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Location: San Francisco, CA | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role The Cloud Inference team scales and optimizes Claude to serve the massive audiences of developers and enterprise companies across AWS, GCP, Azure, and future cloud service providers (CSPs). We own the end-to-end product of Claude on each cloud platform, from API integration and intelligent request routing to inference execution, capacity management, and day-to-day operations. Within Cloud Inference, the model & inference launch team owns the validation pipeline for our inference server and load balancer on these platforms. We're responsible for every inference change — model launches, performance improvements, safeguard integrations — landing on cloud platforms with correctness, performance, and reliability intact. This is high-leverage infrastructure work: validation has to be fast and cheap enough to run on the same accelerators that serve customers, trustworthy enough to replace manual checks, and consistent enough that a change working on Anthropic first-party means it works everywhere. This directly determines how fast frontier models and features ship to every cloud platform, and how quickly performance wins reach production — reclaiming capacity at a time when compute is our scarcest resource. Key responsibilities Be on the critical path for frontier model launches, bringing up inference for new model architectures and shipping them to cloud platforms in lockstep with our first-party platform Work with the core inference team to bring new inference features (e.g. structured sampling, prompt caching, and more) to cloud platforms, owning the platform-specific integration that gets them to production Identify and dive deep on the gaps that make inference behave differently across first-party and CSPs — config drift, observability, deployment patterns, hard cross-platform bugs — and fix them at the source rather than building platform-specific workarounds Design, build, and own the CI/CD infrastructure for the inference server and load balancer across cloud platforms, with shadow traffic, performance baselines (throughput and latency), and correctness checks that catch regressions before production Drive down merge-to-production cycle time by making validation faster, more parallel, and cost-effective enough to run on the same constrained accelerator pool that serves customers, without trading away reliability Analyze observability data across providers to identify performance bottlenecks, cost anomalies, and regressions, and drive remediation based on real-world production workloads Minimum qualifications Have a strong interest in LLM serving; prior inference or ML experience is not required Have significant software engineering experience, with a strong background in high-performance, large-scale distributed systems serving millions of users Have a track record of building automation or test infrastructure that measurably improved release velocity or reliability Have experience building or operating services on at least one major cloud platform (AWS, GCP, or Azure), with exposure to Kubernetes, Infrastructure as Code, or container orchestration Thrive in cross-functional collaboration with both internal teams and external partners Are a fast learner who can quickly ramp up on new technologies, hardware platforms, and provider ecosystems Are highly autonomous and take ownership of problems end-to-end, including work that falls outside your job description Preferred qualifications LLM inference optimization, batching, and caching strategies Capacity-constrained scheduling or shared-resource test infrastructure Solid understanding of multi-region deployments, request routing, load balancing, global traffic management Working with CSP partner teams to scale infrastructure across multiple platforms, navigating differences in networking, security, privacy, and managed service Proficiency in Python or Rust 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: $320,000 — $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: New York City, NY; San Francisco, CA; Seattle, WA 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 Our Inference team is responsible for building and scaling the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry’s largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators. The team has a dual mandate: maximizing compute efficiency to reliably serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms. Inference systems are highly performance sensitive distributed systems. Inference serves hundreds of thousands of customers every day, and the size & span of the inference fleet requires sophisticated routing, scaling, and networking systems. Key responsibilities Design, build, and maintain the distributed systems that serve Claude to millions of users worldwide Develop resilient, flexible systems that adapt in real time to real world events Develop intelligent request routing, load balancing, and traffic management systems across thousands of accelerators and multiple cloud providers Maximize compute efficiency and optimize cost across the fleet by autoscaling and orchestrating production, research, and experimental workloads across multiple cloud providers Build and operate production-grade deployment pipelines for releasing new models to users Provide high-performance inference infrastructure that enables researchers to develop next-generation models Integrate new AI accelerator platforms and support inference for new model architectures Minimum qualifications Significant software engineering experience, particularly with distributed systems Results-oriented, with a bias towards flexibility and impact Willingness to pick up slack, even if it goes outside your job description Desire to learn more about machine learning systems and infrastructure Thrive in environments where technical excellence directly drives both business results and research breakthroughs Care about the societal impacts of your work Preferred qualifications Experience with high-performance, large-scale distributed systems Experience implementing and deploying machine learning systems at scale Experience with load balancing, request routing, or traffic management systems Familiarity with LLM inference optimization, batching, and caching strategies Experience with Kubernetes and cloud infrastructure (AWS, GCP, Azure) Proficiency in Python or Rust Representative projects Designing intelligent routing algorithms that optimize request distribution across many accelerators in different environments Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads Building production-grade deployment pipelines for releasing new models to millions of users reliably Contributing to new inference features Supporting inference for new model architectures Analyzing observability data to tune performance based on real-world production workloads Managing multi-region deployments and geographic routing for global customers 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: $320,000 — $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: Remote Canada At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. Affirm’s Identity team is mission-critical to the customer checkout experience. When a customer chooses Affirm, one of the first steps is an identity check, and our ability to make the right decision directly impacts conversion, revenue, fraud exposure, and regulatory compliance. Our team owns Identity for all markets outside North America, playing a key role in Affirm’s international expansion. We are responsible for KYC, user lifecycle management, and identity decisioning across multiple regulatory environments. This work is about shaping how Affirm adapts its core Identity platform to new market dynamics, customer expectations, and compliance requirements. What you'll do You will be responsible for setting technical strategy for your team on a year-long time scale, and help your team tie it together with critical, business-impacting projects. You will collaborate across teams in the product development lifecycle by collaborating with product management, design & analytics to ensure technical sustainability, risks and trade-offs are well understood and managed. You will act as a force-multiplier for your team through your definition and advocacy of technical solutions and operational processes. You take ownership of your team’s operations and availability by ensuring you have the right monitoring, triage rotations, playbooks, polcities, testing and alerting in place to support “keep the lights on” & on-call efforts. You will foster a culture of quality and ownership on your team by setting code review and design standards for your team, and advocating for them beyond your team through your writing and tech talks. You will help develop talent on your team by providing feedback and guidance, and leading by example. What we look for You have 8+ years of experience designing, developing and launching backend systems at scale using languages like Python or Kotlin. You have an extensive track record of developing highly available distributed systems using technologies like AWS, MySQL, Spark and Kubernetes. You have experience delivering major features, system components or deprecating existing functionality in a system through the definition of a technical and execution plan. You write high quality code that is easily understood and used by others. You thrive in ambiguity, and are comfortable moving from low level language idioms all the way to the architecture of large systems to understand how they work. Your growth and impact trajectory demonstrates that you have mastered gathering and iterating on feedback from your engineering and cross-functional peers. You have strong verbal and written communication skills that support effective collaboration with our global engineering team. This position requires either equivalent practical experience or a Bachelor’s degree in a related field. Base Pay Grade - P Equity Grade - 7 Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills. Base pay is part of a total compensation package that may include monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents). In addition, the employees may be eligible for equity rewards offered by Affirm Holdings, Inc. (parent company). CAN base pay range per year: CAD $181,000 - $241,000 Location - Remote Canada This remote role is open only to candidates residing in Alberta, British Columbia, Manitoba, New Brunswick, Newfoundland and Labrador, Nova Scotia, Ontario, Prince Edward Island, or Saskatchewan. #LI-Remote Remote-first with flexibility built in Affirm is proud to be a remote-first company. Most roles can be done from almost anywhere within the country of employment. Some positions may occasionally require in-person work at an Affirm office, and a few are office-based due to the nature of the work. All new hires will be invited to attend an in-person onboarding experience. Benefits designed for you Our benefits reflect our commitment to care, transparency, and flexibility. Here are a few highlights: Health coverage at no cost: We cover 100% of premiums for employees and their dependents. Spending stipends: Monthly stipends support your tech setup, and the ability to choose health and wellness options that are right for you. Time off to recharge: Flexible time off and generous holiday calendars help you rest when you need to. Own a piece of what you build: Our employee stock purchase plan (ESPP) lets you buy Affirm stock at a discount. We’re committed to providing an inclusive interview process, including accommodations for candidates with disabilities. If you need support, we’re happy to help. For positions based in San Francisco or Los Angeles: Affirm considers qualified applicants with arrest and conviction records, as required by law. By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and consent to the use of your personal information as described.

Location: Remote US At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. Affirm’s Identity team is mission-critical to the customer checkout experience. When a customer chooses Affirm, one of the first steps is an identity check, and our ability to make the right decision directly impacts conversion, revenue, fraud exposure, and regulatory compliance. Our team owns Identity for all markets outside North America, playing a key role in Affirm’s international expansion. We are responsible for KYC, user lifecycle management, and identity decisioning across multiple regulatory environments. This work is about shaping how Affirm adapts its core Identity platform to new market dynamics, customer expectations, and compliance requirements. What you'll do You will be responsible for setting technical strategy for your team on a year-long time scale, and help your team tie it together with critical, business-impacting projects. You will collaborate across teams in the product development lifecycle by collaborating with product management, design & analytics to ensure technical sustainability, risks and trade-offs are well understood and managed. You will act as a force-multiplier for your team through your definition and advocacy of technical solutions and operational processes. You take ownership of your team’s operations and availability by ensuring you have the right monitoring, triage rotations, playbooks, polcities, testing and alerting in place to support “keep the lights on” & on-call efforts. You will foster a culture of quality and ownership on your team by setting code review and design standards for your team, and advocating for them beyond your team through your writing and tech talks. You will help develop talent on your team by providing feedback and guidance, and leading by example. What we look for You have 8+ years of experience designing, developing and launching backend systems at scale using languages like Python or Kotlin. You have an extensive track record of developing highly available distributed systems using technologies like AWS, MySQL, Spark and Kubernetes. You have experience delivering major features, system components or deprecating existing functionality in a system through the definition of a technical and execution plan. You write high quality code that is easily understood and used by others. You thrive in ambiguity, and are comfortable moving from low level language idioms all the way to the architecture of large systems to understand how they work. Your growth and impact trajectory demonstrates that you have mastered gathering and iterating on feedback from your engineering and cross-functional peers. You have strong verbal and written communication skills that support effective collaboration with our global engineering team. This position requires either equivalent practical experience or a Bachelor’s degree in a related field. Base Pay Grade - P Equity Grade - 13 Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills. Base pay is part of a total compensation package that may include equity rewards, monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents.) USA Pacific base pay range (CA, WA, NY, NJ, CT): $230,000 - $290,000 USA Sapphire base pay range (all other U.S. states): $204,00 - $264,000 #LI-Remote Remote-first with flexibility built in Affirm is proud to be a remote-first company. Most roles can be done from almost anywhere within the country of employment. Some positions may occasionally require in-person work at an Affirm office, and a few are office-based due to the nature of the work. All new hires will be invited to attend an in-person onboarding experience. Benefits designed for you Our benefits reflect our commitment to care, transparency, and flexibility. Here are a few highlights: Health coverage at no cost: We cover 100% of premiums for employees and their dependents. Spending stipends: Monthly stipends support your tech setup, and the ability to choose health and wellness options that are right for you. Time off to recharge: Flexible time off and generous holiday calendars help you rest when you need to. Own a piece of what you build: Our employee stock purchase plan (ESPP) lets you buy Affirm stock at a discount. We’re committed to providing an inclusive interview process, including accommodations for candidates with disabilities. If you need support, we’re happy to help. For positions based in San Francisco or Los Angeles: Affirm considers qualified applicants with arrest and conviction records, as required by law. By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and consent to the use of your personal information as described.

Location: Portugal; Brazil SUMMARY: You will join a cross-functional squad responsible for building and maintaining high-scale, customer-facing services. The role involves contributing to new product features, evolving system architecture, improving code quality, and ensuring operational reliability in a modern, cloud-based environment. The ideal engineer thrives in a collaborative, autonomous culture that values experimentation, continuous learning, and shared ownership. This position plays a key part in shaping technical decisions, supporting platform evolution, and delivering impactful solutions at scale. WHAT WILL YOU BE DOING: You will be joining our engineering team and will be a valued member working closely in a collaborative, autonomous, cross-functional team. You will help with the following: Feature Delivery & Collaboration Participation in the design and delivery of new product features in collaboration with product, design, and engineering teams. Exploration of feasibility options and contribution to customer-focused engineering decisions. Commitment to clear goals, delivery expectations, and shared team objectives. Clear and responsible communication within the squad to support alignment and transparency. Communicating your needs clearly and responsibly. Architecture & Technical Decision-Making Contribution to system architecture discussions and evolution of technical design within the squad. Application of OOP, SOLID principles, and clean coding practices to build maintainable Ruby services. Participation in establishing engineering patterns, standards, and long-term architectural improvements. Support in building highly available, resilient, and scalable systems. Code Quality & Testing Development of high-quality Ruby code that is maintainable, readable, and structured for long-term sustainability. Adoption of strong testing practices using RSpec or Minitest to ensure robust test coverage. Improvement of existing systems to enhance reliability, modularity, and testability. Contribution to a culture of automated testing and continuous quality improvements. Operational Excellence Support in building and maintaining services operating under significant scale and traffic. Participation in monitoring, troubleshooting, and enhancing system resilience. Contribution to observability practices, operational readiness, and continuous improvement of production systems. Engagement in deployments and incident support as part of the team’s shared operational ownership. WHAT WE ARE LOOKING FOR: Core Technical Skills Strong hands-on experience with Ruby for building production applications. Ability to deliver maintainable, well-structured code aligned with OOP and SOLID principles. Proficiency in automated testing using RSpec or Minitest. Experience working with Git and collaborative development workflows. Backend Engineering Fundamentals Experience building scalable, API-driven backend services. Understanding of concurrency, asynchronous processing, and distributed system interactions. Experience with PostgreSQL, Redis, and MongoDB for data persistence and caching. Ability to design and troubleshoot systems operating under heavy load and high availability requirements. Operational & Performance Awareness Familiarity with diagnosing performance bottlenecks and implementing optimisations. Strong understanding of observability principles, including monitoring, logging, and system health analysis. Experience supporting and iterating on production systems. Communication & Collaboration Strong English communication skills, both written and verbal. Ability to contribute positively to team collaboration, solution discussions, and knowledge sharing. AWESOME BUT NOT REQUIRED: Experience with containers and orchestration (Docker, Kubernetes). Familiarity with Rack, Sinatra, or Rails frameworks. Exposure to EventMachine or event-driven architectures. Experience with ELK, Datadog, or similar observability stacks. Knowledge of AWS services such as ECR, EC2, S3, and RDS. Exposure to CI/CD pipelines, cloud-native practices, or infrastructure tooling. WHAT’S IN IT FOR YOU? Be part of our collegial environment where responsibility and authority are shared equally amongst colleagues, and help create our company culture A culture in which we don’t criticise failure but ensure we learn from our mistakes An Agile environment where your ideas are welcome The possibility to grow and experience different projects Fully remote Ongoing Training & Mentoring The possibility of travelling - ATTENTION!  THIS POSITION IS FOR  PORTUGAL OR BRAZIL-BASED ONLY

Location: São Paulo, Brazil About Turing Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com . ABOUT THE ROLE Turing is the world's leading research accelerator for frontier AI labs. The STEM Horizontal team produces the high-signal STEM data those labs train on, and this role builds the machinery behind it: the task-authoring tools, data pipelines, evaluation harnesses, sandboxed execution environments, and agentic workflows our researchers and domain experts work inside every day. This sits at the seam between engineering and research. You'll own production systems end-to-end, and you'll be the person a researcher pulls in to ask why an eval is producing misleading numbers. Correctness and reproducibility are the product: a subtle bug here doesn't crash anything, it quietly poisons a training run and costs weeks. If you want to build systems that visibly shape how frontier models learn to reason about code and science, this is the seat. WHAT YOU'LL DO Own services end-to-end: design, implementation, rollout, and production operation. Build backend services and the data pipelines that generate, validate, score, and version datasets, reproducible from a commit and a config. Ship data-dense internal interfaces: virtualised tables, server-side filtering, review and annotation UIs that stay fast at tens of thousands of rows. Build and operate agent harnesses , multi-step loops with tool use, retries, and structured output, running against real repos and test suites. Build sandboxed execution environments where model-generated code runs safely and deterministically at volume, and stand up the RL environments and eval harnesses on top. Trace and debug agent runs end-to-end: where the loop stalled, which tool call failed, why the grader disagreed with the human. Own infrastructure as code and CI/CD; debug production issues across the stack and drive the reliability work that follows. Raise the bar through code review, design docs, and innovation, partnering with researchers and quality owners on what “good” means. TECH STACK Backend Python · FastAPI · Django / Django Ninja · PostgreSQL · MongoDB · REST + OpenAPI Frontend TypeScript · React · Next.js · virtualised tables, server-side filtering Platform Linux · Docker · Terraform · CI/CD · AWS or GCP WHAT YOU NEED 6+ years building and operating production software, ideally at product companies with real scale. Deep Python with production FastAPI and/or Django , ORM performance, migrations, async patterns. Strong PostgreSQL (schema design, query optimisation, indexing) and NoSQL. Frontend production with TypeScript / React / Next.js . Fluent on Linux and Docker ; Terraform or comparable IaC on AWS or GCP , and ownership of the CI/CD that ships it. Daily use of LLM coding tools (Claude Code, Cursor, Copilot) as part of how you actually ship, with the judgement to review their output critically and know where they break down. We are an AI-forward team; this is a must-have. You've built something on top of LLM APIs that other people depended on, an agent, a pipeline, an eval, and you know where it was fragile. Comfort with non-deterministic systems : you can tell a real regression from noise, and you reach for a controlled experiment over a hunch. Advanced Git and real testing discipline, unit, integration, and the negative and edge cases people skip. Clear written communication; comfortable working without hand-holding, and comfortable saying when a spec is wrong. NICE TO HAVE Internal tools or developer platforms used daily by a technical team. Agent frameworks and protocols, LangGraph, MCP, OpenAI/Anthropic tool use. Sandboxing and untrusted code execution: gVisor, Firecracker, seccomp. Workflow orchestration (Temporal, Airflow, Prefect, Dagster) and Kubernetes beyond managed defaults. LLM coding benchmarks (SWE-bench, Terminal-Bench), eval frameworks, or exposure to RLHF / RLVR. PREFERRED BACKGROUND Bachelor's or Master's degree with 6+ years experience in Computer Science, Software Engineering, Data Science, Machine Learning, AI, or a programming-heavy IT field. We weight demonstrated work outcomes most heavily, a strong track record without a matching degree is fine. Values We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. Advantages of joining Turing Work at the frontier of AI , helping the world’s leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks. Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS. Bring frontier AI innovation to the enterprise , applying lessons learned from leading AI labs to solve real-world business challenges. Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies. Move at the pace of AI innovation , with the speed, ownership, and impact of a startup. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace  and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here .

Location: San Francisco, California; New York, New York Workplace: Hybrid WHO WE ARE Notion is the collaborative AI workspace where teams and agents think together https://www.youtube.com/watch?v=vkpYpWfEK5s. We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. ABOUT THE ROLE Millions of people rely on Notion to do their most important work, and protecting that trust is foundational to everything we build. We’re looking for a hands-on Detection Engineer to build and operate the systems and workflows we use to detect and respond to attacks across Notion’s cloud-native environment. You’ll ship high-signal detections, improve the platform that powers them, participate in incident response, and help shape how detection and response engineering scales at Notion. You’ll work closely with Engineering, Corporate Security, and Infrastructure, with broad latitude to identify gaps, prioritize investments, and build what’s needed next. We view detection and response as a software engineering discipline: detections are code, platforms are products, and measurement matters WHAT YOU'LL ACHIEVE - Build and tune high-signal detections across cloud, identity, endpoint, and SaaS environments, with review and mentorship from senior teammates as you ramp up. - Contribute to the detection platform, including rule lifecycle management, tuning, measurement, and rollout safety. - Build tooling and automation that speed up triage, enrichment, investigation, and detection authoring, including LLM-based workflows where useful. - Turn threat intelligence and adversary TTPs into detections, telemetry requirements, and response improvements. - Take part in investigations, incident response, and postmortems, and help turn what we learn into lasting fixes. - Help define and track metrics such as coverage, MTTD, and alert quality. - Join a shared on-call rotation for incident response. SKILLS YOU'LL NEED TO BRING - We're hiring across a range of experience levels. If you have some of these skills but not all, we'd still like to hear from you. - 3+ years of experience in detection engineering, security operations, incident response, threat hunting, or a closely related security or software engineering role. - Have written or tuned detections that run in production, and care about signal quality and cutting noise. - Working knowledge of at least one detection or query language (Sigma, KQL, SPL, YARA-L, EQL, or Panther), or strong SQL or Python skills and the drive to learn one quickly. - An understanding of how attackers operate (for example, MITRE ATT&CK), and the ability to use it to decide what to detect. - Hands-on experience with AWS, GCP, or Azure, ideally including identity and access logs. - Have used SIEM, EDR, or SOAR tools in any size of environment. - Write clearly in runbooks, design docs, and incident notes, and can own well-scoped projects end to end. NICE TO HAVE - Have led purple team, blue team, or adversary emulation exercises that improved detections or telemetry. - Experience running SIEM, EDR, or SOAR platforms at large scale. - Experience building or maintaining detection-as-code workflows (version control, CI, and tests for detections). - Experience applying LLMs or agent-style tooling to security workflows. - Experience securing AI-enabled systems or endpoint tooling. - Kubernetes or container detection experience. - Background in threat intelligence, malware analysis, or digital forensics. - Contributions to the security community through research, tooling, CTFs, or talks. - Experience at a high-growth startup or AI company. Notion is committed to providing highly competitive cash compensation, equity, and benefits. The compensation offered for this role will be based on multiple factors such as location, the role’s scope and complexity, and the candidate’s experience and expertise, and may vary from the range provided below. For roles based in San Francisco or New York City, the estimated base salary range for this role is $185,000 - $280,000 per year.   By clicking “Submit Application”, I understand and agree that Notion and its affiliates and subsidiaries will collect and process my information in accordance with Notion’s Global Recruiting Privacy Policy https://notion.notion.site/Notion-Global-Recruiting-Privacy-Policy-fc3eb4e829354a26a2bb6fd5e289b550 and and NYLL 144 https://notion.notion.site/Ashby-AI-Bias-Audit-2b0efdeead05803bbbfae159ec86c528.   #LI-Onsite A NOTE ON AI You don’t need deep AI expertise for every role, but we do expect every Notino to be intellectually curious, drawn to tinkering and discovery, and excited to use AI as a real collaborator in their work. For some roles, AI fluency is a core requirement — when that’s the case, we'll say so explicitly in the qualifications. People who thrive here don’t treat AI as a novelty. They use it to think better, and make their work easier for others to build on. EQUAL OPPORTUNITY & ACCOMMODATIONS We hire talented people from a wide range of backgrounds. If you’re excited about this role but don’t meet every bullet, we still encourage you to apply. Notion is an equal opportunity employer and does not discriminate on the basis of any legally protected characteristic. Consistent with applicable law, we will consider for employment qualified applicants with arrest and conviction records. Notion provides reasonable accommodations during the application process; if you need one, please let your recruiter know. Notion is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic. Notion considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Notion is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, please let your recruiter know.

Location: Dublin, Ireland Workplace: Hybrid WHO WE ARE Notion is the collaborative AI workspace where teams and agents think together https://www.youtube.com/watch?v=vkpYpWfEK5s. We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. ABOUT THE ROLE Millions of people rely on Notion to do their most important work, and protecting that trust is foundational to everything we build. We’re looking for a hands-on Detection Engineer to build and operate the systems and workflows we use to detect and respond to attacks across Notion’s cloud-native environment. You’ll ship high-signal detections, improve the platform that powers them, participate in incident response, and help shape how detection and response engineering scales at Notion. You’ll work closely with Engineering, Corporate Security, and Infrastructure, with broad latitude to identify gaps, prioritize investments, and build what’s needed next. We view detection and response as a software engineering discipline: detections are code, platforms are products, and measurement matters WHAT YOU'LL ACHIEVE - Build and tune high-signal detections across cloud, identity, endpoint, and SaaS environments, with review and mentorship from senior teammates as you ramp up. - Contribute to the detection platform, including rule lifecycle management, tuning, measurement, and rollout safety. - Build tooling and automation that speed up triage, enrichment, investigation, and detection authoring, including LLM-based workflows where useful. - Turn threat intelligence and adversary TTPs into detections, telemetry requirements, and response improvements. - Take part in investigations, incident response, and postmortems, and help turn what we learn into lasting fixes. - Help define and track metrics such as coverage, MTTD, and alert quality. - Join a shared on-call rotation for incident response. SKILLS YOU'LL NEED TO BRING - We're hiring across a range of experience levels. If you have some of these skills but not all, we'd still like to hear from you. - 3+ years of experience in detection engineering, security operations, incident response, threat hunting, or a closely related security or software engineering role. - Have written or tuned detections that run in production, and care about signal quality and cutting noise. - Working knowledge of at least one detection or query language (Sigma, KQL, SPL, YARA-L, EQL, or Panther), or strong SQL or Python skills and the drive to learn one quickly. - An understanding of how attackers operate (for example, MITRE ATT&CK), and the ability to use it to decide what to detect. - Hands-on experience with AWS, GCP, or Azure, ideally including identity and access logs. - Have used SIEM, EDR, or SOAR tools in any size of environment. - Write clearly in runbooks, design docs, and incident notes, and can own well-scoped projects end to end. NICE TO HAVE - Have led purple team, blue team, or adversary emulation exercises that improved detections or telemetry. - Experience running SIEM, EDR, or SOAR platforms at large scale. - Experience building or maintaining detection-as-code workflows (version control, CI, and tests for detections). - Experience applying LLMs or agent-style tooling to security workflows. - Experience securing AI-enabled systems or endpoint tooling. - Kubernetes or container detection experience. - Background in threat intelligence, malware analysis, or digital forensics. - Contributions to the security community through research, tooling, CTFs, or talks. - Experience at a high-growth startup or AI company. Notion is committed to providing highly competitive cash compensation, equity, and benefits. The compensation offered for this role will be based on multiple factors such as location, the role's scope and complexity, and the candidate's experience and expertise, and may vary from the range provided below. The estimated base salary range for this role is €75,000–€142,000 per year. By clicking “Submit Application”, I understand and agree that Notion and its affiliates and subsidiaries will collect and process my information in accordance with Notion’s Global Recruiting Privacy Policy https://notion.notion.site/Notion-Global-Recruiting-Privacy-Policy-fc3eb4e829354a26a2bb6fd5e289b550?pvs=74. #LI-Onsite A NOTE ON AI You don’t need deep AI expertise for every role, but we do expect every Notino to be intellectually curious, drawn to tinkering and discovery, and excited to use AI as a real collaborator in their work. For some roles, AI fluency is a core requirement — when that’s the case, we'll say so explicitly in the qualifications. People who thrive here don’t treat AI as a novelty. They use it to think better, and make their work easier for others to build on. EQUAL OPPORTUNITY & ACCOMMODATIONS We hire talented people from a wide range of backgrounds. If you’re excited about this role but don’t meet every bullet, we still encourage you to apply. Notion is an equal opportunity employer and does not discriminate on the basis of any legally protected characteristic. Consistent with applicable law, we will consider for employment qualified applicants with arrest and conviction records. Notion provides reasonable accommodations during the application process; if you need one, please let your recruiter know. Notion is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic. Notion considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Notion is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, please let your recruiter know.

Location: Bulgaria, Hungary, Poland Why Join Exadel We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks. From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next. What powers it all? Our people are ambitious, collaborative, and constantly evolving. About the Client The leading provider of vehicle lifecycle solutions, with headquarters in Chicago, enables the companies that build, insure, and replace vehicles to power the next generation of transportation. Its platform delivers advanced mobile, artificial intelligence, and car technologies. It connects a network of 350+ insurance companies, 24,000+ repair facilities, hundreds of parts suppliers, and dozens of third-party data and service providers. The customer's collective solutions enhance productivity and help clients deliver better experiences for end consumers. What You’ll Do Design and implement end-to-end document intelligence pipelines on AWS Develop and optimize ML models for document classification, segmentation, and field extraction Build scalable data processing systems handling PDFs up to 2000 pages Collaborate with subject matter experts to create and refine requirements for extraction Own features from research through production deployment and monitoring Establish evaluation frameworks and quality metrics for extraction accuracy What You Bring Advanced knowledge of Python (native, Pandas, ScikitLearn, Tensorflow or Pytorch, PyStats, Pydantic) Experience with AWS tools for ML Engineering and ML deployment (Sagemaker, Lambda, Cloudformation/CDK, Step Functions) Advanced knowledge of SQL and Data Modeling Experience with GenAI for document intelligence, including prompt engineering, RAG (Retrieval Augmented Generation), multi-modal models (vision + text), and production deployment using AWS Bedrock or Azure OpenAI APIs Experience in experiment design (power analysis and hypothesis testing) Proficiency in both written and verbal communication, required for a remote and largely asynchronous work environment Demonstrated capacity to clearly and concisely communicate complex technical problems and propose iterative solutions Experience owning a feature from concept to production, including proposal, discussion, and execution Nice to have Experience with document processing tools (AWS Textract, Azure Document Intelligence, or similar OCR/layout detection systems) Experience with PDF and Image processing libraries (e.g. PyMuPDF, opnecv, pillow) Experience in Machine Learning/ Data Science (e.g., ML algorithm selection, feature engineering, model training, hyperparameter tuning, supervised and unsupervised learning implementation, building a model pipelines, using Machine Learning tools/libraries/frameworks) Experience working with AWS big data technologies (Redshift, S3, EMR, Glue, etc.) English Level Upper-intermediate Legal & Hiring Information Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more. Reasonable accommodations are available to enable individuals with disabilities to perform essential functions. Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs. Compensation details are shared with candidates at the early stage of the recruitment process. The offer is not binding until a signed contract is in place. Your Benefits at Exadel Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details. International projects In-office, hybrid, or remote flexibility Medical healthcare Recognition program Ongoing learning & reimbursement Well-being program Team events & local benefits Sports compensation Referral bonuses Top-tier equipment provision Exadel Culture We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

Location: Remote - India AI/ML Solution Architect Education & Assessment Platforms About Pratham International Pratham International is a US 501(c)(3) established to support learning innovations for children and youth in contexts across the globe. We enable the adaptation and spread of proven and scalable education solutions pioneered in India by Pratham Education Foundation to contexts across the global south through programming and technical assistance tailored to local realities. Today, Pratham innovations reach millions of children annually through partnerships across ~30 countries. Through the Pratham Shah PraDigi Innovation Centre (PraDigi), Pratham International also seeks to create technology innovations for low-resource communities, and support models aimed at learning for school, work, and life for children and youth. We work on several cutting-edge projects in the domain of Generative AI, Automatic Speech Recognition, and Natural Language Processing. The team’s innovative technology products include the PadhAI: Reading Assessment App, which uses advanced speech recognition to evaluate children’s reading fluency in 8 Indian languages and 6 global languages; Anytime Testing Machine (ATM), an AI-enabled question generation and grading system that allows learners to be assessed on any topic, anytime; and a suite of AI-powered chatbots designed for diverse learning contexts: from early childhood care, to youth employment readiness, and OCR-based analysis tools that digitize and assess student work at scale. At Pratham International, we build for the long term. Whether it’s ensuring products are truly accessible across rural India and the global south through languages, building datasets to ensure context and accuracy for products, or gathering feedback from the field. Backed by partners like Google.org, Anthropic, and the Gates Foundation, we are committed to building digital public goods that ensure every child is in school and learning well. Role Overview About the work We design and deliver AI systems that governments and large education programmes can actually run: curriculum-aligned item generation, paper assembly, handwriting OCR, rubric grading, and teacher-in-the-loop review. The work is already live as practice assessment in India and is being built as a national exam platform in Rwanda, with further country programmes behind it. We are hiring a Solution Architect who sits between discovery and delivery. You will turn messy workshop notes and ministry requirements into architecture a team can build, secure, cost, and operate — RAG and multi-agent systems, LLM-as-judge pipelines, and the cloud/LLMOps layer underneath. You will Own solution design from first workshop to a delivery-ready blueprint (services, data stores, trust boundaries, cost, ops). Architect LLM pipelines: generation, retrieval over curriculum knowledge graphs, standards/duplication/quality judges, constraint-based paper assembly. Design human + AI workflows with audit, segregation of duties, cycle-pinned config, and no student PII in model calls. Choose and govern models, prompts, eval gates, and fallbacks (including OCR: Azure primary, secondary fallback). Shape the Azure/AWS platform: identity, networking, LLMOps/MLOps, observability, and sovereign-hosting constraints. Run client workshops, write POVs and architecture packs, and stay accountable until the system is in production. About the work Pratham International programmes sit at the intersection of pedagogy, public systems, and production AI. The pattern is consistent across countries; the constraints change. Anytime Testing Machine (ATM) — India, practice and feedback End-to-end assessment for real classroom conditions: generate curriculum-aligned items, digitise handwritten answers (often photographed on a phone), grade against rubrics, and return feedback a teacher reviews before it reaches the learner. Built for high pupil–teacher ratios, mixed language (e.g. Hindi + English), and uneven connectivity. Pilots have already reached thousands of learners, including Second Chance (women returning for Grade 10). Model quality is measured against expert golden sets, not vendor slides. National assessment automation A government-grade exam platform. Phase 1 is item authoring and print-ready paper composition before the exam window. Phase 2 is script intake, OCR at national volume, AI-assisted grading with human confirmation on the pilot, results export, and monitoring/evaluation reporting. Subjects span core and elective streams across the curriculum. Design rules that do not exist in a typical SaaS product: cycle-pinned configuration, embargoed papers, hash-chained audit trails, and integration with national student information and assessment management systems. Curriculum knowledge graphs Structured retrieval corpora (concepts + worked examples) that ground generation and judging. This is the standing public-knowledge exception in an otherwise closed exam system, and the seed of a broader education DPI conversation. AI in TaRL and teacher support AI tools that help teachers group and teach by learning level, with an RCT-shaped evidence bar. Same product family: human agency stays in the loop; the model is a capacity multiplier. Country programmes and the three-year direction Adapt the same engine to new ministries, languages, and exam rules (Kenya and other Global South programmes are in scope). The longer bet is a learning and credentialing engine that recognises competence beyond a single syllabus. This is not a chatbot brief. It is constrained generation, retrieval, judging, document AI, workflow, and public-sector operations. Why this role exists Most enterprise AI dies between the workshop and production. We need one person who owns that gap: someone who can sit with NESA, C4IR, Pratham pedagogy, and engineering in the same week, and leave behind a blueprint the delivery team can execute without inventing policy. The target profile is a practising AI/ML Solution Architect — not a pre-sales slide owner, and not an infra-only platform engineer. The person should have done all three of these: Designed GenAI / NLP solutions, PoCs, and client workshops, and can talk to research-grade issues (eval, agent safety, prompt-injection, model-specific behaviour). Owned the AI platform: LLMOps, MLOps, DevSecOps, SRE habits, cloud migration, and FinOps. Taken messy discovery and turned it into Azure-centred RAG and multi-agent designs that a security team will accept. Key Responsibilities Discovery → architecture Lead solution workshops with programme, ministry, and engineering stakeholders. Convert half-formed requirements into service cuts, data stores, sequence diagrams, decision gates, and open-question lists with owners. Write architecture decision records. When the docs disagree (they will), force a decision instead of coding both. AI system design Design LLM jobs as contracts: inputs, JSON schema, temperature, persist prompt hash / model / tokens / latency. Architect generation grounded in structured curriculum blueprints and knowledge-graph retrieval, not "ask the model for a maths paper." Design LLM-as-judge banks (cognitive-level, relevance, difficulty, language, fairness, standards, duplication, blueprint compliance) with thresholds, one-repair rules, and golden-dataset release gates. Design hybrid assembly: constraint solver first, model only on ties and layout exceptions. Design document AI: primary OCR provider, secondary fallback provider, confidence routing, de-identification before any grading call. Specify eval: inter-rater agreement, rubric-band exact match, first-pass item acceptance, cost per paper cycle. Platform, trust, cost Own the reference architecture on the chosen cloud platform(s): identity, RBAC + segregation of duties, private networking, key management, object storage for scans, vector index, data warehouse for monitoring/evaluation reporting. Draw trust boundaries. Student PII never crosses the model gateway. Prompts are curriculum + knowledge-graph + blueprint content only. Put FinOps on the design: token budgets, OCR cost caps, degradation behaviour when a cap is hit, model routing. Specify LLMOps/MLOps: prompt/version registry, eval regression as a release gate, observability, rollback. Design for sovereign hosting and exam-cycle operations (embargo, watermarking, append-only audit, cycle-pinned configuration). Delivery and thought leadership Stay with the build through the first production cycle. Architecture that cannot be implemented is unfinished work. Produce POVs, sequence packs, and workshop artefacts that can be reused in the next country. Mentor tech leads on where the model should stop and the workflow should start. Success in the first two quarters First 30 days — Orient Complete architecture walkthroughs of every live/in-flight system with the current engineering leads; document current state (services, data stores, trust boundaries) as-is, not as-designed Meet every active stakeholder group once: engineering, programme/domain leads, and any external partner or government-side counterpart Inventory all open technical decisions and disagreements in existing specs; log each with current owner (if any) and status Identify the single highest-risk unresolved design question and flag it upward Day 60 — Diagnose Produce a current-state architecture diagram covering every major pipeline: data flow, model/LLM touchpoints, storage, and identity/access boundaries Assign an owner and target resolution date to every open contradiction identified in month 1 Draft a v1 reference architecture for one representative end-to-end workflow: service breakdown, data stores, identity/access model, model gateway placement, and a first-pass cost estimate Day 90 — Commit v1 reference architecture is reviewed and accepted by engineering and relevant stakeholders (not just self-signed) Can walk any core pipeline end-to-end from memory and name every data store, every quality/eval gate, and every trust boundary in it At least one architecture decision record is published for a previously-contested design question, with the decision forced rather than left open A first cost model exists for the reference architecture, with at least one identified lever for reducing spend if usage scales Day 120 — Harden Core pipeline components (generation, retrieval, judging/eval, or equivalent stages for this domain) have documented contracts: defined inputs/outputs, schema, and logged metadata (model, version, cost, latency) An evaluation harness exists for at least one component, with a defined pass/fail threshold A release gate exists that can block a bad prompt, model, or config change from reaching production Day 150 — Extend The next major system phase or capability is specified to the same rigor as the first: trust boundaries, failure modes, fallback behavior, and cost caps documented before build starts FinOps guardrails are in place for at least one production workload: budget ceilings, degradation behavior when a cap is hit, and a routing or fallback strategy Day 180 — Generalize A reusable design pattern or adaptation pack exists, separating what is fixed in the architecture from what varies by deployment context (e.g. language, hosting environment, external-system integration, content/domain rules) At least one engineering or technical lead has been mentored on where model-based logic should stop and deterministic/workflow logic should take over A second production-readiness review (security, cost, or operations) has been passed on a system this person designed or substantially redesigned Qualifications and Experience Must have 8+ years building software or data/AI systems, with recent experience as a Solution Architect, AI/ML Architect, or Principal/Staff Engineer with end-to-end architecture ownership. Shipped at least one production AI/ML system — RAG, multi-agent, LLM-as-judge, or a comparable classical ML/NLP pipeline at scale — that passed a real security, cost, and operations review, not just a pilot or a slide deck. Can produce a delivery-ready architecture blueprint: services, data stores, IAM, failure modes, evaluation strategy, and cost model — detailed enough that engineering isn't guessing at intent. Deep cloud experience on Azure and/or AWS: comfortable defending a landing-zone design, private-endpoint architecture, and a real monthly compute/inference/OCR spend. Fluent in Python, with hands-on experience in both classical ML (model training, evaluation, feature pipelines) and how LLM APIs, embeddings, and vector search actually behave under production load. Comfortable running a room with non-engineers — domain specialists, IT stakeholders, monitoring/evaluation teams — and translating fluently in both directions. Strong written English; this role's output is documentation that functions as a binding technical contract. Strongly preferred Azure AI (AI Foundry / OpenAI / Document Intelligence), plus one of AWS (Bedrock, SageMaker) or GCP (Vertex, BigQuery). LLMOps / MLOps: prompt + model versioning, MLflow or equivalent, eval harnesses, CI that can block a bad prompt. Document AI / OCR at volume; handwriting and low-quality scans, not only clean PDFs. RAG over structured knowledge (graphs, ToS, textbooks) and hybrid search, not only naive chunking. Education, assessment, public sector, or other high-audit domains (health, finance, identity). Certifications: Azure Data Scientist / Azure Solutions Architect; AWS SAA, ML Specialty, or Data Analytics Specialty. Experience with agent security: tool-use limits, DLP on egress, prompt-injection evaluation that is model-specific. FinOps discipline. You have killed a design because it would not survive the token bill. Nice to have Microsoft Fabric, Databricks, Semantic Kernel / Microsoft Agent Framework, MCP (Model Context Protocol) tool integration for agentic workflows. Constraint solvers or exam-blueprint / item-bank systems for automated test assembly. Multilingual generation and feedback, including code-mixed language pairs (e.g. Hindi–English, Spanish–English, or similar). Experience standing up golden/eval datasets with subject-matter experts. Prior work with government data systems, data-sharing agreements, or in-country/sovereign hosting requirements. What this role is not Not a research-only post. Publications help; shipping is the job. Not a pure platform/SRE hire. Infra is part of the design, not the whole design. Not a prompt engineer who hands off “the architecture” to someone else. Not a people manager of a large team on day one — you influence through artefacts and reviews. How we will assess you We value transparency and respect your time. Our hiring process is designed to evaluate both hands-on technical depth and architectural judgment through practical, real-world tasks. Stage 1: Application & Knockout Screening Submit your CV alongside key screening responses Artefact — send two of: architecture note, eval design, runbook, ADR. Slides without decisions do not count. Stage 2: Initial Conversation (30 mins) An introductory screen covering your background, project context and baseline alignment. An opportunity for you to ask questions about our technical roadmap, partner ecosystem, and vision. Stage 3: Practical Take-Home Written Assessment (2–3 hours) Design exercise on a constrained generation + judge + human-review pipeline (we will use a sanitised exam-authoring brief). We want trust boundaries, eval, and cost, not a model-name dump. Stage 4: Deep-Dive Technical & System Architecture Walkthrough Walkthrough of a system you shipped: what failed in review, what you changed, what it costs to run. Stage 5: Final Stakeholder & Vision Alignment Final conversation with key technical leadership and program stakeholders. Employment Details Function: Solutions / Architecture Reports to: Head of Technology / CTO Expected Start Date: Immediate Location: India (remote-first; travel to client workshops as needed) Experience: 8–13 years (strong 6–8 considered if you have shipped production GenAI) Engagement: Full-time Remuneration: Based on candidate’s experience and skillset Flexibility to work across timezones: Our team spans Latin America to Southeast Asia. Early mornings  or late evenings can be a regular part of the rhythm Why join us? Impact at Scale: Your work will directly support the learning journeys of millions of children. With programs active in 31 countries, you will help build Digital Public Goods that bridge the gap for the millions of children across the Global South who still struggle with foundational literacy Innovation at the intersection of Education and Technology: Lead the charge in redefining learning and learning processes through technology. You will contribute to the design and development of cutting-edge learning tools and AI-driven initiatives, ensuring EdTech isn’t just a buzzword, but a scalable solution for global equity. A Culture of Growth and Evidence: At Pratham, we value rigorous testing and continuous learning. You will have the autonomy to experiment with the latest SOTA models, supported by a 5-year strategic roadmap and funding from partners like the Gates Foundation and Anthropic. High-Calibre, Mission-Driven Team: You will work alongside a global team of experts from institutions like MIT, Harvard, and INSEAD. Our alumni have gone on to lead successful startups and international policy shifts, all while remaining dedicated to the goal of “Every Child in School and Learning Well.” Inclusive and Collaborative Environment: Join a diverse team that spans Asia, Africa, and Latin America. We value innovative thinking and local expertise, ensuring that the technology we build is deeply rooted in the realities of the communities we serve. Pratham International is an equal opportunity employer and encourages all qualified people from diverse backgrounds to apply for positions within our organisation, regardless of race, gender, disability or any other status.

Location: Paris Workplace: Hybrid ABOUT VOODOO Founded in 2013, Voodoo is a tech company that creates mobile games and apps with a mission to entertain the world. Gathering 800 employees, 7 billion downloads, and over 200 million active users, Voodoo is the #3 mobile publisher worldwide in terms of downloads after Google and Meta. Our portfolio includes chart-topping games like Mob Control and Block Jam, alongside popular apps such as BeReal and Wizz. TEAM The Engineering & Data team builds innovative tech products and platforms to support the impressive growth of their gaming and consumer apps which allow Voodoo to stay at the forefront of the mobile industry. The Engineering & Data team plays a key role in Voodoo's long-term strategy. It enables Voodoo to both accelerate product diversification and provide a state of the art growth-engine to distribute and scale our games. They create innovative solutions that drive growth with a pragmatic approach, ranging from simple searching to complex machine learning systems. ROLE We’re looking for a Senior Security Engineer to join our Engineering & Data team. In this role, you’ll be responsible for a wide variety of topics: - Security Engineering & Guardrails: Architect, construct, and maintain automated security guardrails and paved paths to foster secure-by-default development environments. - Shift-Left Architecture Guidance: Collaborate with development teams during the early ideation and design phases to embed secure coding practices and architecture from inception. - Continuous & Automated Assessment: Develop automated, continuous assessment capabilities that replace manual reviews and scale seamlessly across the business unit. - Hands-on Code Contribution: Work directly alongside engineers to contribute code for security fixes and paved-path solutions, ensuring security remains the simplest route. - Self-Service Tooling: Partner with developers to build scalable, self-service security tools that empower teams to detect and remediate risks independently. - Preventive & Detective Controls: Implement robust preventive and detective controls to deliver ongoing assurance rather than point-in-time security checks. - Strategic Collaboration & Incident Response: Drive long-term security strategy with key stakeholders while actively participating in periodic on-call rotations for incident support. - AI-Driven Security Innovation: Utilize AI technologies and methodologies to streamline threat detection, accelerate security evaluations, and advance scalable system protection. PROFILE (MUST HAVE) - 5+ years of experience troubleshooting systems, analyzing logs, and automating complex tasks via command-line tools - 5+ years of experience identifying security vulnerabilities, assessing risks, and constructing mitigation strategies - 5+ years of hands-on experience with scripting, software development, and security-focused code reviews across standard programming languages - Demonstrated expertise in recognizing industry-standard security vulnerabilities, understanding threat vector patterns, and applying effective remediation techniques - Proven track record in a leadership or guidance role, such as a technical lead, mentor, or engineering team lead - Proficiency in applying threat modeling and comprehensive risk identification methodologies - Proven track record securing microservices, service-oriented architectures, and web services - Experience with identity provider servers and authentication protocols (such as OAuth2, OIDC, SAML) - Experience with penetration testing (pentest) and vulnerability assessments - Self-starter with strong ownership, accountability, and ability to work autonomously and collaboratively across teams and organizations in a fast-paced environment. PROFILE (NICE TO HAVE) - Advocate for security standards with clarity and empathy. - Familiarity with AI/ML workflows and agents. OUR STACK Terraform, Kubernetes, Prometheus, ArgoCD, CircleCI, GitHub Actions, Atlantis, Grafana, Claude Code, Trivy, Conftest / OPA, AWS IAM Identity Center (SSO), Okta, AWS Secrets Manager, AWS KMS, AWS WAFv2, AWS Shield, AWS ACM, AWS GuardDuty, Sealed Secrets, Kyverno, cert-manager BENEFITS - Competitive salary based on experience - Swile Lunch voucher - Gymlib (100% covered by Voodoo) - Premium healthcare coverage with SideCare, 100% covered for you and your family - Wellness activities in our Paris office - Remote Fridays

Location: New York City Office COMPANY DESCRIPTION Today, when you go to your doctor and get referred to a specialist, your doctor sends out a referral and tells you, “They’ll be in touch soon.” So you wait. And wait. Sometimes days, weeks, or even months. Why? Because too often providers are overwhelmed with the painstakingly tedious work required to get paid by insurance companies. Powered by proprietary models, Tennr handles the complex paperwork that gets patients through the door and providers paid, helping operators get patients the right care, at the right time, in the right setting.   ROLE DESCRIPTION - Own the data engineering function end-to-end: build and maintain production pipelines from Tennr's application into Snowflake, ensuring reliability and performance at scale. - Lead EHR discovery and integration initiatives across ~5–10 healthcare systems. Understand what data is available, what integrations we have, evaluate technical tradeoffs, and build creative solutions to extract and ingest data into Snowflake. - Own Snowflake as our strategic data platform: architect instance setup, implement security best practices and governance, manage vendor relationships, and ensure zero data exposure. - Design and implement data models that transform raw data into usable assets. Surface and safely share that data across Tennr so internal teams can build their own analytics and tooling. - Implement comprehensive monitoring and alerting to detect pipeline issues quickly and resolve them with minimal business impact. - Explore innovative approaches to structure and extract insights from unstructured referral documentation, including potential AI-enabled models to unlock value from clinical text data. CANDIDATE QUALIFICATIONS - 3–5 years of experience in data engineering, with a strong track record of building and maintaining scalable data pipelines and infrastructure. - Proven expertise with Snowflake and modern cloud data platforms (e.g., AWS, GCP); hands-on experience with data pipeline tools and orchestration frameworks. - Strong understanding of healthcare data—claims, EHR systems, and data integration patterns—or demonstrated ability to quickly learn complex domain-specific systems. - Healthcare-data security awareness and familiarity with best practices (e.g., HIPAA considerations, data governance, compliance) is a strong plus. - Excellent problem-solving skills and comfort with complex, ambiguous integration challenges—not just standard connector configuration. - Outstanding communication skills, capable of articulating complex technical and healthcare concepts to a diverse audience. - A team player who thrives in collaborative environments and values diverse perspectives. - Prior experience in a startup or fast-paced tech environment is a plus. WHY TENNR? - Drive Impact: one of our company values is Cowboy, meaning you set the pace. You won’t just talk about things, you’ll get them done. And feel the impact. - Develop Operational Expertise: learn the inner workings of scaling systems, tools, and infrastructure - Innovate with Purpose: we’re not just doing this for fun (although we do have a lot of fun). At Tennr, you’ll join a high-caliber team maniacally focused on reducing patient delays across the U.S. healthcare system. - Build Relationships: collaborate and connect with like-minded, driven individuals in our Hudson Square office 4 days/week - Free lunch! Plus a pantry full of snacks.   BENEFITS - Beautiful new office at 345 Hudson Street - Unlimited PTO - 100% paid employee health benefit options - Employer-funded 401(k) match - Competitive parental leave

Location: Berlin Office; Netherlands; Portugal; Poland; Germany; United Kingdom; Spain Workplace: Remote The AI orchestration of your wildest imagination. n8n is the open workflow orchestration platform built for the new era of AI. We give technical teams the freedom of code with the speed of no-code, so they can automate faster, smarter, and without limits. Backed by a fiercely inventive community and 500+ builder-approved integrations, we’re changing the way people bring systems together and scale ideas for impact. Since our founding in 2019, we’ve grown into a diverse team of over 260 - working across Europe and the US, connected by a shared builder spirit and with our centre of gravity in Berlin. Along the way, we’ve: - Cultivated a community of more than 650,000 active developers and builders - Earned 190K+ GitHub stars, making us one of the world’s Top 40 most popular projects - Backed by top investors, from Sequoia’s first German seed to our SAP's recent strategic investment - bringing us to a $5.2bn valuation That’s the company we’ve built. Now we’d love to see what you can build. If you’re applying, try n8n out - whether you’re technical or not - and share a screenshot of your first workflow with us. The easiest place to start is here: app.n8n.cloud/register http://app.n8n.cloud/register. We’re in a defining moment of an incredible journey. Come and build with us. ABOUT THE ROLE Your mission: turn n8n's strategic partnerships into enterprise pipeline — and decide where our limited partner marketing resources go to make that happen. n8n works with some of the world's largest consulting and technology companies: global SIs such as Accenture, Capgemini and BCG, and technology partners such as SAP, Microsoft, AWS and NVIDIA. In May 2026 SAP made a strategic investment in n8n and announced plans to embed it in Joule Studio. Partnerships are now a core part of our enterprise go-to-market. The hard part isn't generating ideas. Partners propose more campaigns, events and content than any team could run, and enthusiasm doesn't always turn into execution. Without this role, we invest in winning partners and never turn them into pipeline. You'll fix that by choosing a few programs that matter, securing real commitments from both sides, and driving them to measurable results.   Set partner marketing priorities - Build integrated, multi-quarter marketing plans with our priority partners, aligned with the Partnerships team on where each relationship is heading - Rank opportunities on clear criteria — enterprise reach, joint value proposition, commercial upside, partner commitment and ability to execute — and say no, with reasons, to what doesn't make the cut - Tell a promising partnership apart from one that's ready to run joint marketing, and plan accordingly Run programs that create pipeline - Run partner programs choosing the right mix of joint content and customer stories, webinars and technical workshops, executive dinners and field events, joint campaigns, ABM and sales activation - Secure the people, budget and commitments needed on both sides, then keep programs moving from plan to execution across complex partner organisations - Work with Sales on partner lead management and follow-up, and with Field Marketing, Demand Gen, Product Marketing and DevRel on joint go-to-market programs Extend reach to Tier 2 and emerging-market partners - Build co-marketing programs with Tier 2 and regional partners, including in markets such as APAC where partners are our main route in - Adapt what works with strategic partners into lighter-weight programs that need less of our time Build foundations that scale - Turn your best programs into repeatable playbooks for every new strategic partner - Set up the measurement that links partner activity to engagement, qualified opportunities and partner-sourced pipeline, and run regular performance reviews with partners and internal stakeholders - Put partner marketing operations in place — and build them in n8n where it makes sense n8n is an equal opportunity employer and does not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, gender identity, age, marital status, veteran status, or disability status. We can sponsor visas to Germany; for any other country, you need to have existing right to work. Our company language is English. You care about diversity and inclusion? We do too! Check out our Diversity, Inclusion and Belonging initiatives at n8n https://www.notion.so/Diversity-inclusion-and-belonging-n8n-c1bec2fff536422d868b1a438d990e35?pvs=21 (https://www.notion.so/n8n/Diversity-inclusion-and-belonging-n8n-c1bec2fff536422d868b1a438d990e35). Location disclaimer: If you see multiple job postings for the same role, it is most likely because we're hiring remotely for this role and posting in different locations to make sure every potential candidate can see the role. Please apply to the location you're the most likely to work from in the future. BENEFITS - Competitive compensation 💸 – We offer fair and attractive pay. - Ownership 💪 – Our core value is to “empower others,” and we mean it—you’ll get a slice of n8n with equity. - Work/life balance 🏖️ – We work hard but ensure you have time to recharge: - Europe: 30 days of vacation, plus public holidays wherever you are. - US: 20 vacation days, 8 sick days, plus public holidays wherever you are. - Health & wellness 🩺 – - Europe: We provide benefits according to local country norms.* - US: Multiple low-premium, low-deductible medical plans with coverage for individuals and families—plus a no-cost premium HDHP option with a pre-seeded HSA—along with dental and vision coverage. - Future planning 💰 – - Europe: We provide pension contributions according to local country norms.* - US: 401(k) retirement plan with a 4% employer match. - Financial security 🛡️ – - Europe: We provide benefits according to local country norms.* - US: Company-paid short-term and long-term disability insurance, plus life insurance to support you and your loved ones. - Career growth 📈 – We hire rising stars who grow with us! You’ll get €1K (or equivalent) per year to spend on courses, books, events, or coaching to level up your skills. - A passionate team 🤩 – We love our product, and we prove it with regular hackathons where we see who can build the coolest thing with it! - Remote-first 🌏 – Our team works remotely across Europe, with regular off-sites for team bonding. Some roles, like sales in the US, are hybrid—please check the job description. - Giving back 🤝 – We're big fans of open source, and you'll get $100 per month to support projects you care about. - Transparency 🙏 – We all know what everyone’s working on, how the company is doing—the whole shebang. *Country and/or State specific details provided in your employment agreement.

Location: Tel Aviv-Yafo, Gush Dan, Israel About At-Bay We are an insurance company built by cybersecurity experts, leveraging our technology and security expertise to better understand digital risks and, thus, build better insurance products and services. We help clients by providing insurance products, guidance on their security issues, and active risk management. Like software, digital risk is eating the world and we aim to empower businesses to thrive in this ever-changing landscape. We are distributed globally with hubs in San Francisco, New York City, Atlanta, and Tel Aviv. We have aggressive plans to scale our business and believe the best way to make that happen is to immediately invest in further developing our teams. Responsibilities: Planning and execution of complex, diverse software delivery systems Work closely with the Data Team and build their infrastructure as a code Responsibility for building the CI/CD processes for Data Lakes, pipelines, ETL's etc. Take important part in the design & the architecture new workloads and components Research and integrate new technologies into our stack Automate everything. From enormous continuous integration, deployment and delivery pipelines, to small but life changing utilities. Qualifications: 4 years of experience as a DevOps Engineer Experience writing code with Python & Bash- a must Strong hands-on experience with AWS is- a must Experience working with Serverless and data components (Glue, sagemaker, EMR, Lamda's etc...) - an advantage Proficient in modern CI/CD techniques, GitOps (Jenkins, Github Actions, ArgoCD) Proven experience in managing production environment at scale in cloud environment Infrastructure as a code (IaaC), preferably Terraform - a must Independent, autodidact, creative problem solver with excellent debugging skills Location : Tel Aviv, Israel What you'll get A competitive salary, and equity in a super fast growing company, taking over commercial insurance A strong emphasis on work-life balance Beautiful offices in the heart of Tel Aviv, near the train station and main bus stops Passionate, smart, and fun people to work with You will never lack a challenge, we are a unique blend of a fast growing tech startup, an international firm, and an insurance company

Location: Paris Workplace: Hybrid ABOUT VOODOO Founded in 2013, Voodoo is a tech company that creates mobile games and apps with a mission to entertain the world. Gathering 800 employees, 7 billion downloads, and over 200 million active users, Voodoo is the #3 mobile publisher worldwide in terms of downloads after Google and Meta. Our portfolio includes chart-topping games like Mob Control and Block Jam, alongside popular apps such as BeReal and Wizz. TEAM Our Corporate teams support the company’s performance and growth whilst putting people at the core of everything they do. As a French tech leader and global successful company, our Corporate teams are constantly looking for ways to innovate and increase organization efficiency to keep Voodoo ahead of the market. Voodoo’s Corporate function is composed of three teams: HR, Legal and Finance, working together to drive Voodoo’s success. ROLE We're looking for an IT Administrator - AI & Cybersecurity to join our Corporate team. In this role, you'll own the intersection of IT operations, cybersecurity and AI platform administration, reporting directly to the IT Manager. IT & SaaS Administration - Administer the core SaaS stack - Okta (SSO, SCIM, lifecycle, policies), Google Workspace, Slack, Notion, GitHub Enterprise Cloud and 100+ applications across multiple legal entities - Own the MDM estate (Jamf and Intune) across macOS, iOS and Windows: enrolment, compliance baselines, patching and disk encryption - Act as the L2/L3 escalation point for internal support, handling endpoint, identity and SaaS incidents that L1 cannot resolve - Automate manual run work through scripting, APIs and AI agents where they genuinely add value Cybersecurity - Drive the identity hardening roadmap: session lifetimes, adaptive and phishing-resistant MFA, privileged access management and admin role reviews - Own OAuth and third-party app governance across Google Workspace and Okta: inventory, risk-scoring and approval workflows - Control SaaS data exposure - publicly and externally shared files, orphaned shares - and build the tooling to support it - Contribute to the ZTNA rollout, geo-based access controls and detection & response alongside the SOC and SIEM AI Platform Administration - Administer enterprise AI platforms (Claude, Google Gemini & Vertex AI, OpenAI and others): tenants, SSO, licences, usage analytics and budget control - Strengthen the AI governance framework: acceptable-use rules, data classification boundaries, DLP and logging - and detect shadow AI usage - Administer connectors, MCP servers and agent integrations PROFILE - 5+ years of experience in IT administration, infrastructure or IT security in a fast-moving, multi-geography environment - Deep hands-on expertise with IdP administration - Okta strongly preferred - and Google Workspace at enterprise scale - Solid MDM experience across macOS and Windows (Jamf and/or Intune) - Demonstrable cybersecurity practice: IAM hardening, SaaS security posture management, OAuth risk and incident response - you have shipped security work, not just studied it - Automation is a reflex: proficiency in scripting (Python, Bash, PowerShell) and working with REST APIs and workflow tools - Practical experience with enterprise AI platforms and a genuine understanding of the risks introduced by models, agents and connectors accessing corporate data - Able to communicate security trade-offs clearly to executives and technical workarounds to developers - Fluent English is required, French is a plus - Nice to have: security certifications (Security+, CISSP, Okta Certified), ZTNA/SASE or SSPM exposure, cloud IAM on GCP or AWS, ITSM platform experience BENEFITS - Competitive salary based on experience - Swile Lunch voucher - Gymlib (100% covered by Voodoo) - Premium healthcare coverage with SideCare, 100% covered for you and your family - Wellness activities in our Paris office - Remote Fridays

Про нас: В нашей ML-команде сейчас 5 человек. Мы работаем над: • AI-агентом для работы с облачным хранилищем и документами; • сервисом извлечения данных из контрактов и счетов; • RAG-базой знаний по Fileforce для клиентов; • системой поиска аномалий в пользовательских логах. В разработке активно используем современные AI-инструменты и кодинговые агенты (Claude Code, Codex) Задачи: • Разрабатывать новые и поддерживать/улучшать существующие проекты (backend+ML+участие в деплое), а также улучшать мониторинг и аналитику запущенных проектов Требования: • высшее техническое образование (диплом потребуется для оформления японской рабочей визы) • 3+ года опыта в Machine Learning; • опыт самостоятельного ведения проектов; • опыт с agentic/RAG-системами будет большим плюсом; • опыт разработки с помощью кодинговых агентов; • интерес к новым AI-технологиям и готовность постоянно разбираться в новых подходах; • английский на уровне свободного чтения технической документации • релевантный опыт с частью стека и способность быстро осваивать новое: LangGraph, DeepAgents, FastAPI, PostgreSQL, ClickHouse, Docker, vLLM, OpenAI API, AWS S3, Langfuse, OpenTelemetry, MCP, Redis, AWS SQS. Ответы на 10 важных вопросов: 1. Данные: работа преимущественно с данными (файлами различных форматов) компаний из хранилища через внутреннее API, AWS S3, Elasticsearch 2. Железо: на текущий момент преимущественно AWS инфраструктура, аренда VM под проекты и доступ к моделям по API. При экономической эффективности - собственное развертывание. Для работы: ПК в офисе, подключение к AWS VM по ssh, простой ноутбук для удаленной работы 3. Масштаб влияния на core-бизнес? Сейчас в компании упор на ML проекты, поскольку наша команда отвечает за все ML проекты, то влияние и высокие ожидания от проектов у руководства. 4. Уровень развития Data Science в компании? Запущено несколько крупных проектов, настроена основная инфраструктура/пайплайны (разработка, интеграция с внутренними сервисами, мониторинг, базовая аналитика, практика работы с кодинговыми агентами и тд), при этом улучшение процессов и вовлечения ML проектов в процессы компании продолжается. 5. Роль дата сайентиста: ДС-ы участвуют в проработке и реализации полного цикла проектов/фичей совместно с бэкенд и фронтенд командами 6. Бэкграунд у вашего руководителя? linkedin https://www.linkedin.com/in/nikita-vasilenko-ds/ 7. Как часто вам будут мешать работать? Daily meetings 15-20 мин + обсуждения прогресса/фичей внутри команды по мере необходимости 8. Карьерный рост: рост по зп возможен в рамках ежегодного планирования бюджета 9. Prod/Research: Prod 90% 10. Функция сервиса или лидера? На данном этапе сервисных функций больше.

Location: Canada (Remote) Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X . We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity. This is a remote opportunity, and we would be interested in applicants located in the US or Canada. The Opportunity: At Grafana Labs, we build observability tools that help users understand, respond to, and improve their systems – regardless of scale, complexity, or tech stack. We recently started a skunkworks initiative with a mission to bring observability to the rest of the business. Our goal is to make Grafana the single best place where humans and AI agents understand and act on real-time data from across the enterprise. As part of this initiative, we are building an AI-native data intelligence system that gives agents reliable, governed access to enterprise context. This system helps agents retrieve the right data, metadata, definitions, lineage, quality signals, and institutional knowledge without every agent builder having to maintain their own brittle context files. The principle is simple: the context system retrieves, agents decide, and data teams maintain the intelligence. The new team is a mix of seasoned Grafanistas and new hires. We operate with a high degree of autonomy and ownership, both as individuals and as a team. Engineers are empowered to make decisions, move quickly, and validate ideas early – while being supported by a deeply collaborative culture that values curiosity, feedback, and cross-functional partnership. We’re looking for a Senior Software (Database) Engineer to help build the underlying storage system for our general purpose data platform. The database layer has both OLAP and OTLP capabilities to support classic analytics queries while also serving up freshly stored data. It embraces the separation of compute and storage and is designed to run on multiple cloud providers. This is an early-stage role on a high-autonomy team, so you should be comfortable working through ambiguity, making pragmatic architectural decisions, and building systems that can evolve from internal dogfooding to production-grade SaaS. As the team matures, there’s a broad opportunity to expand or redefine this role based on impact and initiative. What You'll Be Doing: Take ownership over and build one or multiple parts of the database: Design, implement, test, and operate ingestion, query planning, distributed query execution, data formats, storage formats. Create a scalable SaaS foundation: Help define and build the architecture for a multi-tenant database service, including tenant isolation, usage tracking, quotas, audit logs, background jobs, and reliable service boundaries. Power agent-facing retrieval workflows: Build APIs and database interfaces that allow AI agents, MCP tools, CLIs, and internal applications to retrieve data quickly. Work across product and infrastructure: Partner with the team to make practical tradeoffs between fast experimentation and long-term reliability, especially as the project moves from prototype to production. Operate what you build: Instrument database services with metrics, logs, traces, alerts, and dashboards. Use observability tools to understand system behavior and improve reliability. Contribute to technical direction: Help shape the architecture, service boundaries, storage choices, API contracts, deployment patterns, and engineering practices for a new product area. Effective communication: You’ll be working in a highly dynamic and collaborative environment, so we need someone who can communicate effectively and contribute across teams. Ownership and impact: Take full ownership of the database solutions you develop, ensuring they are not only innovative but also scalable, maintainable, and aligned with real user workflows. What Makes You a Great Fit: Strong engineering skills: Solid experience building production-grade, user-facing software systems. You’re a self-starter, capable of tackling complex engineering problems and making design decisions with minimal supervision. AI experience with a practical mindset: You’re familiar with AI technologies and frameworks, and you focus on delivering high-quality solutions that work in the real world, not just in theory. Quick iteration and experimentation: You’re comfortable releasing prototypes, collecting feedback, and iterating with a pragmatic mindset. Proven initiative: You take ownership and drive projects forward, pushing boundaries to find the most impactful solutions. You can deal with ambiguity and are able to define scope where things are loosely defined. Collaborative attitude: You communicate effectively with your peers. You’re open to feedback, and you bring a solutions-oriented mindset to the table. Experience with distributed systems, catalogs and table formats, query engines. Mastery of a programming language like golang, C++, or Rust Proven track record of delivering software that made it into production and is actively used by users. Exposure to working in cloud-native environments (e.g., AWS, GCP, Azure). Experience using observability tools to understand and troubleshoot system behavior. Bonus Points for: Experience building distributed query engines. Experience building data warehouses and/or data lakes. Experience building tools for data engineering. How we work: We are a remote-first team that meets regularly over video and does most of our work asynchronously, in writing. We value creativity, diverse perspectives, and clear communication. Tempo is relied upon by prominent global organizations to monitor critical applications and infrastructure, and we expect everyone on the team, including our Staff engineers, to contribute ideas that make it a more reliable, more useful, and more loved product. Compensation & Rewards: In Canada, the Base compensation range for this role is $ 164,490 - $197,389. Actual compensation may vary based on level, experience, and skillset as assessed throughout the interview process. All of our roles include Restricted Stock Units (RSUs), giving every team member ownership in Grafana Labs' success. We believe in shared outcomes—RSUs help us stay aligned and invested as we scale globally. *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process. Why You’ll Thrive at Grafana Labs: 100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose. Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment. Transparent Communication – Expect open decision-making and regular company-wide updates. Innovation-Driven – Autonomy and support to ship great work and try new things. Open Source Roots – Built on community-driven values that shape how we work. Empowered Teams – High trust, low ego culture that values outcomes over optics. Career Growth Pathways – Defined opportunities to grow and develop your career. Approachable Leadership – Transparent execs who are involved, visible, and human. Passionate People – Join a team of smart, supportive folks who care deeply about what they do. In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it. Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable. Equal Opportunity Employer: Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow. Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings. #LI-Remote For information about how your personal data is used once you’ve applied to a job, check out our privacy policy .

Location: United States (Remote) Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X . We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity. This is a remote opportunity, and we would be interested in applicants located in the US or Canada. The Opportunity: At Grafana Labs, we build observability tools that help users understand, respond to, and improve their systems – regardless of scale, complexity, or tech stack. We recently started a skunkworks initiative with a mission to bring observability to the rest of the business. Our goal is to make Grafana the single best place where humans and AI agents understand and act on real-time data from across the enterprise. As part of this initiative, we are building an AI-native data intelligence system that gives agents reliable, governed access to enterprise context. This system helps agents retrieve the right data, metadata, definitions, lineage, quality signals, and institutional knowledge without every agent builder having to maintain their own brittle context files. The principle is simple: the context system retrieves, agents decide, and data teams maintain the intelligence. The new team is a mix of seasoned Grafanistas and new hires. We operate with a high degree of autonomy and ownership, both as individuals and as a team. Engineers are empowered to make decisions, move quickly, and validate ideas early – while being supported by a deeply collaborative culture that values curiosity, feedback, and cross-functional partnership. We’re looking for a Senior Software (Database) Engineer to help build the underlying storage system for our general purpose data platform. The database layer has both OLAP and OTLP capabilities to support classic analytics queries while also serving up freshly stored data. It embraces the separation of compute and storage and is designed to run on multiple cloud providers. This is an early-stage role on a high-autonomy team, so you should be comfortable working through ambiguity, making pragmatic architectural decisions, and building systems that can evolve from internal dogfooding to production-grade SaaS. As the team matures, there’s a broad opportunity to expand or redefine this role based on impact and initiative. What You'll Be Doing: Take ownership over and build one or multiple parts of the database: Design, implement, test, and operate ingestion, query planning, distributed query execution, data formats, storage formats. Create a scalable SaaS foundation: Help define and build the architecture for a multi-tenant database service, including tenant isolation, usage tracking, quotas, audit logs, background jobs, and reliable service boundaries. Power agent-facing retrieval workflows: Build APIs and database interfaces that allow AI agents, MCP tools, CLIs, and internal applications to retrieve data quickly. Work across product and infrastructure: Partner with the team to make practical tradeoffs between fast experimentation and long-term reliability, especially as the project moves from prototype to production. Operate what you build: Instrument database services with metrics, logs, traces, alerts, and dashboards. Use observability tools to understand system behavior and improve reliability. Contribute to technical direction: Help shape the architecture, service boundaries, storage choices, API contracts, deployment patterns, and engineering practices for a new product area. Effective communication: You’ll be working in a highly dynamic and collaborative environment, so we need someone who can communicate effectively and contribute across teams. Ownership and impact: Take full ownership of the database solutions you develop, ensuring they are not only innovative but also scalable, maintainable, and aligned with real user workflows. What Makes You a Great Fit: Strong engineering skills: Solid experience building production-grade, user-facing software systems. You’re a self-starter, capable of tackling complex engineering problems and making design decisions with minimal supervision. AI experience with a practical mindset: You’re familiar with AI technologies and frameworks, and you focus on delivering high-quality solutions that work in the real world, not just in theory. Quick iteration and experimentation: You’re comfortable releasing prototypes, collecting feedback, and iterating with a pragmatic mindset. Proven initiative: You take ownership and drive projects forward, pushing boundaries to find the most impactful solutions. You can deal with ambiguity and are able to define scope where things are loosely defined. Collaborative attitude: You communicate effectively with your peers. You’re open to feedback, and you bring a solutions-oriented mindset to the table. Experience with distributed systems, catalogs and table formats, query engines. Mastery of a programming language like golang, C++, or Rust Proven track record of delivering software that made it into production and is actively used by users. Exposure to working in cloud-native environments (e.g., AWS, GCP, Azure). Experience using observability tools to understand and troubleshoot system behavior. Bonus Points for: Experience building distributed query engines. Experience building data warehouses and/or data lakes. Experience building tools for data engineering. How we work: We are a remote-first team that meets regularly over video and does most of our work asynchronously, in writing. We value creativity, diverse perspectives, and clear communication. Tempo is relied upon by prominent global organizations to monitor critical applications and infrastructure, and we expect everyone on the team, including our Staff engineers, to contribute ideas that make it a more reliable, more useful, and more loved product. Compensation & Rewards: In the US, the Base compensation range for this role is $ 154,445 - $185,334. Actual compensation may vary based on level, experience, and skillset as assessed throughout the interview process. All of our roles include Restricted Stock Units (RSUs), giving every team member ownership in Grafana Labs' success. We believe in shared outcomes—RSUs help us stay aligned and invested as we scale globally. *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process. Why You’ll Thrive at Grafana Labs: 100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose. Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment. Transparent Communication – Expect open decision-making and regular company-wide updates. Innovation-Driven – Autonomy and support to ship great work and try new things. Open Source Roots – Built on community-driven values that shape how we work. Empowered Teams – High trust, low ego culture that values outcomes over optics. Career Growth Pathways – Defined opportunities to grow and develop your career. Approachable Leadership – Transparent execs who are involved, visible, and human. Passionate People – Join a team of smart, supportive folks who care deeply about what they do. In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it. Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable. Equal Opportunity Employer: Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow. Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings. #LI-Remote For information about how your personal data is used once you’ve applied to a job, check out our privacy policy .