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Location: Porto, Portugal Workplace: remote We are seeking a Prompt Engineer to be responsible for the end-to-end technical migration workflow for transitioning templates to LLM autoraters. The role is required to use client’s internal tools to leverage prompt engineering techniques to maximize model performance. Responsibilities: Utilize Automatic Prompt Generation (APG) tools to create baseline prompts for complex parent-child template clusters. Run and supervise Automated Prompt Optimization (APO) tool, review the outputs, and flag when the APO reaches deadlocks or plateaus. Manually draft, test, and refine prompts to navigate complex template architectures, overcome anti-patterns, and handle edge cases where tooling is lacking or broken. Solve edge-case scenarios by designing and refining manual prompts. Monitor shadowbot runs to ensure sufficient disagreements (between human and LLM ratings) are registered, generated, and tracked. Run prompt versions against established gold data to continuously measure autorater quality against the human crowd baseline, calculating accuracy metrics such as F1 scores, precision, and recall. Draft technical launch readiness justifications (Launch Certification Documentation) for final. Requirement: Language Skills : Native fluency in Portuguese and fluent in English. Location: Must be based in Portugal. Education : Bachelor’s, Master’s, or Doctorate degree in Computer Science, Data Science, Computational Linguistics, Human-Computer Interaction (HCI), Cognitive Science, or a related analytical field. Prompt Engineering & AI Expertise : At least 4 years' experience as Prompt Engineer. Proven experience tuning Large Language Models (LLMs) for strict, structured outputs, complex classification tasks, and familiarity with chain-of-thought and few-shot learning. Data Analysis : Strong proficiency in identifying error patterns, analyzing model performance, and using SQL or other data analytics tools. Technical Agility : Ability to quickly learn and master proprietary tools with minimal supervision. Communication : Excellent verbal and written communication skills. Optional / Preferred Skills: Familiarity with enterprise-grade LLM interfaces like the Goose API. Experience in AI model evaluation, data science, computational linguistics, or software engineering. Hands-on experience with Automated Prompt Optimization (APO) systems or tuning workflows. Linguistic expertise, including an understanding of semantics and logic.

Location: Netherlands Workplace: remote We are seeking a Prompt Engineer to be responsible for the end-to-end technical migration workflow for transitioning templates to LLM autoraters. The role is required to use client’s internal tools to leverage prompt engineering techniques to maximize model performance. Responsibilities: Utilize Automatic Prompt Generation (APG) tools to create baseline prompts for complex parent-child template clusters. Run and supervise Automated Prompt Optimization (APO) tool, review the outputs, and flag when the APO reaches deadlocks or plateaus. Manually draft, test, and refine prompts to navigate complex template architectures, overcome anti-patterns, and handle edge cases where tooling is lacking or broken. Solve edge-case scenarios by designing and refining manual prompts. Monitor shadowbot runs to ensure sufficient disagreements (between human and LLM ratings) are registered, generated, and tracked. Run prompt versions against established gold data to continuously measure autorater quality against the human crowd baseline, calculating accuracy metrics such as F1 scores, precision, and recall. Draft technical launch readiness justifications (Launch Certification Documentation) for final. Requirement: Language Skills : Native fluency in Dutch and fluent in English. Location: Must be based in Netherlands. Education : Bachelor’s, Master’s, or Doctorate degree in Computer Science, Data Science, Computational Linguistics, Human-Computer Interaction (HCI), Cognitive Science, or a related analytical field. Prompt Engineering & AI Expertise : At least 4 years' experience as Prompt Engineer. Proven experience tuning Large Language Models (LLMs) for strict, structured outputs, complex classification tasks, and familiarity with chain-of-thought and few-shot learning. Data Analysis : Strong proficiency in identifying error patterns, analyzing model performance, and using SQL or other data analytics tools. Technical Agility : Ability to quickly learn and master proprietary tools with minimal supervision. Communication : Excellent verbal and written communication skills. Optional / Preferred Skills: Familiarity with enterprise-grade LLM interfaces like the Goose API. Experience in AI model evaluation, data science, computational linguistics, or software engineering. Hands-on experience with Automated Prompt Optimization (APO) systems or tuning workflows. Linguistic expertise, including an understanding of semantics and logic.

Location: Japan Workplace: remote We are seeking a Prompt Engineer to be responsible for the end-to-end technical migration workflow for transitioning templates to LLM autoraters. The role is required to use client’s internal tools to leverage prompt engineering techniques to maximize model performance. Responsibilities: Utilize Automatic Prompt Generation (APG) tools to create baseline prompts for complex parent-child template clusters. Run and supervise Automated Prompt Optimization (APO) tool, review the outputs, and flag when the APO reaches deadlocks or plateaus. Manually draft, test, and refine prompts to navigate complex template architectures, overcome anti-patterns, and handle edge cases where tooling is lacking or broken. Solve edge-case scenarios by designing and refining manual prompts. Monitor shadowbot runs to ensure sufficient disagreements (between human and LLM ratings) are registered, generated, and tracked. Run prompt versions against established gold data to continuously measure autorater quality against the human crowd baseline, calculating accuracy metrics such as F1 scores, precision, and recall. Draft technical launch readiness justifications (Launch Certification Documentation) for final. Requirement: Language Skills : Native fluency in Japanese and fluent in English. Location: Must be based in Japan. Education : Bachelor’s, Master’s, or Doctorate degree in Computer Science, Data Science, Computational Linguistics, Human-Computer Interaction (HCI), Cognitive Science, or a related analytical field. Prompt Engineering & AI Expertise : At least 4 years' experience as Prompt Engineer. Proven experience tuning Large Language Models (LLMs) for strict, structured outputs, complex classification tasks, and familiarity with chain-of-thought and few-shot learning. Data Analysis : Strong proficiency in identifying error patterns, analyzing model performance, and using SQL or other data analytics tools. Technical Agility : Ability to quickly learn and master proprietary tools with minimal supervision. Communication : Excellent verbal and written communication skills. Optional / Preferred Skills: Familiarity with enterprise-grade LLM interfaces like the Goose API. Experience in AI model evaluation, data science, computational linguistics, or software engineering. Hands-on experience with Automated Prompt Optimization (APO) systems or tuning workflows. Linguistic expertise, including an understanding of semantics and logic.

Location: Italy Workplace: remote We are seeking a Prompt Engineer to be responsible for the end-to-end technical migration workflow for transitioning templates to LLM autoraters. The role is required to use client’s internal tools to leverage prompt engineering techniques to maximize model performance. Responsibilities: Utilize Automatic Prompt Generation (APG) tools to create baseline prompts for complex parent-child template clusters. Run and supervise Automated Prompt Optimization (APO) tool, review the outputs, and flag when the APO reaches deadlocks or plateaus. Manually draft, test, and refine prompts to navigate complex template architectures, overcome anti-patterns, and handle edge cases where tooling is lacking or broken. Solve edge-case scenarios by designing and refining manual prompts. Monitor shadowbot runs to ensure sufficient disagreements (between human and LLM ratings) are registered, generated, and tracked. Run prompt versions against established gold data to continuously measure autorater quality against the human crowd baseline, calculating accuracy metrics such as F1 scores, precision, and recall. Draft technical launch readiness justifications (Launch Certification Documentation) for final. Requirement: Language Skills : Native fluency in Italian and fluent in English. Location: Must be based in Italy. Education : Bachelor’s, Master’s, or Doctorate degree in Computer Science, Data Science, Computational Linguistics, Human-Computer Interaction (HCI), Cognitive Science, or a related analytical field. Prompt Engineering & AI Expertise : At least 4 years' experience as Prompt Engineer. Proven experience tuning Large Language Models (LLMs) for strict, structured outputs, complex classification tasks, and familiarity with chain-of-thought and few-shot learning. Data Analysis : Strong proficiency in identifying error patterns, analyzing model performance, and using SQL or other data analytics tools. Technical Agility : Ability to quickly learn and master proprietary tools with minimal supervision. Communication : Excellent verbal and written communication skills. Optional / Preferred Skills: Familiarity with enterprise-grade LLM interfaces like the Goose API. Experience in AI model evaluation, data science, computational linguistics, or software engineering. Hands-on experience with Automated Prompt Optimization (APO) systems or tuning workflows. Linguistic expertise, including an understanding of semantics and logic.

Location: Spain Workplace: remote We are seeking a Prompt Engineer to be responsible for the end-to-end technical migration workflow for transitioning templates to LLM autoraters. The role is required to use client’s internal tools to leverage prompt engineering techniques to maximize model performance. Responsibilities: Utilize Automatic Prompt Generation (APG) tools to create baseline prompts for complex parent-child template clusters. Run and supervise Automated Prompt Optimization (APO) tool, review the outputs, and flag when the APO reaches deadlocks or plateaus. Manually draft, test, and refine prompts to navigate complex template architectures, overcome anti-patterns, and handle edge cases where tooling is lacking or broken. Solve edge-case scenarios by designing and refining manual prompts. Monitor shadowbot runs to ensure sufficient disagreements (between human and LLM ratings) are registered, generated, and tracked. Run prompt versions against established gold data to continuously measure autorater quality against the human crowd baseline, calculating accuracy metrics such as F1 scores, precision, and recall. Draft technical launch readiness justifications (Launch Certification Documentation) for final. Requirement: Language Skills : Native fluency in Spanish and fluent in English. Location: Must be based in Spain. Education : Bachelor’s, Master’s, or Doctorate degree in Computer Science, Data Science, Computational Linguistics, Human-Computer Interaction (HCI), Cognitive Science, or a related analytical field. Prompt Engineering & AI Expertise : At least 4 years' experience as Prompt Engineer. Proven experience tuning Large Language Models (LLMs) for strict, structured outputs, complex classification tasks, and familiarity with chain-of-thought and few-shot learning. Data Analysis : Strong proficiency in identifying error patterns, analyzing model performance, and using SQL or other data analytics tools. Technical Agility : Ability to quickly learn and master proprietary tools with minimal supervision. Communication : Excellent verbal and written communication skills. Optional / Preferred Skills: Familiarity with enterprise-grade LLM interfaces like the Goose API. Experience in AI model evaluation, data science, computational linguistics, or software engineering. Hands-on experience with Automated Prompt Optimization (APO) systems or tuning workflows. Linguistic expertise, including an understanding of semantics and logic.

Location: France Workplace: remote We are seeking a Prompt Engineer to be responsible for the end-to-end technical migration workflow for transitioning templates to LLM autoraters. The role is required to use client’s internal tools to leverage prompt engineering techniques to maximize model performance. Responsibilities: Utilize Automatic Prompt Generation (APG) tools to create baseline prompts for complex parent-child template clusters. Run and supervise Automated Prompt Optimization (APO) tool, review the outputs, and flag when the APO reaches deadlocks or plateaus. Manually draft, test, and refine prompts to navigate complex template architectures, overcome anti-patterns, and handle edge cases where tooling is lacking or broken. Solve edge-case scenarios by designing and refining manual prompts. Monitor shadowbot runs to ensure sufficient disagreements (between human and LLM ratings) are registered, generated, and tracked. Run prompt versions against established gold data to continuously measure autorater quality against the human crowd baseline, calculating accuracy metrics such as F1 scores, precision, and recall. Draft technical launch readiness justifications (Launch Certification Documentation) for final. Requirement: Language Skills : Native fluency in French and fluent in English. Location: Must be based in France. Education : Bachelor’s, Master’s, or Doctorate degree in Computer Science, Data Science, Computational Linguistics, Human-Computer Interaction (HCI), Cognitive Science, or a related analytical field. Prompt Engineering & AI Expertise : At least 4 years' experience as Prompt Engineer. Proven experience tuning Large Language Models (LLMs) for strict, structured outputs, complex classification tasks, and familiarity with chain-of-thought and few-shot learning. Data Analysis : Strong proficiency in identifying error patterns, analyzing model performance, and using SQL or other data analytics tools. Technical Agility : Ability to quickly learn and master proprietary tools with minimal supervision. Communication : Excellent verbal and written communication skills. Optional / Preferred Skills: Familiarity with enterprise-grade LLM interfaces like the Goose API. Experience in AI model evaluation, data science, computational linguistics, or software engineering. Hands-on experience with Automated Prompt Optimization (APO) systems or tuning workflows. Linguistic expertise, including an understanding of semantics and logic.

Location: Germany Workplace: remote We are seeking a Prompt Engineer to be responsible for the end-to-end technical migration workflow for transitioning templates to LLM autoraters. The role is required to use client’s internal tools to leverage prompt engineering techniques to maximize model performance. Responsibilities: Utilize Automatic Prompt Generation (APG) tools to create baseline prompts for complex parent-child template clusters. Run and supervise Automated Prompt Optimization (APO) tool, review the outputs, and flag when the APO reaches deadlocks or plateaus. Manually draft, test, and refine prompts to navigate complex template architectures, overcome anti-patterns, and handle edge cases where tooling is lacking or broken. Solve edge-case scenarios by designing and refining manual prompts. Monitor shadowbot runs to ensure sufficient disagreements (between human and LLM ratings) are registered, generated, and tracked. Run prompt versions against established gold data to continuously measure autorater quality against the human crowd baseline, calculating accuracy metrics such as F1 scores, precision, and recall. Draft technical launch readiness justifications (Launch Certification Documentation) for final. Requirement: Language Skills : Native fluency in German and fluent in English. Location: Must be based in Germany. Education : Bachelor’s, Master’s, or Doctorate degree in Computer Science, Data Science, Computational Linguistics, Human-Computer Interaction (HCI), Cognitive Science, or a related analytical field. Prompt Engineering & AI Expertise : At least 4 years' experience as Prompt Engineer. Proven experience tuning Large Language Models (LLMs) for strict, structured outputs, complex classification tasks, and familiarity with chain-of-thought and few-shot learning. Data Analysis : Strong proficiency in identifying error patterns, analyzing model performance, and using SQL or other data analytics tools. Technical Agility : Ability to quickly learn and master proprietary tools with minimal supervision. Communication : Excellent verbal and written communication skills. Optional / Preferred Skills: Familiarity with enterprise-grade LLM interfaces like the Goose API. Experience in AI model evaluation, data science, computational linguistics, or software engineering. Hands-on experience with Automated Prompt Optimization (APO) systems or tuning workflows. Linguistic expertise, including an understanding of semantics and logic.

Location: Remote - US About the Job: Software powers the world, and LaunchDarkly empowers all teams to deliver and control the best software. As an Senior Infrastructure Engineer on the IDE team, you'll help us build, automate, and improve the systems that keep LaunchDarkly running at scale. Our platform serves over twenty trillion feature flags daily across a global AWS footprint. The IDE team owns the infrastructure layer — networking, compute, CI/CD, databases, observability — and we're looking for someone who wants to make that layer increasingly self-service and automated. You'll write software that replaces manual processes, build tools that help other engineers move faster, and contribute to a culture where operational toil is treated as a bug to be fixed, not a fact of life. As part of our you-build-it-you-run-it culture, all engineers participate in an on-call rotation. Responsibilities: Automate infrastructure provisioning, deployment, and operational workflows Build and improve internal tools and platforms that make other engineers more productive Manage and evolve our AWS infrastructure using Terraform Participate in on-call rotations and turn incident patterns into permanent fixes Collaborate with product engineering teams to understand their infrastructure needs and reduce friction Identify repetitive operational work and replace it with software Qualifications: 8+ years of professional software engineering experience Familiarity with AWS (you've used it; you don't need to have memorized every service) You write code to solve problems — not just configuration, but actual software when the situation calls for it You're curious about how things work and willing to learn new tools quickly A commitment to working in a communicative and collaborative environment You hold yourself and others to a high bar when working with production systems You value code quality, automated testing, and engineering best practices Nice to have (but not required): Experience with Terraform or similar Infrastructure-as-Code tools Experience with CI/CD systems (GitHub Actions, Jenkins, etc.) Familiarity with containers and Kubernetes Experience with observability tools like Datadog Pay: Target pay ranges based on Geographic Zones* for Level 4: Zone 1: San Francisco/Bay Area or NYC Metropolitan Area, Boston, Seattle - $191,800 - $263,670** Zone 2: Irvine, LA, Monterey, Santa Barbara, Santa Rosa, Austin, Portland, Philadelphia, Chicago - $172,600 - $237,270** Zone 3: All other US locations - $ 163,000 - $224,070 * LaunchDarkly operates from a place of high trust and transparency; we are happy to state the pay range for our open roles to best align with your needs. Exact compensation may vary based on skills, experience, and location. *Within the United States, our geographic pay zones are defined by counties surrounding major metropolitan areas. **Restricted Stock Units (RSUs), health, vision, and dental insurance, and mental health benefits in addition to salary. About LaunchDarkly: Modern software delivery was supposed to be the foundation for a thriving digital business but reality has proven otherwise. Slow, inefficient development cycles, costly outages, and fragmented customer experiences are preventing developers from building their best software. The LaunchDarkly platform helps developers innovate on new features faster while protecting them with a safety valve to instantly rewind when things go wrong. Developers can target product experiences to any customer segment and maximize the business impact of every feature. And by gradually rolling out new application components, they escape nightmare "big-bang" technology migrations. The LaunchDarkly platform was built to guide engineers to the next frontier of DevOps by: Improving the velocity and stability of software releases, without the fear of end customer outages Delivering targeted experiences by easily personalizing features to customer cohorts Maximizing the business impact of every feature through the ability to experiment and optimize Coordinating the release and optimization of software to provide consistent experiences across mobile platforms and device types Improving the effectiveness and productivity of engineering teams, by providing insights into engineering cadence and stability At LaunchDarkly, we believe in the power of teams. We're building a team that is humble, open, collaborative, respectful and kind. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, veteran status, or disability status. LD invites any applicant to review our written Affirmative Action Plan. To do so, contact People Ops at hr@launchdarkly.com . Do you need a disability accommodation? Fill out this accommodations request form and someone from our People Operations team will contact you for assistance. Your safety matters to us. To protect yourself from potential scams, LaunchDarkly recruiters will only contact you from @ launchdarkly.com email addresses or via LinkedIn from "Verified Recruiter" accounts. Be cautious of emails from other domains.  Legitimate LaunchDarkly recruiters will never ask for money, fees, or banking information before making a job offer. LaunchDarkly will never make a job offer without conducting a formal interview process. Our interview process does not involve asking detailed questions by email. If you are ever unsure about a communication that you receive, don't click any links—visit Careers | LaunchDarkly directly for confirmed job openings and links to apply. Please notify us of any fraudulent representation by sending an email to careers@launchdarkly.com .

Location: South Africa; Mexico; Colombia; Panama; Brazil; Argentina About Huzzle At Huzzle, we connect exceptional B2B professionals with top opportunities at leading companies across the UK, US, Canada, Europe, and Australia. Our clients include startups, digital agencies, and tech platforms in industries such as SaaS, MarTech, FinTech, and EdTech. Unlike an outsourcing agency, we place you directly with a client where you’re hired in-house as a valued member of their team. About the Company This opportunity is with a fast-growing AI-powered Go-To-Market (GTM) systems company focused on helping modern revenue teams scale efficiently. The company builds automation-driven revenue engines that turn market signals into qualified pipeline. Their infrastructure combines AI agents, workflow automation, outbound platforms, and CRM architecture to help growth-stage companies ($1M–$100M+ ARR) build systematic competitive advantages without scaling headcount. Job Type: Full-time Location: Remote Engagement: Independent Contract Key Responsibilities CRM Architecture & Revenue Systems Own the company’s HubSpot CRM architecture end-to-end including pipelines, lifecycle stages, workflows, custom properties, and reporting. Design scalable revenue data models that align CRM activity with pipeline and revenue outcomes. Define and enforce data standards across the GTM stack including HubSpot, Airtable, outbound tooling, and AI systems. Conduct ongoing CRM audits and maintain data integrity, deduplication, and attribution accuracy . Revenue Analytics & Reporting Build reporting frameworks that track pipeline health, revenue velocity, conversion rates, and retention metrics . Develop dashboards that help leadership understand what’s happening in the business in real time . Deliver strategic revenue insights and performance reports to executive leadership. Build client-facing analytics dashboards used for operational reviews and strategic decision-making. RevOps Consulting & Client Delivery Conduct RevOps assessments and CRM audits for client organizations. Design and implement HubSpot and CRM infrastructure including automation, integrations, and reporting. Operate as a senior RevOps advisor in client engagements, providing guidance on pipeline architecture, analytics, and systems strategy. Develop playbooks and frameworks that enable RevOps delivery to scale. Systems Integration & Automation Build and manage automation workflows using n8n or equivalent integration tools . Connect CRM systems with outbound tools, enrichment platforms, and operational databases. Implement integrations between CRM systems and billing platforms such as Stripe. Use AI tools to automate reporting, data analysis, documentation, and operational workflows. RevOps Practice Development Help build and scale the RevOps practice within the organization . Contribute to hiring and mentoring junior RevOps analysts and operations specialists. Develop internal frameworks and best practices for RevOps service delivery. Requirements Core Qualifications Deep HubSpot CRM architecture expertise with experience building systems from the ground up. Proven experience designing revenue pipelines, lifecycle models, and CRM data structures . Hands-on experience building integrations using n8n, Zapier, Make, APIs, or webhook-based workflows . Strong revenue analytics skills , including pipeline coverage modeling, CAC analysis, and cohort retention analysis. Experience implementing automation-driven GTM systems across CRM, outbound tools, and data platforms. Working knowledge of Salesforce CRM , including data models, reporting, and migration planning. Ability to translate complex operational data into clear strategic recommendations . Preferred Experience Experience delivering RevOps consulting or agency-style CRM implementations . Hands-on production experience with n8n automation workflows . Experience integrating Stripe or billing platforms with CRM systems . Familiarity with AI tools used in operations workflows (e.g., AI-assisted reporting, workflow automation, documentation generation). Experience hiring or mentoring RevOps analysts or CRM administrators . Benefits 💻 Fully Remote: Work from anywhere with international teams 🚀 Career Growth: Join companies in SaaS, MarTech, and B2B services 🤝 Peer Community: Connect with high-performing sales professionals in our network 🧭 Ongoing Support: Receive guidance from Huzzle before and after placement

Location: Riyadh, Saudi Arabia; Cairo, Egypt; Delhi, India; Casablanca, Morocco; Dubai, United Arab Emirates Müller’s Solutions is looking for a Google Cloud Application Modernization Specialist to drive our application modernization initiatives. In this role, you will work closely with clients to assess their existing applications and transform them into modern, cloud-native solutions using Google Cloud technologies. Your expertise will enable organizations to leverage the flexibility, scalability, and innovation that Google Cloud offers. Key Responsibilities: Evaluate existing application architectures and identify opportunities for modernization using GCP services. Design and implement cloud-native architectures that enhance application performance and scalability. Guide clients through the application migration process, ensuring best practices are followed to minimize downtime and disruptions. Collaborate with development teams to refactor and containerize applications for deployment on Google Kubernetes Engine (GKE) or App Engine. Facilitate workshops and training sessions to educate clients about cloud technologies and modernization strategies. Assess and implement DevOps practices and CI/CD pipelines to streamline application delivery and operations. Monitor and optimize modernized applications to ensure they meet performance, security, and compliance standards. Document modernization processes, architectures, and lessons learned for knowledge sharing within the organization. Stay current with industry trends, emerging technologies, and Google Cloud advancements related to application modernization. Requirements Requirements: Bachelor's degree in Computer Science, Information Technology, or a related field. 5+ years of experience in application development, architecture, or modernization, with a strong focus on Google Cloud Platform. Proven experience with microservices architecture, containerization, and orchestration technologies like Kubernetes. Strong understanding of Google Cloud services related to application development, such as Cloud Run, Cloud Functions, and BigQuery. Experience with programming languages such as Java, Python, or Go in developing cloud-native applications. Solid knowledge of DevOps practices and tools for continuous integration and delivery. Excellent communication skills, with the ability to guide and influence clients and technical teams. Strong problem-solving abilities and a passion for technology and innovation. Preferred Qualifications: Google Cloud certifications (e.g., Google Cloud Professional Cloud Architect or Google Cloud Professional Application Developer) are a plus. Experience with legacy application modernization and migration strategies. Familiarity with Agile methodologies and practices. Previous experience working directly with clients in consulting or customer-facing roles. Benefits Why Join Us: Opportunity to work with a talented and passionate team. Competitive salary and benefits package. Exciting projects and innovative work environment.

Location: San Francisco, CA | New York City, NY | 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 Anthropic is seeking Software Engineers to join our Observability team within the Infrastructure organization. The Observability team owns the monitoring and telemetry infrastructure that every engineer and researcher at Anthropic depends on, from metrics and logging pipelines to distributed tracing, profiling, error analytics, alerting, and the dashboards and query interfaces that make it all actionable. By joining this team, you'll have a direct impact on the reliability and operational excellence of Anthropic's research and product systems. As Anthropic scales its infrastructure across large GPU, TPU, and Trainium clusters, the volume and complexity of operational data is growing by orders of magnitude, and an increasing share of the most challenging problems live below the application layer. We're building next-generation observability systems, including high-throughput telemetry pipelines, fleet-wide continuous profiling, eBPF-based tracing and network visibility, and agentic diagnostic tools, so engineers can detect, diagnose, and resolve issues in minutes rather than hours, even when the answer lies in the kernel, the network stack, or an accelerator rather than on a dashboard. Key responsibilities Design and build scalable telemetry ingest and storage pipelines for metrics, logs, traces, and error data across Anthropic's multi-cluster infrastructure Build observability solutions that give engineers deep, low-overhead visibility into system behavior across the fleet Own and evolve core observability platforms, leading migrations and architectural improvements that improve reliability, reduce cost, and scale with organizational growth Build instrumentation libraries, SDKs, and eBPF-based auto-instrumentation to emit high-quality telemetry, with and without code changes Reduce mean time to detection and resolution by building cross-signal correlation (from kernel-level events up to application traces), unified query interfaces, and AI-assisted diagnostic tooling Improve fleet-wide efficiency by turning continuous profiling and utilization telemetry into actionable optimization insights across CPU, memory, and accelerator fleets Partner with Research, Inference, Product, and Infrastructure teams to ensure observability solutions meet the unique needs of each organization Minimum qualifications Experience building and operating large-scale observability or monitoring infrastructure Hands-on experience with observability signals end to end, from instrumentation through ingest to query and analysis Understanding of high-throughput telemetry pipelines and the tradeoffs involved in collecting, storing, and querying operational data at scale Comfort debugging below the application layer, in the kernel, the network stack, or the hardware Excellent communication skills and the ability to partner with internal teams to improve their operational visibility and incident response capabilities Ability to work independently on ambiguous, high-impact technical challenges Preferred qualifications Experience building or operating eBPF-based observability in production, such as tracing, profiling, or network visibility Experience running continuous profiling at fleet scale, including managing overhead budgets and symbolization Kernel- and syscall-level debugging experience and performance engineering skills Experience profiling or instrumenting accelerator workloads Experience operating metrics systems at very high cardinality, or large-scale telemetry storage backends Experience with log storage migrations or operating columnar databases (e.g., ClickHouse, BigQuery) for analytics workloads Experience with OpenTelemetry instrumentation, collector pipelines, and tail-based sampling strategies Interest in applying AI/LLMs to operational workflows such as automated root cause analysis, anomaly detection, or intelligent alerting Enthusiasm for building foundational infrastructure 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. 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: Riyadh, Saudi Arabia; Cairo, Egypt; Delhi, India; Dubai, United Arab Emirates; Casablanca, Morocco Müller’s Solutions is on the hunt for a skilled Google Cloud Architect to lead our cloud strategy initiatives and design innovative solutions using Google Cloud Platform (GCP). In this crucial role, you will be responsible for developing scalable, secure, and efficient cloud architectures that meet business requirements while guiding teams on best practices in cloud implementation and governance. Key Responsibilities: Design and architect scalable, reliable, and cost-effective GCP solutions aligned with business objectives. Collaborate with stakeholders to gather requirements and translate them into technical solutions leveraging GCP services. Develop and implement standards, guidelines, and best practices for GCP architectures across the organization. Lead migration efforts of existing applications and systems to GCP, ensuring best practices around security and compliance are followed. Conduct cloud readiness assessments and application architecture evaluations to identify needed improvements. Oversee the integration of cloud services with on-premises components or external platforms as necessary. Advise on cloud strategies, best practices, and industry trends to senior management and technical teams. Provide technical leadership and mentorship to engineering teams, promoting cloud-native development methodologies. Build and maintain documentation for cloud solutions, architectures, and processes. Engage with vendor management to evaluate and select relevant cloud services and tools. Requirements Requirements: Bachelor's degree in Computer Science, Information Technology, or a related field. 5+ years of experience in cloud architecture, with a strong focus on Google Cloud Platform. Proven experience in designing and implementing complex architectures on GCP, including compute, storage, and networking. Deep understanding of GCP services and capabilities, including BigQuery, Cloud Functions, and Kubernetes Engine. Expertise in Infrastructure as Code (IaC) practices using tools like Terraform or Cloud Deployment Manager. Strong knowledge of cloud security principles and best practices for governance and compliance. Excellent communication and collaboration skills to work effectively with diverse teams and stakeholders. Strong problem-solving skills and the ability to think critically in fast-paced environments. Preferred Qualifications: Google Cloud certifications (e.g., Google Cloud Professional Cloud Architect or Google Cloud Professional DevOps Engineer) are highly desirable. Experience with DevOps practices, CI/CD pipelines, and automation tools. Familiarity with open-source technologies and frameworks relevant to GCP architecture. Experience in cloud cost management and optimization techniques. Benefits 1- Attractive Package. 2- Family Benefits. 3- Visa. 4-Air Tickets.

Location: Riyadh, Saudi Arabia Müller’s Solutions is looking for an experienced Azure Cloud Engineer to join our dynamic team. In this role, you will be responsible for designing, deploying, and managing our Azure cloud infrastructure, ensuring the scalability, security, and performance of our applications. You will collaborate with various teams to facilitate the migration of services to Azure and optimize our cloud environment for efficiency and cost-effectiveness. Key Responsibilities: Management of Azure virtual machines Configuration and management of Azure networking Administration of storage in Azure Management of Azure Active Directory / Microsoft Entra ID Optimization of costs (FinOps) and monitoring of budgets Configuration of Azure Monitor and performance tracking Administration of Microsoft Defender for Cloud Configuration of backups and daily monitoring & validation of backup processes Execution of quarterly Disaster Recovery (DR) testing Management of Azure Backup and on-premises backup solutions Monitoring and reporting on Recovery Time Objective (RTO) and Recovery Point Objective (RPO) Oversight of Microsoft 365 backup processes Design and implement Azure solutions that align with best practices and meet organizational needs. Oversee the management and monitoring of Azure resources including virtual machines, storage accounts, and networking elements. Automate the deployment and operational processes using Infrastructure as Code (IaC) tools, such as Terraform or Azure Resource Manager (ARM) templates. Integrate on-premises infrastructure with Azure services to create hybrid cloud solutions. Ensure compliance and governance standards for security across all Azure environments. Maintain documentation of architecture diagrams, operational procedures, and guidelines for best practices. Collaborate with development teams to facilitate efficient operational processes and application delivery. Identify and resolve issues with Azure services, determining root causes and implementing effective solutions.tions. Requirements Requirements: Bachelor's degree in Computer Science, Information Technology, or a related field. 3+ years of experience in cloud engineering or architecture, with a focus on Microsoft Azure. Strong understanding of Azure services and tools including Azure Virtual Machines, Azure Functions, and Azure App Services. Experience with scripting and automation using PowerShell, Azure CLI, or other automation tools. Familiarity with networking concepts and security principles in cloud environments. Excellent problem-solving skills and attention to detail. Effective communication skills to work collaboratively in a team-oriented environment. Preferred Qualifications: Microsoft Azure certifications (e.g., Azure Solutions Architect Expert or Azure DevOps Engineer) are highly desirable. Experience with DevOps practices and tools (e.g., CI/CD pipelines, Azure DevOps). Knowledge of containerization technologies such as Docker and Kubernetes. Experience with monitoring tools such as Azure Monitor, Application Insights, or third-party solutions. Benefits 1- Attractive Package. 2- Family Benefits. 3- Visa. 4-Air Tickets.

Location: San Francisco, CA | New York City, NY | 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 As a Technical Program Manager on the Compute team, you will help drive the planning, coordination, and execution of programs that keep Anthropic's compute infrastructure running efficiently at scale. Our compute fleet is the foundation on which every model training run, evaluation, and inference workload depends. You'll join a small, high-impact TPM team and take ownership of critical workstreams across the compute lifecycle, from how supply is procured and brought online, to how capacity is allocated and utilized across teams. The exact focus will depend on your strengths and the team's evolving needs. You'll partner with Infrastructure, Systems, Research, Finance, and Capacity Engineering to shape the processes, tooling, and coordination mechanisms that allow Anthropic to move fast while managing an increasingly complex compute environment. Responsibilities: Own and drive critical programs across the compute lifecycle, coordinating execution across multiple engineering, research, and operations teams Build and maintain operational visibility into the compute fleet, ensuring the organization has a clear picture of supply, demand, utilization, and health Lead cross-functional coordination for compute transitions: bringing new capacity online, migrating workloads, and managing decommissions across cloud providers and hardware platforms Partner with engineering and research leadership to navigate competing priorities and drive alignment on how compute resources are planned, allocated, and used Identify and close operational gaps across the compute pipeline, whether through new tooling, improved processes, or better cross-team communication Own trade-off discussions between utilization, cost, latency, and reliability, synthesizing inputs from technical and business stakeholders and communicating decisions to leadership Develop and improve the processes and frameworks the team uses to plan, track, and execute compute programs at increasing scale and complexity You may be a good fit if you: Have 7+ years of technical program management experience in infrastructure, platform engineering, or compute-intensive environments Have led complex, cross-functional programs involving multiple engineering teams with competing priorities and ambiguous requirements Have experience working with research or ML teams and translating their needs into operational plans and technical requirements Are comfortable diving deep into technical details (cloud infrastructure, cluster management, job scheduling, resource orchestration) while maintaining program-level visibility Thrive in ambiguous, fast-moving environments where you need to define scope and build processes from the ground up Have strong communication skills and can engage credibly with engineers, researchers, finance, and executive leadership Have a track record of building trust with engineering teams and driving changes through influence rather than authority Strong candidates may also have: Experience managing compute capacity across multiple cloud providers (AWS, GCP, Azure) or hybrid cloud/on-premises environments Familiarity with job scheduling, resource orchestration, or workload management systems (Kubernetes, Slurm, Borg, YARN, or custom schedulers) Experience with GPU or accelerator infrastructure, including the unique challenges of large-scale ML training and inference workloads Built or improved observability for infrastructure systems: dashboards, alerting, efficiency metrics, or cost attribution Capacity planning experience including demand forecasting, cost modeling, or hardware lifecycle management Scaled through hypergrowth in AI/ML, HPC, or large-scale cloud environments Deadline to Apply: None, applications will be received on a rolling basis. 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: $290,000 — $365,000 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. 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: Riyadh, Saudi Arabia; Dammam, Saudi Arabia; Al Khobar, Saudi Arabia Eram Talent is seeking a proficient Master Data Management (MDM) Business Analyst - Informatica to join our dynamic team. In this role, you will serve as a key liaison between business stakeholders and technical teams to ensure that Informatica-based MDM solutions effectively meet organizational data management needs. You will be responsible for gathering and documenting business requirements, analyzing existing data processes, and collaborating with technical teams on solution design and implementation. You will also help in identifying data quality issues, facilitate data governance activities, and support ongoing MDM initiatives to improve data accuracy, consistency, and compliance. If selected, the work location would be onsite at Al Khobar. Key Responsibilities Collaborate with business stakeholders to understand their master data requirements, document data definitions, and analyze data structures for optimal data management. Plan and execute data migration activities, including data mapping, data extraction, transformation, and loading (ETL) processes, during system upgrades or platform transitions. Ensure compliance with data security and privacy regulations, implement access controls, and monitor data usage to protect sensitive master data. Conduct thorough analysis of existing master data sets to identify discrepancies, anomalies, and opportunities for improvement, providing actionable insights to stakeholders. Develop and generate reports, dashboards, and data visualizations to provide insights into master data quality, trends, and performance, supporting decision-making processes. Facilitate change management activities related to master data management initiatives, including communication, training, and stakeholder Develop and enforce master data governance policies, standards, and processes to ensure data quality, consistency, and compliance with regulatory requirements. Collaborate with business users and IT teams to map data sources, define data hierarchies, and create data models that support effective master data management. Define and implement data standardization rules and processes to harmonize master data elements across disparate systems and business units. Coordinate the integration of master data management solutions with existing enterprise systems, ensuring seamless data flow and interoperability. Requirements Bachelor’s degree in Information Technology, or equivalent from a recognized and accredited university is required 5+ Years of Work Experience as a Master Data Management (MDM) Business Analyst or similar role is required. Certified Data Privacy Solutions Engineer (CDPSE) preferred Certifications in MDM or Informatica is highly preferred. Experience in Information Technology / Data Solutions / Networking / Cybersecurity preferred Proven experience as a Business Analyst, specifically in Master Data Management (MDM). Strong understanding of MDM principles, data governance, and data quality management. Experience with MDM tools (e.g., Informatica, SAP MDG, Oracle) is a plus. Excellent analytical and problem-solving skills. Strong communication and interpersonal skills to effectively engage with stakeholders.

Location: Rotterdam, Netherlands Workplace: on-site At TechBiz Global, we are providing recruitment service to our TOP clients from our portfolio. We are currently seeking a 1st/2nd Line Desktop Support Engineer to join one of our clients ' teams. If you're looking for an exciting opportunity to grow in a innovative environment, this could be the perfect fit for you. Job Overview: We are urgently seeking an enthusiastic IT professional to join our technical services team for an international client. This role is for a 1st Line Support Engineer who will be responsible for resolving technical issues and providing support across various hardware and software platforms. Key Responsibilities: Resolve laptop/desktop and networking issues, liaising with users when necessary. Provide support and maintenance for application software. Assist in the technical implementation of PC hardware applications for user environments. Ensure that software/hardware implementations adhere to change control guidelines, procedures, and methodologies. Handle incident and service request resolution, including hardware component changes. Support incidents and service support requests from other groups, including distributed servers and printers. Perform equipment maintenance and hardware repairs. Manage installation, moves, additions, changes, and disposal (IMACD) services. Key Duties: Installation: Deliver ready-to-use computers, install hardware, perform software license migration, conduct performance tests, and obtain user approval. Move: Disconnect and pack equipment for transport, reconnect and start up equipment at destination locations. Change: Perform equipment changes and conduct performance tests to ensure functionality. Maintenance and Repair: Perform software updates, hardware changes (mouse, screen, keyboard, dock station, etc.), and compatibility reviews. Helpdesk/Desktop Support experience. Proficiency in MS Windows. Ability to meet targets and SLAs. Strong knowledge of laptop and desktop hardware/software. Networking knowledge. Experience with hardware/software recovery, updating, and installation. Ability to perform Windows installations. Strong communication skills. Excellent organizational skills and attention to detail. Dutch language skills are required.

Location: Singapore Workplace: Remote The Technical Account Manager ("TAM") Architect role will be a member of our Support Services team and Support group, planned to report into our regional Support Engineering Managers. This new role will perform functions that our existing team already provides in part: ongoing TAM, Consultative, and Support functions working with a set of customers providing Consultative Support, Escalation insights, and oversight. TAM Architects will also be assisting with Support Cases for enterprise customers in an L3 role (Support Level 3 = Escalated cases). NOTE: This person can be remote in Singapore, but must be open to regional travel as required for onsite customer visits across the APJ region. A TAM Architect will be successful in the role if they provide the following aptitude and approach: - Highly technical with a focus on providing useful solutions to our users, customers, and prospects - Great communicator with team members and customers - Consulting, support, and project management skills and background - 50% of the work will be case-initiated consultative support of strategic users/customers/prospects - 50% of the work will be TAM functions (project guidance, onboarding coordination, escalations, communications, documentation, roadmap, meeting leadership) - Some onsite regional travel will be required, estimated currently at up to 35% of the time WHAT YOU WILL DO: - Work with strategic and enterprise ClickHouse users, customers, and prospects as identified by ClickHouse Sales to work on onboarding, production launches, and POCs - Provide architectural, technical, and migration guidance and assistance - Lead projects, escalations, and meetings to enable ongoing user/customer success - Ownership and oversight of L3 Support Cases and Escalations, working closely with the Support L1/L2 team - Partner closely with ClickHouse Product Management, Engineering, and Sales to help develop the roadmap and account plans - Be present and available according to the scheduling and onsite travel required to deliver high-quality 24x7 Support in a global, distributed environment - Assist with hiring and mentoring new team members - Develop and assist with Docs, Knowledge Base articles, ClickHouse Learning, Reference Architecture, and QA needs WHAT YOU BRING ALONG: - 5+ years of experience in Technical Account Management, Professional Services, Senior Support, and/or Project Management roles - 5+ years of relevant industry experience in implementing, operating, and/or supporting  operating scalable, fault-tolerant, distributed database management systems ("DBMS") - Technical breadth and depth in relevant subjects such as DBMS, OLAP, Cloud/SaaS platforms, distributed systems software engineering, Linux/Unix, Kubernetes, System or Network Administration, and big data - Experience leading and shipping large scope technical projects in collaboration with multiple experienced engineers. - Expertise with a public cloud provider (AWS, GCP, Azure) and their infrastructure as a service offering (e.g. EC2). - Excellent communication skills and the ability to work in a customer-facing role and in close collaboration with the Support Services, Engineering, and Sales teams - A mindset of teamwork, global engagement, empathy, and solving challenging problems - A sense of adventure and urgency in building the most scalable, highest performing, largest, and fastest databases on the planet - Self-driven, curious, and eager to continuously learn and grow PERKS - Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries. - Healthcare - Employer contributions towards your healthcare. - Equity in the company - Every new team member who joins our company receives stock options. - Time off - Flexible time off in the US, generous entitlement in other countries. - A USD$500 Home office setup if you’re a remote employee. - Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites. CULTURE - WE ALL SHAPE IT As part of a rapidly scaling start-up, you will be instrumental in shaping our culture. Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse. EQUAL OPPORTUNITY & PRIVACY ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.

Location: San Francisco; Stockholm; New York; London Workplace: OnSite ABOUT US: AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. THE ROLE: Modal is hiring a high-impact Solutions Architect to drive technical strategy across our most strategic enterprise accounts. You will operate as the executive technical counterpart to Enterprise Account Executives, leading complex evaluations, shaping infrastructure modernization roadmaps, and driving multi-product adoption across AI/ML workloads. This role is not demo support. It is a strategic, consultative position requiring strong architectural depth, executive presence, and the ability to influence 7–8 figure infrastructure decisions. You will work directly with CTOs, VPs of Engineering, and ML platform leaders to help them rethink how AI infrastructure should be built and operated. If you thrive in high-velocity technical sales environments and want to shape the infrastructure layer powering modern AI companies, this role is for you. WHAT YOU’LL DO: - Own the technical strategy for large, complex enterprise accounts - Partner with Enterprise Account Executives to drive 6–7+ figure opportunities from qualification through close - Lead deep technical discovery across platform, ML, DevOps, and infrastructure stakeholders - Architect end-to-end migration strategies from AWS, GCP, or Azure to Modal’s serverless infrastructure - Drive executive-level technical conversations that connect infrastructure architecture to business impact (velocity, cost efficiency, reliability) - Design and oversee proof-of-concepts that demonstrate production-grade scalability and performance - Navigate security reviews, compliance discussions, and procurement processes with confidence - Build durable relationships with technical champions and executive sponsors - Orchestrate cross-functional virtual account teams (Sales, Product, Engineering, Support) to ensure successful adoption - Influence Modal’s product roadmap by surfacing structured enterprise feedback - Mentor other Solutions Architects and contribute to technical best practices across the team REQUIREMENTS: - 5+ years in Solutions Engineering, Sales Engineering, or enterprise-facing technical roles in infrastructure, cloud, or developer platforms - Demonstrated success driving complex enterprise sales cycles ($250K+ ACV; experience with $1M+ ARR accounts strongly preferred) - Experience working with large, sophisticated Bay Area technology companies or global enterprises - Deep expertise in cloud infrastructure (AWS, GCP, Azure) including compute, networking, storage, and managed services - Strong architectural understanding of containers and orchestration (Docker, Kubernetes) - Experience designing distributed systems and production data platforms - Strong working knowledge of ML/AI infrastructure (training pipelines, inference systems, GPU workloads, MLOps) - Experience leading cloud migration or infrastructure modernization initiatives - Familiarity with Infrastructure as Code (Terraform, Pulumi, CloudFormation) and CI/CD systems - Production programming experience in Python strongly preferred - Executive-level communication skills with the ability to influence technical and business stakeholders - Proven ability to lead cross-functional virtual teams in high-stakes account environments - Strong business acumen and understanding of enterprise procurement and buying processes - Willingness to travel up to 30%