building global and scalable Data Lakehouse solution used by multiple trading desks at QRT Contributing into software and infrastructure design and implementation in AWS cloud environment Developing data pipelines in Python using data libraries and cloud SDKs Data modelling within scope of Data Lake and OLAP - large volumes and highly concurrent data access Optimizing performance of the data lake as well as OLAP databases in cross-region environment Ensuring data completeness and quality across critical pipelines Build and support tailored data solutions for Quants and Traders Your present skillset 5+ year of experience and proven track record of building data platforms Python and SQL mastery are essential, C++ is a big plus Appetite to contribute into cloud infrastructure Ability to build a structured approach to problem-solving Independent and autonomous while still a strong team player Intellectual curiosity to learn rapidly Finance experience is highly desirable QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Location: New York, Chicago, or Remote CCC Intelligent Solutions Inc. (CCC) is a leading cloud platform for the multi-trillion-dollar insurance economy , creating intelligent experiences for insurers, repairers, automakers, part suppliers, and more. At CCC, we’re making life just work by empowering more than 35,000 businesses with industry-leading technology to get drivers back on the road and to health quickly and seamlessly. We’re pushing boundaries with innovative AI solutions that simplify and enhance the claims and repair journey. Through purposeful innovation and the strength of its connections, CCC technologies empower the people and industry relied upon to keep lives moving forward when it matters most. Learn more about CCC at www.cccis.com . The Role As a Senior Software Engineer - Agentic you will build the event-driven systems that keep claims moving for our customers, connecting our AI agents to the rest of CCC. When these systems work, claims move faster and the machinery stays invisible. Agentic coding tools are how you move fast. What you add is what they are worst at: distributed-systems design, correctness when things fail partway, and the debugging nobody else gets to the bottom of. You own a product area end to end and define the reliability bar it ships against. Salary range is: $180,000 - 225,000 This position is bonus eligible. Key Responsibilities: Own the delivery of backend services, built in Python and TypeScript, from an ambiguous problem, scoped with product managers and data scientists, through production operation. Build and operate durable, event-driven, multi-tenant systems in which agents run as steps inside deterministic workflows, designing their failure modes, replay semantics, and cost profile before they show up under load. Own tracing and audit for your area: every model call and agent step recorded, so any recommendation can be reconstructed and cited back to its sources by on-call and auditors alike. Own how claims automation data is modeled and managed across our relational, document, and graph stores. Ensure the security and isolation of sensitive data. Author the design documents for complex systems to get feedback and buy-in, review other engineers' designs and code with the same care, and mentor the engineers in your area. Raise the bar for how the team works with agentic coding tools: sharpen the specifications, instruction files, hooks, and permission policies they run under, and hold generated code to the same review standard before it merges. Take part in a shared on-call rotation for the systems you own. Requirements: 6+ years of professional software engineering experience, including an event-driven system you designed, shipped to customers, and ran in production. Python and TypeScript at the level of setting a team's conventions, plus a background in a systems language such as Rust, Go, Java, or C#. Strong computer science and distributed-systems fundamentals you use at work: concurrency, consistency, ordering, and how systems fail. Event-driven systems built on a broker such as Kafka, Azure Event Hubs, or Service Bus that handle duplicate, late, and failed events without losing or double-processing work. Data modeling and development across relational, document, and graph databases such as PostgreSQL, MongoDB, and Neo4j, including when each type fits and the partition-key, consistency, and tenant-isolation calls you made. Systems architected and operated on Azure or AWS, with CI/CD and infrastructure as code, and hands-on time with a durable workflow engine such as Temporal or the Durable Task Scheduler. A clear account of how you constrain an agentic coding tool's context and verify its output, from daily use of Claude Code, Cursor, GitHub Copilot, or similar on production work, plus changes you turned back, and why. Technical design documents you have authored for systems that span more than one team, used to get feedback and buy-in before building, and that those teams then built to. Clear writing and discussion for technical and non-technical audiences: drawing out a customer's real problem and explaining the trade-offs back to them. Even Better if You Have: React and TypeScript experience, so you can deliver a full-stack feature end to end, especially chat, streaming, and citation-heavy AI experiences. Formal methods or fault-injection testing, such as Lean, TLA+, or deterministic simulation. Performance work below the application layer: profiling, memory, and concurrency tuning. Familiarity with how AI agents reach their tools and enterprise systems, through the Model Context Protocol (MCP), the Agent2Agent (A2A) protocol, command-line tools, and microservices. Exposure to the insurance, claims, or automotive repair domains. What Success Looks Like: In your first six months, services you built run in production against SLOs you set, and you can show they held as load grew. You are trusted with the hardest correctness and scale problems, and you turn them into a design, a shipped system, and a number you can put in front of a customer. You are energized by what agentic coding tools make possible. Your team ships more than its headcount suggests, and your specifications and reviews are why the output survives production. You have a passion for systems that last: failures are designed for in advance, and when one happens anyway, the trace says exactly where. Standards you set for reliability, reviews, and design documents outlive the project they started on. Engineers you mentor ship reliable services without your direct involvement. You enjoy getting a product manager, a data scientist, and a customer's team into one room and coming out with a single agreed scope, and you can argue a position without needing to win it. You embrace our ambitious, collaborative, and empathetic values, and you like problems where the answer has to be measured rather than argued. Interview Policy & Privacy Notice: A video interview is required for this position. Video interviews are transcribed. Transcriptions are retained and may be reviewed by CCC and our recruiters. Candidates are not permitted to use generative AI or automated assistance during the interviews unless explicitly allowed by the interview team for a specific exercise. Our Job Applicant Privacy Notice is available HERE . About CCC's Commitment to Employees: CCC Intelligent Solutions understands that our employees play an integral role in our vision to shape a world where life just works. Our team is defined by our values of Integrity, Customer-Focus, Innovation, Inclusion & Diversity, Tenacity, and Connection. Through diverse perspectives, purposeful innovation, and the strength of connections, our technologies empower the people and industry relied upon to keep lives moving forward when it matters most. At CCC, together everyone can thrive as we innovate and collaborate, creating employee experiences that just work. We are committed to providing opportunities for our people to make real-life impacts, advance in their careers, and contribute to CCC’s success. CCC offers competitive compensation and benefits to support you and your families, including: 401K Match Paid time off Annual Incentive Plan Performance Bonus Comprehensive health insurance Adoption Assistance Tuition Reimbursement Wellness Programs Stock Purchase Plan options Employee Resource Groups For more information about our benefits, please check out our careers site . Here, you belong. You are seen, valued, and respected. We celebrate you for who you are and all you bring. Every voice is heard and is important to our success. You can hear what employees have to say about our culture here

Location: San Francisco, CA | New York City, NY 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 Platform Intelligence turns each new Claude model's abilities into API features that developers can build on. Our goal is to make the full intelligence of each model available through the API. We own the capabilities that shape what Claude can do for developers: tool use, built-in tools such as web search and code execution, thinking controls, structured outputs, and the memory, files, and skills APIs. We also run the API side of every Claude model launch, including its safety features and controls. That means getting the API ready for each new model, coordinating with research, safeguards, product, and cloud partners, and making sure the model, its features, the SDKs, and the docs all ship together on launch day. The work sits where research meets product. We work with new models before they are public. When a model gains a new ability, we work out what it should look like as an API, build it, and ship it to developers on our own platform and on cloud platforms. Those decisions shape how developers first use each model. We also own API versioning and the evals that tell us a capability works in production. What you'll do You'll lead the design, build, and operation of API capabilities used by developers around the world. You'll work with research to understand what a new model can do and turn that into an interface that is simple, durable, and hard to misuse. You'll lead the API side of new model launches. You'll plan the work, track readiness across teams, resolve the issues that come up late, and see the launch through on the day. Between launches, you'll make the next one faster and safer. You'll set technical direction for work that spans several teams, write clear design proposals, review API designs from other teams, and mentor engineers on the team. Representative projects Lead API readiness for a Claude model launch, so that every feature works on day one across our API, SDKs, docs, and cloud partners Take a new model ability from research prototype to public API feature, from interface design to production rollout Build and operate tools such as web search and code execution under real traffic Automate the manual parts of a model launch Build the evals that catch a capability regression before a launch You might be a good fit if you: Have led technical projects that spanned several teams, from design through launch and operation Have designed and operated production distributed systems where correctness, latency, and availability all matter Have strong product sense and care about API design and developer experience Make sound technical decisions with incomplete information, as models and priorities change close to a launch Explain tradeoffs clearly to research, product, and go-to-market partners, including non-engineers Make the engineers around you better through design review and mentoring Use AI tools as a regular part of how you design, build, and review software Care about the societal impacts of your work and Anthropic's mission to build safe, beneficial AI Strong candidates may also have: Building public APIs, SDKs, or developer platforms Working with large language models, including tool use, agents, or evals Running launches or migrations with fixed deadlines and many dependent teams Building tools for agents, such as search or code execution Storage, memory, or context systems at scale Integrating with cloud platforms such as AWS, Google Cloud, and Azure Deadline to apply: None. Applications will be reviewed on a rolling basis. Location Preference: Preference will be given to candidates based in NY, SEA, SF or the Bay Area given the current location of team. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco; New York City In 2026, we launched Computer, the defining product for the new era of agentic AI. Millions of people and teams adopt Perplexity and Computer on their own, and the Growth team owns the loops that turn that adoption into lasting usage and revenue. We're hiring a Growth GTM Engineer to build the systems that turn product usage into revenue and turn self-serve usage into enterprise pipeline. You'll turn first-party Computer and Enterprise usage into account-level signals. You'll ship the in-product paths that capture sales intent, and build and validate those signals with data science. Alongside product engineers, you ship production code, instrument the product and run experiments. You'll partner closely with Revenue Operations, who own Salesforce, CPQ, routing and sales reporting. Tech Stack: TypeScript | Next.js | React | Python | PostgreSQL | Snowflake | Eppo | AWS WHY PERPLEXITY IS DIFFERENT - Craftsmanship. We build high quality, tasteful products targeting both the AI native and AI curious. - Ownership. You identify the problem, design the solution and ship it. - Entrepreneurship. We think like founders, act with urgency, and hustle to deliver for each other and our users. - Scholarship. Work among highly talented peers, pursuing knowledge and truth, upleveling ourselves, our teams, and our products. - Partnership. We amplify each others' strengths, break down silos, and give selflessly to help our colleagues deliver excellence. WHAT YOU'LL DO - Build account-level PLG signals: map users and workspaces to accounts, and define the activation, expansion and intent signals that predict an enterprise deal. Publish them as trusted models that sales use for scoring and routing. - Own the in-product paths from self-serve to sales, like contact-sales entry points, high-intent upsells and meeting booking, across web and app. Decide who sees them, when and with what context, and measure them end to end, from surface to booked meeting to pipeline. - Lead experiments end to end on sales-assist surfaces and targeting, from hypothesis and instrumentation through analysis and rollout. Partner with Data Science to measure meetings and qualified opportunities, not just clicks. - Build the internal tools and automation Growth and GTM teams run on - Partner closely with Sales, Sales Systems, Data Science, Marketing and Product to turn product signals into pipeline. Be upstream partner to sales systems that own Salesforce, CPQ and routing QUALIFICATIONS - 2+ years as a growth, GTM, data or full-stack engineer, shipping production code (TypeScript/React, Python). - Strong SQL and comfort building data models in a warehouse (Snowflake, dbt-style). - Experience instrumenting product events and running A/B experiments end to end. - Commercial instinct: you start from a revenue problem ("trial-to-enterprise conversion won't move") and work back to the signal or surface that fixes it. - Comfort with REST APIs, webhooks and integrating third-party GTM tools. - Operator mindset: you talk to customers directly, ship fixes, and don't need a PM to translate requests. NICE TO HAVE - Experience in a PLG-to-enterprise motion: product-qualified leads, scoring users into accounts, sales-assist flows. - Experience as a GTM or growth engineer at a B2B SaaS or GTM-tooling company. - Entity resolution, dedup or domain enrichment. - Familiarity with Salesforce, Default, Chili Piper, Intercom, Clay, Hightouch/Polytomic or similar (as a consumer and integrator, not an admin). - Experience building LLM-powered internal tools or agents.

Location: San Francisco; New York City In 2026, we launched Computer, the defining product for the new era of agentic AI. Millions of people and teams adopt Perplexity and Computer on their own, and the Growth team owns the loops that turn that adoption into lasting usage and revenue. We're hiring a Growth GTM Engineer to build the systems that turn product usage into revenue and turn self-serve usage into enterprise pipeline. You'll turn first-party Computer and Enterprise usage into account-level signals. You'll ship the in-product paths that capture sales intent, and build and validate those signals with data science. Alongside product engineers, you ship production code, instrument the product and run experiments. You'll partner closely with Revenue Operations, who own Salesforce, CPQ, routing and sales reporting. Tech Stack: TypeScript | Next.js | React | Python | PostgreSQL | Snowflake | Eppo | AWS WHY PERPLEXITY IS DIFFERENT - Craftsmanship. We build high quality, tasteful products targeting both the AI native and AI curious. - Ownership. You identify the problem, design the solution and ship it. - Entrepreneurship. We think like founders, act with urgency, and hustle to deliver for each other and our users. - Scholarship. Work among highly talented peers, pursuing knowledge and truth, upleveling ourselves, our teams, and our products. - Partnership. We amplify each others' strengths, break down silos, and give selflessly to help our colleagues deliver excellence. WHAT YOU'LL DO - Build account-level PLG signals: map users and workspaces to accounts, and define the activation, expansion and intent signals that predict an enterprise deal. Publish them as trusted models that sales use for scoring and routing. - Own the in-product paths from self-serve to sales, like contact-sales entry points, high-intent upsells and meeting booking, across web and app. Decide who sees them, when and with what context, and measure them end to end, from surface to booked meeting to pipeline. - Lead experiments end to end on sales-assist surfaces and targeting, from hypothesis and instrumentation through analysis and rollout. Partner with Data Science to measure meetings and qualified opportunities, not just clicks. - Build the internal tools and automation Growth and GTM teams run on - Partner closely with Sales, Sales Systems, Data Science, Marketing and Product to turn product signals into pipeline. Be upstream partner to sales systems that own Salesforce, CPQ and routing QUALIFICATIONS - 2+ years as a growth, GTM, data or full-stack engineer, shipping production code (TypeScript/React, Python). - Strong SQL and comfort building data models in a warehouse (Snowflake, dbt-style). - Experience instrumenting product events and running A/B experiments end to end. - Commercial instinct: you start from a revenue problem ("trial-to-enterprise conversion won't move") and work back to the signal or surface that fixes it. - Comfort with REST APIs, webhooks and integrating third-party GTM tools. - Operator mindset: you talk to customers directly, ship fixes, and don't need a PM to translate requests. NICE TO HAVE - Experience in a PLG-to-enterprise motion: product-qualified leads, scoring users into accounts, sales-assist flows. - Experience as a GTM or growth engineer at a B2B SaaS or GTM-tooling company. - Entity resolution, dedup or domain enrichment. - Familiarity with Salesforce, Default, Chili Piper, Intercom, Clay, Hightouch/Polytomic or similar (as a consumer and integrator, not an admin). - Experience building LLM-powered internal tools or agents.

Location: Montevideo, Uruguay; Remote.AR, Remote.LATAM-country; Remote.BR, Brazil; Remote.CO, Colombia; Rosario, Remote.LATAM-country We are looking for an experienced Senior Developer who combines strong React frontend skills with robust Python/Django backend expertise. This role offers the opportunity to work on cutting-edge solutions that are transforming the real estate technology sector. The ideal candidate will help build and optimize full-stack applications that enhance the apartment leasing experience for property managers and renters alike. Our client values proactive team members who are eager to dive deep into the multifamily real estate domain, understand the unique challenges of property management, and actively contribute to solving complex business problems. You’ll be expected to go beyond just coding to truly understand the client’s field, engage with their business challenges, and take ownership of delivering solutions that make a real impact. DataArt is seeking a talented Senior Full-Stack Developer with strong React and Python expertise to join our team for an exciting project with our client, a leading proptech company that is revolutionizing the apartment rental process through innovative technology solutions. Our client provides AI-powered leasing automation, renter communication tools, and operational intelligence for multifamily property management companies. They are at the forefront of digital transformation in real estate, helping property managers streamline operations, enhance renter experiences, and make data-driven decisions through cutting-edge technology that automates routine tasks and provides actionable insights. Design responsive and user friendly web applications using React.js and modern JavaScript Build and maintain backend services using Python and Django Create reusable React components and implement state management solutions Develop and optimize RESTful APIs and microservices architecture Ensure integration between frontend and backend systems Collaborate with UX UI designers to implement accessible interfaces Optimize application performance for fast load times and smooth user interactions Identify opportunities for product improvement and innovation Analyze the property management domain to understand user needs and pain points Ensure code quality, performance, and security practices across the full stack 5 plus years of professional experience in full-stack development Experience with React.js, including hooks, Context API, and modern React patterns Proficiency in JavaScript, TypeScript, HTML5, CSS3, and responsive design Experience with Python and Django for backend development Experience with state management libraries such as Redux, MobX, or Context API Understanding of RESTful service architecture and API design Experience with frontend build tools such as Webpack, Vite, or similar tools Familiarity with frontend testing frameworks such as Jest and React Testing Library Experience with Git and CI CD pipelines Ability to solve technical problems with attention to detail Ability to understand business context and domain specifics Communication skills for working in a distributed team environment English proficiency at B2 level or higher Experience with LLM API providers such as OpenAI and Anthropic Knowledge of LangSmith or similar AI ML observability tools Experience in the PropTech or Real Estate industry Knowledge of cloud platforms such as AWS, Azure, or GCP Experience with containerization using Docker and Kubernetes Familiarity with GraphQL Experience with Next.js or other React frameworks Knowledge of UI UX design principles and tools such as Figma and Sketch Experience working with stakeholders to gather requirements and translate them into technical solutions

Location: Bengaluru, India We are looking for a Senior Data QE Engineer with solid experience in ETL testing and data validation, and strong SQL skills. You will design and run data quality tests, validate pipelines end to end, reconcile source and analytical data, and give engineering and business teams evidence for release decisions. You will also automate comparisons in Python, work with Airflow pipeline runs, and use AWS and Grafana to observe pipeline health. You will use an AI coding assistant to analyze data and author SQL, Python, and quality checks, and you will review generated output before it is used. This position is intended for Hyderabad-based candidates who are available to work from the office. The client runs a large application landscape and the analytical datasets behind it. Data moves from PostgreSQL sources on AWS into Snowflake through orchestrated pipelines. Quality for that data is part of delivery: test design, checks on movement and transformation, quality metrics, and practical help when data has to be corrected. Data QE engineers own that hands-on work for data moving from source systems into analytical datasets, from test design through execution, investigation, and release-readiness reporting. Own data quality for data moving from source systems into analytical datasets, from test design through execution, investigation, and reporting. Design, implement, and execute data quality tests, and publish quality metrics and dashboards that producing and consuming groups can use. Validate pipelines end to end, covering movement, transformation, completeness, history, freshness, and compliance. Write reconciliation, drift, and quality SQL on Snowflake layered models (raw, history, silver, and gold), including slowly changing dimensions and merge behavior. Validate PostgreSQL sources with consistent snapshot counts and checks that logical replication kept the expected data. Use logical and physical data models and data contracts to assess downstream impact and set quality coverage. Automate data comparison and reconciliation in Python with pytest, and keep the checks in GitHub. Trigger pipeline runs in Airflow and read task results into the quality verdict. Investigate quality issues and support remediation with the groups that produce and consume the data. Design failover, outage, and volume tests and judge the evidence, including recovery time and recovery point. The platform team executes destructive and chaos tests. Run read-only checks in pre-production and production. Integrate quality checks with CI/CD on GitHub Actions or an equivalent tool. Use AWS and Grafana to observe pipeline health, including CloudWatch metrics, secrets metadata, and container platform state. Check classification, masking, and retention against the stated data rules. Track defects to closure in Jira and keep test cases and results in TestRail. Provide quality evidence, risks, and readiness input for releases. Use an AI coding assistant to analyze data and author SQL, Python, and quality checks, and review generated output before it is used. Senior-level data quality engineering experience in ETL testing and data validation. Strong SQL and Snowflake data-modelling experience, including layered raw, history, silver, and gold models, reconciliation and drift queries, and slowly changing dimensions and merge behavior. Experience with logical and physical data models and with assessing the downstream impact of schema and data-contract changes. Experience validating PostgreSQL sources, including consistent snapshot counts and logical replication. Hands-on Python automation for data comparison and reconciliation, using pytest or an equivalent framework. Experience running and reading orchestrated pipelines in Airflow or an equivalent scheduler. Experience validating data movement, transformation, completeness, history, freshness, and compliance from source systems into analytical datasets. Experience diagnosing data quality issues and supporting remediation. Experience integrating data quality checks with CI/CD using GitHub Actions or equivalent tools. Experience with test management and defect tracking in TestRail and Jira. Working knowledge of AWS and Grafana for pipeline observation, including CloudWatch, secrets management, and container platforms. Experience designing resilience tests and judging evidence for failover, outage, volume, and recovery objectives. Working knowledge of data classification, masking, and retention checks. Experience producing data quality metrics, reports, and dashboards. Experience with risk-based testing in Agile or Kanban teams. Hands-on use of AI coding assistants (Cursor, GitHub Copilot, Claude Code, Codex, or equivalent) to author SQL, Python, and quality checks, with human review of generated output. Ability to communicate clearly with engineering and business stakeholders. Experience providing quality evidence, risks, and readiness input for releases. Experience observing Snowflake Openflow or NiFi connector state well enough to recognize a stalled load. Experience with custom cross-table data quality checks that publish results for dashboarding. Familiarity with GenAI, LLMs, and agentic workflows for maintaining data quality checks. Familiarity with RAG and MCP concepts for QE tooling and for generating test data. Knowledge of AI-driven test optimization and coverage analytics (SeaLights or equivalent). Experience with service virtualization using WireMock or an equivalent tool, so checks can run when a dependency is unavailable. Experience specifying and reviewing dbt tests. Developers author those tests.

Location: Ho Chi Minh City, Vietnam Position Overview As a Senior/ DevOps Engineer, you will scale, and secure our hybrid cloud and on-premises infrastructure across AWS and private bare-metal/virtualized environments. In this role, you will champion an AI-first paradigm—integrating AI tooling into root-cause analysis, proactive observability, automated incident response, and continuous deployment workflows. You will partner closely with engineering teams to streamline delivery pipelines, drive zero-downtime reliability, and ensure our mission-critical custody platforms operate at peak performance and bank-grade security. Duties & Responsibilities Architect, provision, and maintain multi-region AWS cloud environments alongside on-premises virtualized infrastructure using declarative Infrastructure-as-Code (Terragrunt). Manage, harden, and scale production-grade Kubernetes clusters, implementing advanced ingress controllers, service mesh, Helm/Kustomize packages, and GitOps pipelines (ArgoCD, Crossplane). Deploy, administrate, and maintain dedicated blockchain nodes (RPC, validator, archive, and sentry nodes across multiple Layer 1 and Layer 2 protocols), ensuring data synchronization, high availability, and network health. Enforce cloud and container security controls, including fine-grained Kubernetes network policies, IAM least-privilege models, secrets management, Kubernetes, linux and AWS security control and automated vulnerability scanning across delivery pipelines. Integrate AI and AIOps tooling into observability suites to deliver intelligent anomaly detection, automated log parsing, and rapid root-cause analysis. Performance tune microservices and cloud workloads to handle spikes in high-volume, low-latency financial transactions with high availability. Requirements 6–10 years of experience in Linux/Unix systems engineering, cloud architecture, and modern DevOps/SRE practices. Kubernetes Mastery : Production-grade expertise deploying and managing Kubernetes clusters (EKS / bare-metal), Helm, Kustomize, service mesh, and GitOps tooling (ArgoCD). Infrastructure as Code (IaC) : Deep hands-on experience using Terraform, Terragrunt, following modular, DRY configuration patterns. Programming & Automation : Able to understand at least one modern programming language with harness engineering skills. Cloud & Hybrid Compute: Extensive production experience in AWS, paired with practical exposure to on-prem virtualization platforms (e.g., Proxmox, VMware ESXi, or KVM). Deep Networking Knowledge: Strong grasp of OSI layer fundamentals (TCP/UDP, BGP, DNS, TLS/mTLS, HTTP/gRPC) and comfort debugging live traffic issues on the wire (tcpdump, Wireshark, eBPF). Databases & State: Operational familiarity with relational databases and middleware (PostgreSQL, MariaDB/MySQL, Mongodb, Redis, Kafka), including replication, failover strategies, and backup pipelines. Eligible to work in Vietnam. Bonus Experience Hands-on experience in cybersecurity practices (e.g., threat modeling, penetration testing remediation, SOC 2/ISO 27001 compliance standards, or managing HSM/KMS cryptographic infrastructure). Direct experience running, securing, and maintaining blockchain nodes (e.g., Ethereum, Bitcoin, EVM/Cosmos-based chains, or Solana). Benefits As one of the leading Web3 innovators, Hex Trust offers a front-row seat in the ever-changing blockchain & crypto industry. We genuinely believe that people are our greatest asset, and invest heavily so they’re best prepared to support our mission to unlock ownership in decentralized markets! You will be joining a company that is always committed to creating a supportive & inclusive environment that promotes personal and professional growth that furthers your success and drives innovation, collaboration, and passion in the blockchain space. At Hex Trust, we are proud of our H.E.X. culture: H eart E mpowerment X cellence Join us at Hex Trust and not only can you look forward to working with blockchain professionals to build the decentralized future, but also: Generous Amounts of Paid Time Off (incl. leave for Birthdays, Work Anniversary, and Mental Health etc.) Access to Corporate Discounts and exclusive Employer Perks Medical & Retirement Plans Professional Learning and Development Opportunities Elevate your work using cutting-edge technology Fun & friendly office spaces Regular company & social events

Location: Canada What The Role Is We're hiring a Staff MLE for the Discovery team to own recommendations and personalization across Babylist's consumer experience — the homepage feed, product recs, search, and the ML-powered systems that make registry building feel effortless. Babylist was built on editorial recommendations: products chosen by people with deep baby gear expertise. That editorial foundation is a big part of why millions of families trust us. We're now building ML-powered personalization on top of it, using one of the richest first-party datasets in parenting. We're early in this work, and we have a real mandate. A small Discovery team has initial retrieval and reranking models live on parts of the site and a steady cadence of A/B tests. We are looking for a Staff MLE who has seen personalization done well at scale and can set the technical direction for where we go next. Registry building is the heart of the Babylist product. Every parent builds a list of dozens of products, from swaddle to stroller, with real stakes (a friend or family member is going to buy these things, and a baby is going to use them). As a universal registry, this registry also typically spans many retailers. This makes registry building on Babylist one of the most interesting personalization problems in consumer e-commerce: latent intent, life-stage progression, multi-stakeholder gift dynamics, deep declarative signal in millions of completed registries, cross-retailer datapoints, and a user who genuinely wants help. If you want to join a mature ML org and tune models at the margins, this isn't the right role. If you've worked inside a strong recommendations team, learned what good looks like, and want to build from zero-to-one at a company earlier in the journey, read on. What You'll Own You'll be the technical lead for personalization on the Discovery team, working alongside a PM, Engineering Manager, Senior MLE and fullstack software engineers. You set where our models go over the next year or two, sequence the bets that get there, and stay deep in building. A few examples of the problems you’ll get to shape: Product recommendations across every surface. Product detail pages, add-next recommendations after someone adds to their registry, vibes/aesthetic representations of products and the shared models underneath them. Personalizing the Feed. Deciding which products, editorial content and social content each family sees, and in what order. Personalizing search. Bringing what we know about a family into search results, and helping decide how much search should share retrieval and ranking with recommendations. Making Addie (our AI registry assistant) better at recs. Working with the team behind Addie so its product suggestions draw on the same models and signals as the rest of the site. In practice, you will: Take a fuzzy business problem from first sketch to production model, and own whether it moved the metric. Make the modeling and architecture calls that span surfaces and are expensive to reverse. Design the evaluation, offline and online, that tells us a model is good before and after it ships. Know when a rule or a simple baseline is the right first step, and when it's time to pursue more advanced approaches. Partner with product, design and data to help shape what's worth building. Coach engineers on the team, and more broadly be an ML expert and resource to the wider engineering org. Who You Are You’ve shipped recommendation and/or personalization systems that reached real users at scale within a consumer product, and can point to the business impact of your work. You’ve done this within a team that did ML well — you know what good looks like, and are motivated to bring that to a company earlier in their ML journey. You bring: Expertise in recommender fundamentals: for example, candidate generation vs. ranking, offline vs. online evaluation, cold start solutions, and handling position and popularity bias. Fluency in the Python ML stack and comfort owning models through deployment and monitoring, including contributions to our application backend. An ability to take an ambiguous problem and start moving before anyone hands you the full picture. A builder's instinct for early-stage ML. You understand effort vs. effectiveness tradeoffs and can advocate for when a rule beats a model, or a model is “good enough” for early learnings. An outcome and user focused mindset. You measure yourself by business impact, and you can connect a model change to user experience & registry adds, conversion or revenue. AI-native daily practice. You're already using AI to move faster and improve your output, and you stay curious about what's coming next. Compensation We post real numbers. For a Canada-based Staff Engineer, the starting base salary range is 299,300 to 372,600 CAD plus a target annual bonus of 20 percent of base. That's total target cash of roughly 359,160 to 447,120 CAD. On top of that you get meaningful equity and a 401(k) match. Where you start in that range depends on your experience, and your pay grows from there with performance and scope. How We Build AI is the default here. Engineers run agentic sessions for most of the work, and a lot of the interesting engineering now lives in the scaffolding that makes the agents good: the eval harnesses, the curated context, custom review skills and fast CI. Agents also triage incidents and handle a big share of support. A human always owns the outcome. The architecture is intentionally simple: one Rails monolith, MySQL and few moving parts. That's deliberate. Simple infrastructure lets us move fast and lets AI reason about the whole system, so the hardest problems are the ones in front of customers. The Stack Core app: Rails, Packwerk, React, TypeScript, Sidekiq Mobile: iOS (Swift), Android (Kotlin) Data, search & events: MySQL, Snowflake, dbt, Airflow, Weaviate, WarpStream, Hex, Sigma Machine learning: deep learning, matrix factorization, retrieval & ranking, AWS SageMaker, MLflow AI & dev tooling: Claude Code, Devin, Linear, CodeRabbit, Warden, LangChain, Bedrock AgentCore, Maxim Infra & ops: AWS, Kubernetes, Terraform, GitHub Actions, Datadog, incident.io, LaunchDarkly Key integrations: Shopify (payments), Iterable (CRM) Why Babylist An engineer, expecting her first baby, couldn't find the registry she wanted. So she built it. That's how Babylist started, and it's still how we work: engineers solving problems for families. Becoming a parent is one of the biggest moments in a person's life. Millions reach it for the first time every year, making thousands of decisions and figuring it out as they go. That's who we build for, and we're a long way from done. Ten million people give gifts through Babylist every year. We did more than $750M in revenue in 2025, up 45 percent over the year before, and we've been profitable for eight years while staying independent. So you can take on a hard, multi-year problem without watching over your shoulder for the next round or the next correction. And the team is small, around 65 engineers, so what you ship stays visible and your scope stays wide. How We Work Remote-first across the US and Canada, and we have been for years. That's not changing. We trust you to own your time and your outcomes, and we get everyone in a room together twice a year. Teams are small, pods of three to five engineers, so nothing you ship disappears into a committee. You'll work shoulder to shoulder with product, design and data, and with the partners across the business who rely on what you ship. You'll also stay close to customers yourself: sitting in on user interviews, watching session recordings, riding along with support. Here that's part of the engineering job, on a regular basis. How We Hire Three rounds, usually two to three weeks start to finish. Recruiter conversation (30 minutes). Trade context: what you want next, what we're building and straight answers on comp, team and remote. Technical screen (1 hour). One round, no AI, language-agnostic. Reach for Google when you normally would. We just want to see how you reason from first principles. Final round (4 hours). Four one-hour interviews: system design, AI-assisted coding with the tools you'd actually use here, product sense and culture and values. You'll hear back either way within 24 to 48 hours. If your timeline is tight, tell us and we'll move faster. Benefits Company-paid medical and fully covered dental and vision A 401(k) match Generous paid parental leave for birthing and non-birthing parents, plus a gradual return-to-work program Winter Wonder Week, a paid company-wide week off at the end of the year A remote-work stipend Mental-health and wellness support A Few Things To Know We record and transcribe interviews to evaluate candidates, in line with applicable privacy laws. We expect you to use AI in your work and we welcome it in the process, but what you submit and say should reflect your own thinking. If you have a family member or close relationship with a Babylist employee, let your recruiter know. Official outreach only ever comes from an @babylist.com address

Location: United States What The Role Is We're hiring a Staff MLE for the Discovery team to own recommendations and personalization across Babylist's consumer experience — the homepage feed, product recs, search, and the ML-powered systems that make registry building feel effortless. Babylist was built on editorial recommendations: products chosen by people with deep baby gear expertise. That editorial foundation is a big part of why millions of families trust us. We're now building ML-powered personalization on top of it, using one of the richest first-party datasets in parenting. We're early in this work, and we have a real mandate. A small Discovery team has initial retrieval and reranking models live on parts of the site and a steady cadence of A/B tests. We are looking for a Staff MLE who has seen personalization done well at scale and can set the technical direction for where we go next. Registry building is the heart of the Babylist product. Every parent builds a list of dozens of products, from swaddle to stroller, with real stakes (a friend or family member is going to buy these things, and a baby is going to use them). As a universal registry, this registry also typically spans many retailers. This makes registry building on Babylist one of the most interesting personalization problems in consumer e-commerce: latent intent, life-stage progression, multi-stakeholder gift dynamics, deep declarative signal in millions of completed registries, cross-retailer datapoints, and a user who genuinely wants help. If you want to join a mature ML org and tune models at the margins, this isn't the right role. If you've worked inside a strong recommendations team, learned what good looks like, and want to build from zero-to-one at a company earlier in the journey, read on. What You'll Own You'll be the technical lead for personalization on the Discovery team, working alongside a PM, Engineering Manager, Senior MLE and fullstack software engineers. You set where our models go over the next year or two, sequence the bets that get there, and stay deep in building. A few examples of the problems you’ll get to shape: Product recommendations across every surface. Product detail pages, add-next recommendations after someone adds to their registry, vibes/aesthetic representations of products and the shared models underneath them. Personalizing the Feed. Deciding which products, editorial content and social content each family sees, and in what order. Personalizing search. Bringing what we know about a family into search results, and helping decide how much search should share retrieval and ranking with recommendations. Making Addie (our AI registry assistant) better at recs. Working with the team behind Addie so its product suggestions draw on the same models and signals as the rest of the site. In practice, you will: Take a fuzzy business problem from first sketch to production model, and own whether it moved the metric. Make the modeling and architecture calls that span surfaces and are expensive to reverse. Design the evaluation, offline and online, that tells us a model is good before and after it ships. Know when a rule or a simple baseline is the right first step, and when it's time to pursue more advanced approaches. Partner with product, design and data to help shape what's worth building. Coach engineers on the team, and more broadly be an ML expert and resource to the wider engineering org. Who You Are You’ve shipped recommendation and/or personalization systems that reached real users at scale within a consumer product, and can point to the business impact of your work. You’ve done this within a team that did ML well — you know what good looks like, and are motivated to bring that to a company earlier in their ML journey. You bring: Expertise in recommender fundamentals: for example, candidate generation vs. ranking, offline vs. online evaluation, cold start solutions, and handling position and popularity bias. Fluency in the Python ML stack and comfort owning models through deployment and monitoring, including contributions to our application backend. An ability to take an ambiguous problem and start moving before anyone hands you the full picture. A builder's instinct for early-stage ML. You understand effort vs. effectiveness tradeoffs and can advocate for when a rule beats a model, or a model is “good enough” for early learnings. An outcome and user focused mindset. You measure yourself by business impact, and you can connect a model change to user experience & registry adds, conversion or revenue. AI-native daily practice. You're already using AI to move faster and improve your output, and you stay curious about what's coming next. Compensation We post real numbers. For a US-based Staff Engineer, the starting base salary range is $233,500 to $290,700, plus a target annual bonus of 20 percent of base. That's total target cash of roughly $280,200 to $348,840. On top of that you get meaningful equity and a 401(k) match. Where you start in that range depends on your experience, and your pay grows from there with performance and scope. How We Build AI is the default here. Engineers run agentic sessions for most of the work, and a lot of the interesting engineering now lives in the scaffolding that makes the agents good: the eval harnesses, the curated context, custom review skills and fast CI. Agents also triage incidents and handle a big share of support. A human always owns the outcome. The architecture is intentionally simple: one Rails monolith, MySQL and few moving parts. That's deliberate. Simple infrastructure lets us move fast and lets AI reason about the whole system, so the hardest problems are the ones in front of customers. The Stack Core app: Rails, Packwerk, React, TypeScript, Sidekiq Mobile: iOS (Swift), Android (Kotlin) Data, search & events: MySQL, Snowflake, dbt, Airflow, Weaviate, WarpStream, Hex, Sigma Machine learning: deep learning, matrix factorization, retrieval & ranking, AWS SageMaker, MLflow AI & dev tooling: Claude Code, Devin, Linear, CodeRabbit, Warden, LangChain, Bedrock AgentCore, Maxim Infra & ops: AWS, Kubernetes, Terraform, GitHub Actions, Datadog, incident.io, LaunchDarkly Key integrations: Shopify (payments), Iterable (CRM) Why Babylist An engineer, expecting her first baby, couldn't find the registry she wanted. So she built it. That's how Babylist started, and it's still how we work: engineers solving problems for families. Becoming a parent is one of the biggest moments in a person's life. Millions reach it for the first time every year, making thousands of decisions and figuring it out as they go. That's who we build for, and we're a long way from done. Ten million people give gifts through Babylist every year. We did more than $750M in revenue in 2025, up 45 percent over the year before, and we've been profitable for eight years while staying independent. So you can take on a hard, multi-year problem without watching over your shoulder for the next round or the next correction. And the team is small, around 65 engineers, so what you ship stays visible and your scope stays wide. How We Work Remote-first across the US and Canada, and we have been for years. That's not changing. We trust you to own your time and your outcomes, and we get everyone in a room together twice a year. Teams are small, pods of three to five engineers, so nothing you ship disappears into a committee. You'll work shoulder to shoulder with product, design and data, and with the partners across the business who rely on what you ship. You'll also stay close to customers yourself: sitting in on user interviews, watching session recordings, riding along with support. Here that's part of the engineering job, on a regular basis. How We Hire Three rounds, usually two to three weeks start to finish. Recruiter conversation (30 minutes). Trade context: what you want next, what we're building and straight answers on comp, team and remote. Technical screen (1 hour). One round, no AI, language-agnostic. Reach for Google when you normally would. We just want to see how you reason from first principles. Final round (4 hours). Four one-hour interviews: system design, AI-assisted coding with the tools you'd actually use here, product sense and culture and values. You'll hear back either way within 24 to 48 hours. If your timeline is tight, tell us and we'll move faster. Benefits Company-paid medical and fully covered dental and vision A 401(k) match Generous paid parental leave for birthing and non-birthing parents, plus a gradual return-to-work program Winter Wonder Week, a paid company-wide week off at the end of the year A remote-work stipend Mental-health and wellness support A Few Things To Know We record and transcribe interviews to evaluate candidates, in line with applicable privacy laws. We expect you to use AI in your work and we welcome it in the process, but what you submit and say should reflect your own thinking. If you have a family member or close relationship with a Babylist employee, let your recruiter know. Official outreach only ever comes from an @babylist.com address

Location: London Workplace: OnSite ABOUT US At LangChain, our mission is to enable every company to own its intelligence. We believe agents will transform how companies operate, and we're building the foundation to make that future possible. Our open-source harnesses and LangSmith platform give developers and enterprises the infrastructure to run, improve, and govern agents at scale. We've raised $460M to date, with our most recent funding round valuing the company at $3B, backed by leading investors including Sequoia, Benchmark, IVP, and CapitalG. As we continue to expand our platform and tackle some of the hardest challenges in agent engineering, every team member has the opportunity to make a meaningful impact and help shape both our technology and the future of the industry. More than 7,000 organizations rely on LangSmith, from fast-growing startups to Fortune 500 enterprises, including NVIDIA, Bridgewater, LinkedIn, Workday, and Rippling. We're just getting started on making high-performing agents easier to build and manage at scale. ABOUT THE ROLE We're hiring a Vice President to own and lead our EMEA business. You'll inherit a team of 20+ quota-carrying Commercial and Enterprise AE's across four hubs: London, Amsterdam, Munich, Stockholm and be responsible for building the management layer, operating model and partner ecosystem that takes the EMEA region from early traction to consistent, scaled revenue. This is a second-line leader role that will see you report directly to the Global Vice President of Sales and operate with meaningful autonomy across pipeline, hiring, partner relationships and executive engagement. WHAT YOU'LL OWN Team leadership and performance - Lead, develop and expand the Sales teams across EMEA from day one - Run weekly pipeline reviews, deal coaching sessions, and forecast calls with precision and consistency - Identify and close performance gaps early: coach the team to close larger deals faster and navigate complex, multi-stakeholder cycles - Build a culture of accountability and development; create clear career paths for senior individual contributors, including first-line management opportunities as the team scales Revenue - Own the EMEA number: quarterly and annual quota attainment across all sub-regions - Build and maintain a healthy pipeline that supports consistent delivery and predictable forecasting to leadership - Engage directly in strategic deals as executive sponsor, bringing credibility and commercial weight to enterprise negotiations - Establish the region's strongest lighthouse accounts across key industry verticals, building referenceable wins that anchor LangChain's market position in EMEA Hiring - Manage multiple open roles across EMEA simultaneously: owning the full hiring lifecycle across pipeline, assessment and closing - Partner with the internal talent team to move at pace without compromising on quality - Define the headcount profile for EMEA beyond Q4 and feed into H1 planning, ensuring the team is built ahead of the revenue curve Partner ecosystem - Owns hyperscaler and GSI/RSI relationships (AWS, Google Cloud, Azure, and key SIs) across EMEA - Develop a structured partner motion that generates qualified pipeline and supports deal acceleration, reduces risk and drives expansion - Represent LangChain at partner QBRs and executive engagements in region Market presence - Represent LangChain as a keynote-ready leader at partner events, customer engagements, and industry conferences across the region: including KubeCon, Money20/20, Nordic AI summits, and customer EBCs - Build LangChain's brand with technical buyers, CIOs, and innovation leaders across Northern Europe's most important enterprise accounts - Bring intelligence on the EMEA markets back to the Global VP of Sales and product teams to inform roadmap and go-to-market positioning WHAT WE'RE LOOKING FOR Experience - 10+ years in enterprise SaaS sales, with at least 5+ years in a regional or sub-regional leadership role managing quota-carrying AE's - Demonstrable track record of hitting and exceeding regional revenue targets across multiple quarters - Experience managing teams across multiple countries and time zones, with the cultural intelligence to operate across EMEA - Background selling to technical buyers (engineering leaders, CTOs, platform teams): you understand how developer tools get evaluated and adopted - Experience in the AI, data, or developer tooling space strongly preferred; familiarity with the LangChain ecosystem is a meaningful plus Leadership - You've run teams of 20+ AEs before and know the difference between managing and coaching - You can hold a forecast conversation with a VP and a deal coaching session with an AE in the same afternoon and add value in both - You hire well and fast. You know what good looks like for enterprise AE profiles and you can run structured hiring processes across four open roles simultaneously - You've built or contributed to a partner motion before: you understand what "partner pipeline" means in practice, not just in theory Operating style - You bias toward action. You don't wait for a playbook to be handed to you: you build it - You're comfortable with ambiguity and early-stage scale. This is not a role with a fully defined motion; you'll shape a significant part of it - You communicate clearly and directly, to your team and to leadership - You're present in the market. You attend the right events, know the right people and build relationships that translate into pipeline and retention COMPENSATION PHILOSOPHY: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Location: CAN: Vancouver (333 Seymour St) Workplace: Hybrid The role / impact You will deliver high-quality, impactful software that aligns with team and business goals, always keeping customer needs and outcomes front of mind. By identifying and solving complex, ambiguous problems independently, you will produce robust, high-quality, and scalable software that helps change the world by supporting small businesses. Your daily work will focus on systems, scalability, and engineering quality while collaborating across teams to drive technical excellence and developer efficiency. Through clear and thoughtful communication, you will ensure stakeholders are well-informed and aligned. You will play a key part in fostering an inclusive team culture by mentoring others and sharing feedback with empathy. Your active participation in planning, delivery, and continuous improvement will contribute directly to the success of the broader Xero community. The team / how they connect You will join the Payments team within Product Platforms, which forms the critical foundation underneath core product areas like invoices, bills, payments, and payroll. The team exists to make it easy for other groups across Xero to build on a strong foundation of accounting concepts, data, and libraries safely and efficiently. Operating across Wellington and Vancouver, we collaborate closely to reduce tight coupling, establish clear service boundaries, and accelerate product velocity global-wide. The team is currently working on / Initially, you will focus on - Transitioning from a monolithic architecture to modern microservices to remove delivery bottlenecks and improve efficiency. - Building and operating services in a production cloud environment utilizing C#, .NET Core, and AWS. - Resolving complex legacy problems, database scalability challenges, and modernizing service interfaces or APIs. - Automating manual processes and applying test-driven and trunk-based development practices. Where and how you can work This role is based at our on-site location in Vancouver. We operate on a hybrid model where you will spend one to two days a week in the office for collaborative technical discussions and team alignment, with the flexibility to work from home on the other days. You will also have the opportunity to travel to New Zealand for onboarding after your first couple of weeks. Here are some of the things we are looking for - You bring proficient backend development experience with one or more programming languages such as C#, .NET, Java, or Go. - A solid understanding of distributed systems concepts, including service-to-service communication, eventual consistency, and resilience patterns belongs in your toolkit. - Your background features practical experience working with relational databases where transactional data integrity and ACID principles are critical. - Having a familiar working knowledge of modern DevOps practices, automated testing, and continuous integration pipelines will help you succeed. - Showing an interest in utilizing modern artificial intelligence tools will enable you to enhance personal productivity and streamline engineering workflows. - You possess strong communication and collaboration skills, with the capacity to manage internal stakeholders like a technical product partner. Apply even if your experience isn't a perfect match! At Xero, we hire based on your skills, passion, and the unique perspective you can bring to enhance our culture and team. Compensation & Total Rewards At Xero, we value the impact and skills you bring to the team. We believe in a Total Package philosophy - ensuring your value is recognized through a holistic lens that includes base salary, performance incentives, and world-class benefits. The expected base salary range for this role is 131,800 - 150,000 CAD. Individual pay is determined by various factors, including geography, level of experience, and the specific skills you bring to the role. In addition to base pay, Xero’s roles are eligible for the following forms of variable compensation: - Variable Pay: Permanent employees are eligible to participate in our annual bonus and equity (RSU) programs. You may also be eligible for performance-based cash or equity (RSUs) incentives depending on your role level, and company performance. - Comprehensive Benefits: World-class health, wellness, and retirement programs. Xero Perks https://careers.xero.com/inside-xero/benefits-wellbeing/ including Wellbeing days, generous leave, and dedicated professional development budgets. This is a posting for an existing vacancy. Xero uses AI to help screen applications based on job-related qualifications. These tools assist our recruiters but do not make automated hiring decisions. A human recruiter reviews all candidates before any hiring action is taken.

Location: New York City Metropolitan Area; Brooklyn, New York; Manhattan, New York; New York, New York; New Jersey; San Francisco Bay Area, California Workplace: hybrid About us At Provectus, you don’t prototype in a sandbox and hand a client a slide deck. You embed inside a bank, an insurer, or a health system, learn the work, and ship a Claude + AWS system into their real, regulated production — then you watch the business number move. We’re an Anthropic and AWS Partner with 150+ certified architects. That means the newest models, real budgets, and problems that matter — without the layers, politics, and years-to-impact of a hundred-thousand-person firm. 350+ builders, 100+ customers in production, founder-led since 2010, offices across North America, LATAM, and EMEA.  Why Provectus Frontier access — Anthropic Preferred Partner: newest Claude models, real budgets, real problems. Real tasks (not scope), real deployment. You go where the operating problem is and ship production code to real users, not slide decks that sit in a drive.  Embedded, not engaged. You are part of the customer’s team and inside their process — not a vendor running a project alongside it. Embedded is not staff-augmented. Autonomous. You own the work from framing through to production, visible to clients and founders.  You own the method; nobody hands you a ticket. Your experience stays portable. Every engagement is a new problem, often in a new industry, so your skills compound instead of narrowing to one product. No legacy-maintenance grind, not a single stack. Craft & growth — build beside senior FDEs on a Claude-certified team; a real platform (talks, OSS) to grow your name. We give you a stage: Claude certification, conference talks, open-source contributions, published work under your own name. What you’ll do: Spend the first weeks of each engagement in the operator’s seat, learning the constraints from the inside, then rebuild the function from first principles alongside the client and a Forward Deployed Executive — and you are the one who builds it. Be part of the customer’s team, inside their process; work on real tasks, not scoped deliverables, and own the method autonomously. You won’t start from zero. Provectus builds industry Blueprints — working systems that have already shipped for a customer in your industry. Your engagement starts from that baseline, and what you learn in the field goes back into it. Deliver across Cowork Activation, Agentic SDLC, and Blueprint Activations in Financial Services and Healthcare. Help shape how leading enterprises adopt AI, from strategy through first deployment; help build the tooling and frameworks of a growing AI delivery practice. What we look for: Typically 7+ years building software, a substantial share of it writing production code you were accountable for. You are hands-on today and intend to stay that way. Genuinely willing to spend time understanding someone else’s job before writing code; demonstrated ability to become conversant in an unfamiliar business function quickly. Shipped GenAI/LLM systems to production — not demos, not notebooks. You’ve handled the parts that get hard after the prototype works. You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured and why. Strong engineering fundamentals — dropped into an unfamiliar codebase or language, you’re productive. Python and/or TypeScript proficiency; depth matters more than stack. Cloud-native delivery on AWS (GCP/Azure a plus), including the operational reality of a system someone else inherits. Pre-sales experience. Credible with senior stakeholders — you can hold a redesign conversation with a BU head and a scoping conversation with a CTO without losing either room. Comfort with ambiguity and ownership. Engagements start underspecified by design. Closing that gap is the job. Hands-on experience with Claude, Claude Code, and Cowork (skills, workflows, MCP, integrations, connectors, custom harnesses). Nice to have: Containers and orchestration (Kubernetes/ECS) and CI/CD in production. IaC depth: AWS CDK, CloudFormation, Terraform. Open-source contributions or public writing on applied AI. What we offer: Full-time. On-site visits to client’s facilities and our office in NYC 1/week Unlimited Vacation policy. Generous health, vision, and dental insurance. 401(K) matching plan. Base salary $180k–$200k + bonuses; OTE up to $250k. The salary range is determined through interviews and a review of the education, experience, knowledge, skills, and abilities of the applicant, and alignment with market data. *No Visa sponsorship We’re real A person reads your application. We filter out AI-generated and fraudulent submissions automatically. Every application that clears that filter is read by someone on our team. We may ask for a quick ID verification. Fraudulent applications are common, and this protects real candidates. You’ll meet the people you’d work with. We host AI engineering events in New York and San Francisco. We'd be happy to talk in person. Your interviews are with Pavel Borobov, Solutions Architect, and Stepan Pushkarev, Co-Founder & CEO. How we hire: Recruitment interview. Tech interview with our FDE (30 min). A live engineering building session (1.5 hours). We hand you a business function and the constraints. You have to understand the job and rebuild it — then say what you’d build and how you’d know it worked. Use AI the way you normally would; we expect AI-generated code. What we look at is how you used AI, the judgment behind your choices, and what you researched beyond what any LLM already knows. Soft skills interview. Offer discussion.

Location: Remote - Global Workplace: Remote At Moxie, we empower ambitious aesthetic entrepreneurs to build profitable, independent practices—without burnout, overwhelm, or guesswork. In just a few years, we've grown from an idea to a global, remote-first team now supporting 700+ practices nationwide. Our purpose is simple: to unlock sustainable success for aesthetic entrepreneurs, at every stage of their journey. STAFF PLATFORM ENGINEER We're looking for a Staff Platform Engineer to lead some of Moxie's highest-impact infrastructure and developer productivity initiatives in Q4 2026 and H1 2027, starting with Continuous Delivery. Beyond the project work, you'll provide technical leadership across the company and own and validate major architectural decisions that shape how Moxie builds, with particular responsibility for cloud infrastructure, CI/CD, developer environments, observability, and operational tooling. You'll join our Platform team and work closely with engineers across Moxie to improve how we build, test, deploy, and operate software. You'll help evolve our developer platform to support both engineers and increasingly autonomous AI agents, with an emphasis on automation, self-service tooling, and reducing friction throughout the software development lifecycle. You'll also share responsibility for production reliability and operational support with our distributed Platform team, including participation in on-call and incident response during Americas hours. OUR OBJECTIVES FOR THE ROLE - Ship early wins that improve developer productivity. Within your first month, you're contributing to production infrastructure and developer tooling, participating in architectural discussions, and identifying opportunities for improvement. By month two, you've delivered targeted improvements to CI reliability, merge workflows, deployment automation, or local development environments. - Lead major platform initiatives from design to production. Take ownership of a meaningful workstream within our existing Continuous Delivery initiative, leading it through design, architecture review, cross-functional collaboration, and production. By month six, lead a second ambitious initiative, such as progressive delivery or developer environment improvements, to a visible milestone or production-ready state. - Shape architecture across the company. Within your first month, you're actively participating in architectural discussions and identifying opportunities to improve Moxie's systems. By month three, you're leading technical proposals, influencing major architectural decisions across teams, and taking designs from proposal through review, approval, and implementation, with particular ownership of our infrastructure and developer platform. - Build the next generation of developer infrastructure. By month nine, you've advanced automation, self-service environments, and the infrastructure needed to support increasingly autonomous AI engineering workflows, with measurable improvements in delivery speed, reliability, or developer experience. - Own non-project technical initiatives and engineering culture. Start owning at least one org-level initiative in your first three months (for example infrastructure standards, architecture governance, technical documentation, or engineering-wide reliability practices), and by month nine own one or two initiatives with measurable gains in quality or velocity, while shipping v1 of one or more key initiatives. WE'RE LOOKING FOR - Staff-level engineering experience. You've led large, ambiguous initiatives as a hands-on IC, owning delivery, tradeoffs, and major architectural decisions across teams. - Technical leadership and engineering standards. You've improved engineering practices, influenced peers across teams, and partnered with engineering leadership to resolve complex decisions and raise the technical bar. - Cloud infrastructure and architecture. You've designed, built, and operated production systems on AWS (ECS/Fargate, RDS, or equivalents), using containers and infrastructure as code (Terraform/Terragrunt), with strong judgment around scalability, reliability, and security. - Continuous Delivery expertise. You've improved CI/CD pipelines, testing infrastructure, and deployment workflows, with measurable gains in delivery speed, frequency, and reliability. - Developer platform thinking. You treat engineers as customers, building self-service tooling, developer environments, and scalable abstractions that reduce friction for both engineers and autonomous AI agents. - Observability and operational excellence. You've designed reliable, observable production systems using Datadog or equivalent tooling, with effective monitoring and alerting, and can diagnose complex production failures and drive lasting improvements. This is not a role for someone who prefers to advise from the sidelines or work a ticket queue; you'll build the fix yourself. WHY JOIN US? - Momentum from day one. You join an in-flight Continuous Delivery initiative with leadership backing, so your work lands in a plan that already has support. - A solid base to build on. Datadog observability is established and the deploy process works, so you improve a running platform instead of starting from zero. - You're not alone. You share US-hours coverage with an Americas staff platform engineer and work alongside an EU platform team. - Above all, we're in this to empower small business owners to own and grow their businesses. If you succeed, Med Spas will remain the opportunity for independent owner-operators instead of being dominated by a small number of large chains. If that speaks to you, speak to us. - We have much left to build. But given the market feedback we're getting and our founding team's company-building experience, we think we are writing the first chapters of a real success story. - Competitive salary and fully remote work. At Moxie, we believe in creating a workplace where everyone feels valued, trusted, and included. Our team lives by our values: act as owners, give more than we take, move with speed and care, and simplify and learn every day. We welcome people of all backgrounds, experiences, and perspectives to apply. If you require any accommodations to fully participate in the interview process, please let us know, we’re happy to assist.

Location: Remote, Massachusetts, United States, AMER From Fivetran’s founding until now, our mission has remained the same: to make access to data as simple and reliable as electricity. With Fivetran, customer data arrives in their warehouses, canonical and ready to query, with no engineering or maintenance required. We’re proud that more organizations continue to leverage our technology every day to become truly data-driven. About Us Fivetran and dbt Labs are bringing together two industry-leading companies with a shared mission: helping organizations unlock the full value of their data. Together, we’re delivering the data infrastructure layer that helps organizations move, transform, and trust their data — from the moment data moves, through every transformation, to the context teams and AI systems rely on. Fivetran helps organizations automate data movement across the systems, clouds, engines, and tools they rely on. dbt Labs pioneered analytics engineering, helping teams transform data into reliable, governed insights. Together, we support thousands of organizations as they build a trusted foundation for analytics, AI, and better business decisions. As we bring our teams and technology together, we’re building on the strengths of both companies while continuing to deliver the products and experiences our customers know and trust. It’s an exciting time to join us: we’re creating a company with the scale, talent, and technology to help more organizations put their data to work with greater speed, confidence, and impact. During this transition period, you may see references to both Fivetran and dbt Labs throughout our recruiting process as we integrate our teams, systems, and career sites. About the Role Fivetran + dbt  is seeking a Manager of Security Operations, Incident Detection and Response, to bolster and improve the robustness and security of the platform and the entire enterprise. This people-leadership role is hands-on and execution-focused, requiring deep expertise in security operations, incident detection and response, AI-driven security automation, and securing multi-tenant SaaS environments. You'll build and lead a high-performing team, own the detection and response technology stack, and serve as the accountable leader for incident response across the entire enterprise, ensuring threats are detected, contained, and remediated quickly from endpoint to cloud to production. This is a full-time remote position based out of the US (EST Time Zone). Technologies You’ll Use Crowdstrike, Okta, Google Workspace, Wiz, Open Source, Notion, JIRA What You’ll Do People Leadership: Lead, mentor, and develop a team of detection and response engineers and analysts. Set clear goals, manage performance, and grow careers while fostering a culture of ownership, curiosity, and urgency. Hiring & Team Building: Recruit, hire, and onboard top security talent. Define team structure, roles, on-call rotations, and hiring plans to scale the team alongside the business. Enterprise Incident Response: Own the incident response program for the entire enterprise, including investigation, containment, eradication, remediation, and post-incident review. Act as incident commander for major security events and coordinate with Legal, Privacy, Communications, and executive leadership. Detection Engineering: Build, optimize, and maintain high-fidelity detections across cloud, identity, endpoint, SaaS, and application layers, using threat-informed approaches such as MITRE ATT&CK to close coverage gaps. AI-Driven Security Operations: Drive the adoption of AI, including LLMs and AI agents, to automate alert triage, enrichment, investigation, and response. Evaluate and integrate AI capabilities to scale the team, and build detections for threats targeting AI systems and AI usage across the enterprise. Multi-Tenant SaaS Security: Design detection and response strategies tailored to a multi-tenant SaaS platform, including tenant isolation, cross-tenant access, and customer data protection. Lead customer-impacting incident response and coordinate customer notifications. Security Technology Ownership: Own the security operations technology stack, including SIEM, SOAR, EDR/XDR, cloud detection and response, and log pipelines. Manage the roadmap, budget, and vendor relationships. Threat Hunting & Intelligence: Lead proactive threat hunting and integrate threat intelligence to identify and mitigate emerging threats before they impact the business. Cross-Team Collaboration: Work directly with engineering, infrastructure, IT, application security, and GRC teams to integrate detection and response practices and remediate risks across build pipelines, runtime environments, and corporate systems. Tooling & Automation: Develop and maintain automation, playbooks, and integrations to streamline security processes and provide self-service security tools to the organization. Security Standards & Metrics: Implement consistent security controls, monitoring, and alerting across the enterprise. Define and report on key metrics such as mean time to detect (MTTD) and mean time to respond (MTTR), and support compliance requirements. Knowledge Sharing: Stay up to date with trends in security operations, incident response, cloud security, and AI security, applying this knowledge to improve the Fivetran platform's security posture. Skills We’re Looking For Security Operations & Incident Response Expertise: Deep expertise in detecting, investigating, and responding to security incidents, with a track record of leading enterprise-wide incident response. People Management: Proven experience managing, hiring, and developing security teams, including setting priorities, managing performance, and building a strong team culture. Multi-Tenant SaaS Experience: Extensive experience securing and responding to incidents in multi-tenant SaaS environments at scale, with a strong understanding of tenant isolation and customer data protection. AI Proficiency: Hands-on experience applying AI, including LLMs and AI agents, to security operations to automate detection, triage, and response, and a strong understanding of the risks AI introduces. Cloud & Infrastructure Security: Strong experience with cloud platforms (e.g., AWS, GCP, Azure), Kubernetes, and containerized environments, including cloud-native logging and detection. Detection & Response Tooling: Proficiency with SIEM, SOAR, EDR/XDR, identity, and cloud detection tools, and experience integrating them into automated workflows. Technology Ownership: Experience owning a security technology roadmap, including tool selection, budgets, and vendor management. Problem-Solving: Excellent problem-solving and troubleshooting skills, with the ability to make sound decisions under pressure in fast-paced environments. Communication: Strong communication skills with the ability to effectively collaborate with and educate engineering teams, and to communicate clearly with executives and customers during incidents. Curiosity & Urgency: Demonstrates strong curiosity, a sense of urgency, and a hands-on approach to diving deep into complex technical problems to drive timely and effective solutions. #LI-Remote #LI-AM1 The compensation range displayed on this job posting reflects the minimum and maximum target for new hire compensation for the target position and level, and may include sales incentives or target bonuses depending on the role.  Our compensation ranges are determined by role, level, and location. Our job titles may span more than one career level. Within the range, individual compensation is determined by additional factors, including job-related skills, experience, relevant education or training, business need, market demands. The compensation range is subject to change and may be modified in the future. Your recruiter can share more about the specific compensation range for your location during the hiring process. Pay Range $186,701 — $233,376 USD Perks and Benefits 100% employer-paid medical insurance * Generous paid time away from work, including paid vacation or flexible/unlimited vacation depending on role and country, plus paid sick time, inclusive parental leave, paid holidays, including a year-end Global Week of Rest, and volunteer days off. RSU stock grants* Professional development and training opportunities Company virtual happy hours, free food, and fun team-building activities Monthly cell phone stipend Access to an innovative mental health support platform that offers personalized care and resources in areas such as: therapy, coaching, and self-guided mindfulness exercises for all covered employees and their covered dependents. * May vary by country and worker type - please reach out to your recruiter for more information Click here to learn more about Fivetran's Benefits by Region. We’re honored to be valued at over $5.6 billion , but more importantly, we’re proud of our core values of Get Stuck In, Do the Right Thing, and One Team, One Dream . Read about us in Forbes . Fivetran brings together high-quality talent across the globe to make data access as easy and reliable as electricity for our customers. We value and recognize that our customers benefit from having innovative teams made of people from many backgrounds, experiences, and identities. Fivetran promotes diversity, equity, inclusion & belonging through attracting, recruiting, developing, and retaining a diverse workforce, not only because it is the right thing to do, but because it helps us build a world-class company to better serve our customers, our people and our communities. To learn more about Fivetran’s culture and what it’s like to be part of the team, click here and enjoy our video. To learn more about our candidate privacy policy, you can read our statement here . We are committed to ensuring that all candidates have an equal opportunity to participate in our interview process. If you require accommodations at any stage of the process due to a disability, medical condition, or any other circumstance, please don't hesitate to submit your request by filling out this form . We will work with you to provide reasonable accommodations to facilitate your participation and ensure a fair and accessible interview experience. Your request and any information provided will be kept confidential and will not impact your candidacy. We look forward to hearing from you and accommodating your needs to the best of our ability.

Location: Remote, New York, United States, AMER From Fivetran’s founding until now, our mission has remained the same: to make access to data as simple and reliable as electricity. With Fivetran, customer data arrives in their warehouses, canonical and ready to query, with no engineering or maintenance required. We’re proud that more organizations continue to leverage our technology every day to become truly data-driven. About Us Fivetran and dbt Labs are bringing together two industry-leading companies with a shared mission: helping organizations unlock the full value of their data. Together, we’re delivering the data infrastructure layer that helps organizations move, transform, and trust their data — from the moment data moves, through every transformation, to the context teams and AI systems rely on. Fivetran helps organizations automate data movement across the systems, clouds, engines, and tools they rely on. dbt Labs pioneered analytics engineering, helping teams transform data into reliable, governed insights. Together, we support thousands of organizations as they build a trusted foundation for analytics, AI, and better business decisions. As we bring our teams and technology together, we’re building on the strengths of both companies while continuing to deliver the products and experiences our customers know and trust. It’s an exciting time to join us: we’re creating a company with the scale, talent, and technology to help more organizations put their data to work with greater speed, confidence, and impact. During this transition period, you may see references to both Fivetran and dbt Labs throughout our recruiting process as we integrate our teams, systems, and career sites. About the Role Fivetran + dbt  is seeking a Manager of Security Operations, Incident Detection and Response, to bolster and improve the robustness and security of the platform and the entire enterprise. This people-leadership role is hands-on and execution-focused, requiring deep expertise in security operations, incident detection and response, AI-driven security automation, and securing multi-tenant SaaS environments. You'll build and lead a high-performing team, own the detection and response technology stack, and serve as the accountable leader for incident response across the entire enterprise, ensuring threats are detected, contained, and remediated quickly from endpoint to cloud to production. This is a full-time remote position based out of the US (EST Time Zone). Technologies You’ll Use Crowdstrike, Okta, Google Workspace, Wiz, Open Source, Notion, JIRA What You’ll Do People Leadership: Lead, mentor, and develop a team of detection and response engineers and analysts. Set clear goals, manage performance, and grow careers while fostering a culture of ownership, curiosity, and urgency. Hiring & Team Building: Recruit, hire, and onboard top security talent. Define team structure, roles, on-call rotations, and hiring plans to scale the team alongside the business. Enterprise Incident Response: Own the incident response program for the entire enterprise, including investigation, containment, eradication, remediation, and post-incident review. Act as incident commander for major security events and coordinate with Legal, Privacy, Communications, and executive leadership. Detection Engineering: Build, optimize, and maintain high-fidelity detections across cloud, identity, endpoint, SaaS, and application layers, using threat-informed approaches such as MITRE ATT&CK to close coverage gaps. AI-Driven Security Operations: Drive the adoption of AI, including LLMs and AI agents, to automate alert triage, enrichment, investigation, and response. Evaluate and integrate AI capabilities to scale the team, and build detections for threats targeting AI systems and AI usage across the enterprise. Multi-Tenant SaaS Security: Design detection and response strategies tailored to a multi-tenant SaaS platform, including tenant isolation, cross-tenant access, and customer data protection. Lead customer-impacting incident response and coordinate customer notifications. Security Technology Ownership: Own the security operations technology stack, including SIEM, SOAR, EDR/XDR, cloud detection and response, and log pipelines. Manage the roadmap, budget, and vendor relationships. Threat Hunting & Intelligence: Lead proactive threat hunting and integrate threat intelligence to identify and mitigate emerging threats before they impact the business. Cross-Team Collaboration: Work directly with engineering, infrastructure, IT, application security, and GRC teams to integrate detection and response practices and remediate risks across build pipelines, runtime environments, and corporate systems. Tooling & Automation: Develop and maintain automation, playbooks, and integrations to streamline security processes and provide self-service security tools to the organization. Security Standards & Metrics: Implement consistent security controls, monitoring, and alerting across the enterprise. Define and report on key metrics such as mean time to detect (MTTD) and mean time to respond (MTTR), and support compliance requirements. Knowledge Sharing: Stay up to date with trends in security operations, incident response, cloud security, and AI security, applying this knowledge to improve the Fivetran platform's security posture. Skills We’re Looking For Security Operations & Incident Response Expertise: Deep expertise in detecting, investigating, and responding to security incidents, with a track record of leading enterprise-wide incident response. People Management: Proven experience managing, hiring, and developing security teams, including setting priorities, managing performance, and building a strong team culture. Multi-Tenant SaaS Experience: Extensive experience securing and responding to incidents in multi-tenant SaaS environments at scale, with a strong understanding of tenant isolation and customer data protection. AI Proficiency: Hands-on experience applying AI, including LLMs and AI agents, to security operations to automate detection, triage, and response, and a strong understanding of the risks AI introduces. Cloud & Infrastructure Security: Strong experience with cloud platforms (e.g., AWS, GCP, Azure), Kubernetes, and containerized environments, including cloud-native logging and detection. Detection & Response Tooling: Proficiency with SIEM, SOAR, EDR/XDR, identity, and cloud detection tools, and experience integrating them into automated workflows. Technology Ownership: Experience owning a security technology roadmap, including tool selection, budgets, and vendor management. Problem-Solving: Excellent problem-solving and troubleshooting skills, with the ability to make sound decisions under pressure in fast-paced environments. Communication: Strong communication skills with the ability to effectively collaborate with and educate engineering teams, and to communicate clearly with executives and customers during incidents. Curiosity & Urgency: Demonstrates strong curiosity, a sense of urgency, and a hands-on approach to diving deep into complex technical problems to drive timely and effective solutions. #LI-Remote #LI-AM1 The compensation range displayed on this job posting reflects the minimum and maximum target for new hire compensation for the target position and level, and may include sales incentives or target bonuses depending on the role.  Our compensation ranges are determined by role, level, and location. Our job titles may span more than one career level. Within the range, individual compensation is determined by additional factors, including job-related skills, experience, relevant education or training, business need, market demands. The compensation range is subject to change and may be modified in the future. Your recruiter can share more about the specific compensation range for your location during the hiring process. Pay Range $186,701 — $233,376 USD Perks and Benefits 100% employer-paid medical insurance * Generous paid time away from work, including paid vacation or flexible/unlimited vacation depending on role and country, plus paid sick time, inclusive parental leave, paid holidays, including a year-end Global Week of Rest, and volunteer days off. RSU stock grants* Professional development and training opportunities Company virtual happy hours, free food, and fun team-building activities Monthly cell phone stipend Access to an innovative mental health support platform that offers personalized care and resources in areas such as: therapy, coaching, and self-guided mindfulness exercises for all covered employees and their covered dependents. * May vary by country and worker type - please reach out to your recruiter for more information Click here to learn more about Fivetran's Benefits by Region. We’re honored to be valued at over $5.6 billion , but more importantly, we’re proud of our core values of Get Stuck In, Do the Right Thing, and One Team, One Dream . Read about us in Forbes . Fivetran brings together high-quality talent across the globe to make data access as easy and reliable as electricity for our customers. We value and recognize that our customers benefit from having innovative teams made of people from many backgrounds, experiences, and identities. Fivetran promotes diversity, equity, inclusion & belonging through attracting, recruiting, developing, and retaining a diverse workforce, not only because it is the right thing to do, but because it helps us build a world-class company to better serve our customers, our people and our communities. To learn more about Fivetran’s culture and what it’s like to be part of the team, click here and enjoy our video. To learn more about our candidate privacy policy, you can read our statement here . We are committed to ensuring that all candidates have an equal opportunity to participate in our interview process. If you require accommodations at any stage of the process due to a disability, medical condition, or any other circumstance, please don't hesitate to submit your request by filling out this form . We will work with you to provide reasonable accommodations to facilitate your participation and ensure a fair and accessible interview experience. Your request and any information provided will be kept confidential and will not impact your candidacy. We look forward to hearing from you and accommodating your needs to the best of our ability.

Задачи: - Работа с SQL и Python - Моделирование данных (DWH / Data Lake / Lake House) - Работа с ClickHouse, Redshift, BigQuery - Работа с Big Data стеком (HDFS, Spark, Cloud, Object Storage) - Работа с ETL / ELT инструментами (Airflow, Flink, Dagster) - Использование Agile методологий - Интеграция с AI агентами (Cloude Code, ChatGPT, Copilot, OpenCode) Требования: - Коммерческий опыт работы от 2 лет - Знание SQL и Python - Английский язык на уровне B2 и выше Будет плюсом: - Опыт работы с веб-фреймворками (Flask, FastAPI, Django) - Опыт работы с системами обмена сообщениями (Kafka, RabbitMQ, Kinesis, SQS) - Опыт работы с облачными хранилищами (AWS, Azure, GCP) - Опыт работы с CI/CD Условия: - Просторный офис А класса в нескольких шагах от метро - Защищённая от инфляции заработная плата - Гибкий рабочий график - Молодой коллектив, ценящий инновации и совместную работу Вакансия перспективная, планируемая к созданию и/или замещению.

Location: Redwood City, CA, United States WHAT IS BOX? Box (NYSE:BOX) is the leader in Intelligent Content Management. Our platform enables organizations to fuel collaboration, manage the entire content lifecycle, secure critical content, and transform business workflows with enterprise AI. We help companies thrive in the new AI-first era of business. Founded in 2005, Box simplifies work for leading global organizations, including JLL, Morgan Stanley, and Nationwide. Box is headquartered in Redwood City, CA, with offices across the United States, Europe, and Asia. By joining Box, you will have the unique opportunity to continue driving our platform forward. Content powers how we work. It’s the billions of files and information flowing across teams, departments, and key business processes every single day: contracts, invoices, employee records, financials, product specs, marketing assets, and more. Our mission is to bring intelligence to the world of content management and empower our customers to completely transform workflows across their organizations. With the combination of AI and enterprise content, the opportunity has never been greater to transform how the world works together and at Box you will be on the front lines of this massive shift. WHY BOX NEEDS YOU The Reliability Engineering team at Box ensures our platform delivers world-class performance, scalability, and reliability as we continue to serve millions of users worldwide. As our business grows, so does the complexity of operating distributed systems at scale. Our mission is to proactively identify and solve the hardest reliability and performance challenges across Box’s infrastructure, working closely with product and platform teams to build resilient, scalable, and highly performant services. As a Senior Software Engineer on the Reliability Engineering team, you’ll have a direct impact on the performance and scalability of our most critical services. You’ll partner with engineering teams across the company to analyze complex system behaviors under load, design scalable solutions, and build testing frameworks that validate service reliability before issues arise in production. This role provides a unique opportunity to work broadly across our technical stack and make meaningful contributions to Box’s long-term scalability and customer experience. WHAT YOU’LL DO Partner with product and platform engineering teams to assess service designs for scalability and performance risks, ensuring systems are built for long-term growth. Analyze production workloads, system metrics, and load test results to identify bottlenecks, resource inefficiencies, and architectural scaling limits. Design and build frameworks for load testing, capacity modeling, and performance validation that enable teams to proactively address scale concerns. Drive improvements in backend service efficiency, API response times, and resource utilization across Box’s globally distributed platform. Collaborate with SRE, infrastructure, and platform teams to optimize scaling strategies, auto-scaling policies, and resource allocation. Build automation and tooling that integrate performance validation into CI/CD pipelines, enabling early detection of regressions. Participate in root cause analysis of performance-related incidents, identify systemic issues, and drive cross-team remediation efforts. Contribute to the evolution of observability standards (SLIs, SLOs, latency/error budgets) that measure and guide service health. WHO YOU ARE 5+ years of experience in software engineering, performance engineering, or site reliability engineering, with a focus on backend systems and scalability. Proficient in one or more programming languages such as Go or Java, with an emphasis on building performant services. Strong understanding of distributed systems, concurrency, resource contention, and efficient system design. Hands-on experience analyzing and improving application and system performance across compute, storage, database, and networking layers. Familiarity with load testing and performance benchmarking tools (e.g., Locust, JMeter, Gatling, or custom frameworks). Experience working with cloud infrastructure (AWS, GCP) and container orchestration (Kubernetes). Proficient with observability tools and telemetry systems (e.g., Prometheus, Chronosphere, Grafana, Datadog, ELK). Excellent problem-solving and analytical skills, with a data-driven approach to diagnosing complex system behaviors. Strong collaboration and communication skills; comfortable partnering across engineering teams to drive reliability improvements. PREFERRED QUALIFICATIONS Experience with service mesh technologies (Istio, Envoy) and cloud-native networking performance optimization. Exposure to capacity planning, cost optimization, and long-term resource forecasting in cloud environments. Familiarity with incident response processes, post-incident reviews, and reliability improvement practices. Experience contributing to internal platforms, developer tooling, or performance automation frameworks. METHODOLOGY Agile management - Scrum Issue tracking tool - Jira Knowledge repository - Confluence Code reviews - GitHub Enterprise Version control system - Git EQUAL OPPORTUNITY We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability, and any other protected ground of discrimination under applicable human rights legislation. Box strives to respect the dignity and ‎‎independence of people with disabilities and is committed to giving them the same ‎‎opportunity to succeed as all other employees. Inclusiveness is core to our culture at Box, and we strive to ensure you get the most from your interview experience. Box makes reasonable accommodations for applicants with disabilities. If a reasonable accommodation is needed to participate in the job application or interview process, please complete this form . Reasonable accommodations may include scheduling adjustments, document dictation and beyond. Notice to applicants in Los Angeles:  Box, Inc and its related branches will consider for employment, qualified applicants with criminal histories in a manner consistent with the Los Angeles Fair Chair Ordinance.  The Fair Chance Ordinance is provided here . Notice to applicants in San Francisco:  Box, Inc and its related branches will consider for employment, qualified applicants with criminal histories in a manner consistent with the San Francisco Fair Chair Ordinance.  The Fair Chance Ordinance is provided here . For details on how we protect your information when you apply, please see our Personnel Privacy Notice. If you are a California-resident, please read our California Applicant & Candidate Privacy Notice here . NOTICE OF USE OF AI At Box, we believe in the power of AI to improve the recruiting process while keeping people at the heart of every decision. For more information on the use of AI in our hiring process, please visit our webpage here . Box is committed to fair and equitable compensation practices. Actual base salary (or OTE if commissionable role) is dependent upon factors such as: knowledge, skill level, experience, and work location. This role is also eligible for equity and benefits. For more information , check out our benefits and perks . In accordance with OFCCP compliance, here is the Pay Transparency Provision . Redwood City Pay Range $198,500 — $248,000 USD