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Location: London Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. We are looking for an experienced Trading Systems Software Engineer to help build the applications, platforms and engineering capabilities that support QRT’s global trading environment. This is a broad software engineering role spanning application development, distributed systems, cloud technology, deployment automation and production engineering. You will design and build software used by traders, quantitative researchers, operations teams and other engineers across the firm. Your Future Role within QRT Design, develop and maintain production-grade applications, services and APIs supporting QRT’s trading platform. Build shared platforms and reusable capabilities that can be adopted across multiple trading desks and engineering teams. Develop modern web applications and operational tools that improve visibility, control and efficiency across trading workflows. Design scalable distributed and event-driven systems that integrate with trading platforms, market data services and internal infrastructure. Build deployment tooling, release automation and self-service capabilities that make software easier and safer to deploy and operate. Develop automated workflows for data processing, operational tasks and engineering processes using technologies such as Apache Airflow. Partner with traders, quantitative researchers and operations teams to understand their needs and solve practical business problems. Design software for latency-sensitive environments, balancing performance with reliability, scalability and operational simplicity. Build observable and resilient systems with appropriate monitoring, alerting, recovery and failure-handling capabilities. Work alongside infrastructure, cloud and DevOps engineers to deploy and support software across global production environments. Contribute to technical design and architectural decisions, evaluating new technologies where they can deliver meaningful value. Take ownership of software throughout its lifecycle, from initial design and implementation through to production support and continuous improvement. Your present skillset At least five years of experience developing and supporting production-grade software. Strong programming and software engineering skills in one or more languages such as Python, Java, Go, Node.js or C++. Experience designing maintainable, testable and scalable applications and services. A strong understanding of software design principles, data structures, algorithms and engineering fundamentals. Experience building RESTful APIs, distributed systems or event-driven architectures. Exposure to containerisation, orchestration and delivery technologies such as Docker, Kubernetes and CI/CD pipelines. Experience with public cloud technologies, preferably AWS. An understanding of messaging technologies such as Kafka or RabbitMQ. Experience considering reliability, observability, performance and failure recovery when designing production systems. Strong analytical and problem-solving skills, with the ability to make sound engineering decisions and explain the associated trade-offs. The ability to work effectively with both technical and non-technical stakeholders. QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees to achieve a healthy work-life balance.

Location: Paris; Linz; Munich; London; Berlin Workplace: Remote ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. The Role Mistral AI is looking for AI Scientists with deep machine learning expertise and hands-on engineering experience to expand what Mistral's agentic tools can do across the engineering lifecycle across CAE (CFD, FEA etc) and EDA/Semi.. Within AI4Engineering Science, your core work is building the pre and post-training data for Mistral's LLMs to reason about and execute real engineering tasks. Alongside this, you'll help shape the agent architectures and harness that let these models operate reliably inside multi-step engineering workflows, not just answer isolated questions. You'll work closely with domain experts across CAE and EDA to ground this work in how engineers actually work, and with the broader research team to translate that domain grounding into training signal and evaluation benchmarks that measure genuine task competence. What You Will Do - Design pretraining, SFT, and RL data for engineering tasks across CAD, CAE, and semiconductor/EDA - Define verifiers and evaluation criteria that capture what "correct" and "high-quality" actually mean for each engineering task, beyond surface-level plausibility - Design and improve agent architectures and harnesses: how models plan, call tools, recover from errors, and chain steps together across long-horizon engineering workflows - Build evaluation benchmarks and diagnostic tooling to identify where models fail on engineering tasks, and trace those failures back to gaps in data, reward design, or agent scaffolding - Collaborate with domain experts across CAEand EDA (and the science and solutions teams more broadly) to identify which engineering workflows are highest-value to target next - Contribute to Mistral's broader pre and post-training research, sharing findings and methodology across the science organization What We're Looking For - Fluent English with excellent communication skills, able to explain technical ML and engineering concepts to both engineering and non-technical audiences - Deep, hands-on machine learning expertise, particularly LLM development - Demonstrated experience running, debugging, and validating real engineering workflows in at least one of CAD, CAE, semiconductor simulation, or EDA. - You write clean, readable Python code and are comfortable in Linux/HPC environments - Self-directed, you don't need detailed roadmaps to make progress - Low-ego, collaborative, and eager to learn at the intersection of engineering and ML It would be great if you - Have experience building or fine-tuning agentic systems (tool use, multi-step planning, agent orchestration frameworks) - Have experience with reward modeling, RLHF/RLAIF/RLVR, or preference-based training - Have industrial or academic experience with CAE, or EDA tools (e.g. SolidWorks, CATIA, Fluent, Abaqus, LS-DYNA, STAR-CCM+, Cadence/Synopsys/Siemens EDA tools) - Have contributed to a large open-source or industry codebase - Have publications in engineering and ML venues (NeurIPS, ICLR, JFM, AIAA, etc.)   WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: Poland Workplace: fully About Us We are a recruitment agency specializing in fintech and iGaming. We help international companies find and hire strong professionals across Europe and beyond, offering both recruitment and staffing services. Role Overview Take ownership of the automation stack and turn manual processes into reliable workflows used every day. You will work across n8n, PostgreSQL, JavaScript and AI integrations, with the scope to improve existing systems and build new solutions. The work involves Docker and Git, and close collaboration with skilled colleagues across the business. Key Responsibilities Build and improve n8n workflows connecting recruitment, sales and finance tools. Design PostgreSQL tables and views, write reporting queries and maintain consistent data across systems. Write JavaScript in n8n Code nodes for data transformation, API calls and custom logic. Build AI-powered steps for candidate scoring, data enrichment and text generation, including prompt design and model cost control. Integrate tools through REST APIs and webhooks, and adapt integrations when vendor APIs change. Monitor workflow runs, investigate failures and resolve root causes. Gather requests from recruiters, team leads and finance, then deliver working solutions. Document workflows, the data model and key technical decisions. Requirements Proven experience automating business processes used daily by non-technical teams. Hands-on experience building and maintaining production workflows in n8n. PostgreSQL skills in schema and view design, complex SQL reporting and data synchronisation. Working knowledge of JavaScript for data processing and API integrations. Experience integrating LLM APIs, such as OpenAI, into business workflows, including prompt design. Practical knowledge of REST APIs, webhooks and authentication methods, including OAuth and API keys. Git, Docker and basic Linux server administration are a plus. Languages: English B2, Russian C1. Key Soft Skills Independence, ownership and accountability. A structured approach and attention to detail. Clear communication with non-technical users. Analytical thinking and pragmatic problem-solving. What We Offer Competitive salary aligned with experience. Collaborative and transparent team culture. Recognition of personal milestones and achievements.

Location: Armenia Workplace: fully About Us We are a recruitment agency specializing in fintech and iGaming. We help international companies find and hire strong professionals across Europe and beyond, offering both recruitment and staffing services. Role Overview Take ownership of the automation stack and turn manual processes into reliable workflows used every day. You will work across n8n, PostgreSQL, JavaScript and AI integrations, with the scope to improve existing systems and build new solutions. The work involves Docker and Git, and close collaboration with skilled colleagues across the business. Key Responsibilities Build and improve n8n workflows connecting recruitment, sales and finance tools. Design PostgreSQL tables and views, write reporting queries and maintain consistent data across systems. Write JavaScript in n8n Code nodes for data transformation, API calls and custom logic. Build AI-powered steps for candidate scoring, data enrichment and text generation, including prompt design and model cost control. Integrate tools through REST APIs and webhooks, and adapt integrations when vendor APIs change. Monitor workflow runs, investigate failures and resolve root causes. Gather requests from recruiters, team leads and finance, then deliver working solutions. Document workflows, the data model and key technical decisions. Requirements Proven experience automating business processes used daily by non-technical teams. Hands-on experience building and maintaining production workflows in n8n. PostgreSQL skills in schema and view design, complex SQL reporting and data synchronisation. Working knowledge of JavaScript for data processing and API integrations. Experience integrating LLM APIs, such as OpenAI, into business workflows, including prompt design. Practical knowledge of REST APIs, webhooks and authentication methods, including OAuth and API keys. Git, Docker and basic Linux server administration are a plus. Languages: English B2, Russian C1. Key Soft Skills Independence, ownership and accountability. A structured approach and attention to detail. Clear communication with non-technical users. Analytical thinking and pragmatic problem-solving. What We Offer Competitive salary aligned with experience. Collaborative and transparent team culture. Recognition of personal milestones and achievements.

Location: Serbia Workplace: fully About Us We are a recruitment agency specializing in fintech and iGaming. We help international companies find and hire strong professionals across Europe and beyond, offering both recruitment and staffing services. Role Overview Take ownership of the automation stack and turn manual processes into reliable workflows used every day. You will work across n8n, PostgreSQL, JavaScript and AI integrations, with the scope to improve existing systems and build new solutions. The work involves Docker and Git, and close collaboration with skilled colleagues across the business. Key Responsibilities Build and improve n8n workflows connecting recruitment, sales and finance tools. Design PostgreSQL tables and views, write reporting queries and maintain consistent data across systems. Write JavaScript in n8n Code nodes for data transformation, API calls and custom logic. Build AI-powered steps for candidate scoring, data enrichment and text generation, including prompt design and model cost control. Integrate tools through REST APIs and webhooks, and adapt integrations when vendor APIs change. Monitor workflow runs, investigate failures and resolve root causes. Gather requests from recruiters, team leads and finance, then deliver working solutions. Document workflows, the data model and key technical decisions. Requirements Proven experience automating business processes used daily by non-technical teams. Hands-on experience building and maintaining production workflows in n8n. PostgreSQL skills in schema and view design, complex SQL reporting and data synchronisation. Working knowledge of JavaScript for data processing and API integrations. Experience integrating LLM APIs, such as OpenAI, into business workflows, including prompt design. Practical knowledge of REST APIs, webhooks and authentication methods, including OAuth and API keys. Git, Docker and basic Linux server administration are a plus. Languages: English B2, Russian C1. Key Soft Skills Independence, ownership and accountability. A structured approach and attention to detail. Clear communication with non-technical users. Analytical thinking and pragmatic problem-solving. What We Offer Competitive salary aligned with experience. Collaborative and transparent team culture. Recognition of personal milestones and achievements.

Location: Tbilisi, Georgia Workplace: fully About Us We are a recruitment agency specializing in fintech and iGaming. We help international companies find and hire strong professionals across Europe and beyond, offering both recruitment and staffing services. Role Overview Take ownership of the automation stack and turn manual processes into reliable workflows used every day. You will work across n8n, PostgreSQL, JavaScript and AI integrations, with the scope to improve existing systems and build new solutions. The work involves Docker and Git, and close collaboration with skilled colleagues across the business. Key Responsibilities Build and improve n8n workflows connecting recruitment, sales and finance tools. Design PostgreSQL tables and views, write reporting queries and maintain consistent data across systems. Write JavaScript in n8n Code nodes for data transformation, API calls and custom logic. Build AI-powered steps for candidate scoring, data enrichment and text generation, including prompt design and model cost control. Integrate tools through REST APIs and webhooks, and adapt integrations when vendor APIs change. Monitor workflow runs, investigate failures and resolve root causes. Gather requests from recruiters, team leads and finance, then deliver working solutions. Document workflows, the data model and key technical decisions. Requirements Proven experience automating business processes used daily by non-technical teams. Hands-on experience building and maintaining production workflows in n8n. PostgreSQL skills in schema and view design, complex SQL reporting and data synchronisation. Working knowledge of JavaScript for data processing and API integrations. Experience integrating LLM APIs, such as OpenAI, into business workflows, including prompt design. Practical knowledge of REST APIs, webhooks and authentication methods, including OAuth and API keys. Git, Docker and basic Linux server administration are a plus. Languages: English B2, Russian C1. Key Soft Skills Independence, ownership and accountability. A structured approach and attention to detail. Clear communication with non-technical users. Analytical thinking and pragmatic problem-solving. What We Offer Competitive salary aligned with experience. Collaborative and transparent team culture. Recognition of personal milestones and achievements.

Location: Cyprus; Finland; Ireland; Malta; Montenegro; Sweden What you'll be solving A platform engineer opens their AI client of choice, connects it to CAST AI, and types: "Why did our spend jump 40% in eu-west last week?" Thirty seconds later they have an answer, pulled from live cluster state and cost data, with links back to the evidence. No dashboards. No YAML archaeology. Just a question and a correct, permission-checked answer. Your job is to make that interaction boring. Reliably, securely, at production scale. Behind it sits the hard part: an AI assistant that reasons over thousands of production Kubernetes clusters, a platform that safely exposes company infrastructure to external AI clients, and quality pipelines that tell us when the agent is wrong before a customer does. Get it right, and operators stop clicking through consoles entirely. Get it wrong once, and an agent gives a confidently wrong answer to someone managing production. CAST AI already runs Kubernetes infrastructure autonomously. Our automation makes thousands of cost-and-reliability decisions a day. Cast Pilot is the team building the intelligence layer on top of that: AI assistants for Kubernetes and the cloud itself . Our assistant already answers thousands of questions a month from hundreds of organizations. Now we're opening the platform up: a public, permission-aware MCP server so customers can plug CAST AI straight into their own AI clients and agents, deeper connectivity across all three major clouds (AWS, GCP, Azure), and a continuous push to make our agents smarter, better grounded, and more capable. This is greenfield AI platform work on top of battle-tested infrastructure. Most features ship in 1 to 4 weeks. This is a location-specific opportunity. We are currently accepting applications from candidates residing in the following European countries: Bulgaria, Croatia, Estonia, Greece, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Cyprus, Malta, Finland, Sweden, Ireland, Moldova, North Macedonia, Montenegro, Slovenia, and Ukraine. Requirements Strong software engineering fundamentals: you design clean abstractions, write maintainable code, and can justify your architecture choices, not just make something work. You're a generalist who is as comfortable debugging a distributed system as designing an auth flow or tuning an agent's behavior. Production experience with Go is strongly preferred; candidates without Go should demonstrate strong systems programming skills in a comparable language. Experience building or operating large-scale SaaS platforms in production: multi-tenant systems, high volumes, and the failure modes that only show up at scale. Solid understanding of Kubernetes. Our entire platform runs on it, and the assistants we build answer questions about it. You should be at home with autoscaling, scheduling, and networking concepts. You've personally driven a complex project end-to-end. Hands-on experience with AI coding agents and agentic development workflows. This is how we build, not just what we build. You've used observability tooling in production. CI/CD and DevOps practices experience. Strong English skills, both verbal and written. Startup mindset: adaptable, proactive, and comfortable with ambiguity. What will make you stand out You've built agentic systems that shipped : MCP servers or clients, agent gateways, tool-use orchestration, RAG pipelines, evaluation frameworks, and you can talk about what broke in production and how you found out. This is the single biggest differentiator for our team. Deep hands-on experience with one or more of AWS, GCP, or Azure, with real understanding of IAM, compute, networking, and their APIs, not just console-level usage. Experience with LLM application quality: evaluations, prompt engineering at scale, latency and cost optimization of agent loops. Knowledge of OAuth 2.0 / OIDC and multi-tenant authorization design. Deep knowledge of EKS, GKE, or AKS internals. Kubernetes or cloud-native OSS contributions. Responsibilities Design and build the systems behind our AI assistant: agent flows, context retrieval, and the data connections that let it reason about live Kubernetes infrastructure. Build and evolve our public, permission-aware MCP server : curated tools, identity, audit, and strict safety gates, so customers can use CAST AI from their own AI clients. Develop and maintain cloud connectivity across AWS, GCP, and Azure, and the data foundations our agents build on. Write production Go services that interact with cloud provider APIs, the Kubernetes control plane, and LLM APIs in real time. Own features end-to-end: from design through implementation, testing, and production rollout (most projects ship in 1 to 4 weeks). Debug novel problems: an agent giving a wrong answer, a cross-cloud permission edge case, a data freshness issue that only appears at scale. Build the quality harness: evals, telemetry, feedback loops, that let us ship agent improvements without regressions. Contribute to product direction and backlog. Shape what gets built next, not just how it's built. Participate in the team's on-call rotation. Tools We Use Daily Programming Languages: Go AI & Agents: MCP (servers and clients), agent gateways, LLM provider APIs, RAG, evaluation pipelines Cloud & Orchestration: Kubernetes, AWS, GCP, Azure Infrastructure as Code: Terraform Databases & Storage: PostgreSQL, Cloud Object Storage, ClickHouse Workflows & APIs: Temporal, GCP Pub/Sub, gRPC, REST Observability & Product Analytics: Prometheus, Grafana, Loki, Tempo, PostHog CI/CD & GitOps: GitLab/GitHub CI with ArgoCD and Kargo What's in it for you? Competitive salary (€6,500 to €9,000 gross, depending on the level of experience) Work on genuinely new problems: production MCP platforms and AI assistants for Kubernetes and cloud infrastructure are not solved domains. You'll be defining them, not following a playbook. Equity options. Real users, fast: your work ships to hundreds of organizations in weeks, not quarters. Enjoy a flexible, remote-first global environment. Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology. Spend 10% of your work time on personal projects or self-improvement. Learning budget for professional and personal development, including access to international conferences and courses. Annual hackathon to spark new ideas and strengthen team bonds. Team-building budget and company events to connect with your colleagues. Equipment budget to ensure you have everything you need. Extra days off to help maintain a healthy work-life balance. Hiring process Screening call with Recruiter Hiring Manager interview Technical interview (system design) Live coding Culture Check interview with an executive As part of our standard hiring process, a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr. Please note that Cast AI does not provide any form of visa sponsorship/work permit. #LI-Remote

Location: European Union What you'll be solving A platform engineer opens their AI client of choice, connects it to CAST AI, and types: "Why did our spend jump 40% in eu-west last week?" Thirty seconds later they have an answer, pulled from live cluster state and cost data, with links back to the evidence. No dashboards. No YAML archaeology. Just a question and a correct, permission-checked answer. Your job is to make that interaction boring. Reliably, securely, at production scale. Behind it sits the hard part: an AI assistant that reasons over thousands of production Kubernetes clusters, a platform that safely exposes company infrastructure to external AI clients, and quality pipelines that tell us when the agent is wrong before a customer does. Get it right, and operators stop clicking through consoles entirely. Get it wrong once, and an agent gives a confidently wrong answer to someone managing production. CAST AI already runs Kubernetes infrastructure autonomously. Our automation makes thousands of cost-and-reliability decisions a day. Cast Pilot is the team building the intelligence layer on top of that: AI assistants for Kubernetes and the cloud itself . Our assistant already answers thousands of questions a month from hundreds of organizations. Now we're opening the platform up: a public, permission-aware MCP server so customers can plug CAST AI straight into their own AI clients and agents, deeper connectivity across all three major clouds (AWS, GCP, Azure), and a continuous push to make our agents smarter, better grounded, and more capable. This is greenfield AI platform work on top of battle-tested infrastructure. Most features ship in 1 to 4 weeks. This is a location-specific opportunity. We are currently accepting applications from candidates residing in the following European countries: Bulgaria, Croatia, Estonia, Greece, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Cyprus, Malta, Finland, Sweden, Ireland, Moldova, North Macedonia, Montenegro, Slovenia, and Ukraine. Requirements Strong software engineering fundamentals: you design clean abstractions, write maintainable code, and can justify your architecture choices, not just make something work. You're a generalist who is as comfortable debugging a distributed system as designing an auth flow or tuning an agent's behavior. Production experience with Go is strongly preferred; candidates without Go should demonstrate strong systems programming skills in a comparable language. Experience building or operating large-scale SaaS platforms in production: multi-tenant systems, high volumes, and the failure modes that only show up at scale. Solid understanding of Kubernetes. Our entire platform runs on it, and the assistants we build answer questions about it. You should be at home with autoscaling, scheduling, and networking concepts. You've personally driven a complex project end-to-end. Hands-on experience with AI coding agents and agentic development workflows. This is how we build, not just what we build. You've used observability tooling in production. CI/CD and DevOps practices experience. Strong English skills, both verbal and written. Startup mindset: adaptable, proactive, and comfortable with ambiguity. What will make you stand out You've built agentic systems that shipped : MCP servers or clients, agent gateways, tool-use orchestration, RAG pipelines, evaluation frameworks, and you can talk about what broke in production and how you found out. This is the single biggest differentiator for our team. Deep hands-on experience with one or more of AWS, GCP, or Azure, with real understanding of IAM, compute, networking, and their APIs, not just console-level usage. Experience with LLM application quality: evaluations, prompt engineering at scale, latency and cost optimization of agent loops. Knowledge of OAuth 2.0 / OIDC and multi-tenant authorization design. Deep knowledge of EKS, GKE, or AKS internals. Kubernetes or cloud-native OSS contributions. Responsibilities Design and build the systems behind our AI assistant: agent flows, context retrieval, and the data connections that let it reason about live Kubernetes infrastructure. Build and evolve our public, permission-aware MCP server : curated tools, identity, audit, and strict safety gates, so customers can use CAST AI from their own AI clients. Develop and maintain cloud connectivity across AWS, GCP, and Azure, and the data foundations our agents build on. Write production Go services that interact with cloud provider APIs, the Kubernetes control plane, and LLM APIs in real time. Own features end-to-end: from design through implementation, testing, and production rollout (most projects ship in 1 to 4 weeks). Debug novel problems: an agent giving a wrong answer, a cross-cloud permission edge case, a data freshness issue that only appears at scale. Build the quality harness: evals, telemetry, feedback loops, that let us ship agent improvements without regressions. Contribute to product direction and backlog. Shape what gets built next, not just how it's built. Participate in the team's on-call rotation. Tools We Use Daily Programming Languages: Go AI & Agents: MCP (servers and clients), agent gateways, LLM provider APIs, RAG, evaluation pipelines Cloud & Orchestration: Kubernetes, AWS, GCP, Azure Infrastructure as Code: Terraform Databases & Storage: PostgreSQL, Cloud Object Storage, ClickHouse Workflows & APIs: Temporal, GCP Pub/Sub, gRPC, REST Observability & Product Analytics: Prometheus, Grafana, Loki, Tempo, PostHog CI/CD & GitOps: GitLab/GitHub CI with ArgoCD and Kargo What's in it for you? Competitive salary (€6,500 to €9,000 gross, depending on the level of experience) Work on genuinely new problems: production MCP platforms and AI assistants for Kubernetes and cloud infrastructure are not solved domains. You'll be defining them, not following a playbook. Equity options. Real users, fast: your work ships to hundreds of organizations in weeks, not quarters. Enjoy a flexible, remote-first global environment. Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology. Spend 10% of your work time on personal projects or self-improvement. Learning budget for professional and personal development, including access to international conferences and courses. Annual hackathon to spark new ideas and strengthen team bonds. Team-building budget and company events to connect with your colleagues. Equipment budget to ensure you have everything you need. Extra days off to help maintain a healthy work-life balance. Hiring process Screening call with Recruiter Hiring Manager interview Technical interview (system design) Live coding Culture Check interview with an executive As part of our standard hiring process, a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr. Please note that Cast AI does not provide any form of visa sponsorship/work permit. #LI-Remote

Location: Estonia; Greece; Latvia; Lithuania; Poland; Slovakia; Ukraine What you'll be solving A platform engineer opens their AI client of choice, connects it to CAST AI, and types: "Why did our spend jump 40% in eu-west last week?" Thirty seconds later they have an answer, pulled from live cluster state and cost data, with links back to the evidence. No dashboards. No YAML archaeology. Just a question and a correct, permission-checked answer. Your job is to make that interaction boring. Reliably, securely, at production scale. Behind it sits the hard part: an AI assistant that reasons over thousands of production Kubernetes clusters, a platform that safely exposes company infrastructure to external AI clients, and quality pipelines that tell us when the agent is wrong before a customer does. Get it right, and operators stop clicking through consoles entirely. Get it wrong once, and an agent gives a confidently wrong answer to someone managing production. CAST AI already runs Kubernetes infrastructure autonomously. Our automation makes thousands of cost-and-reliability decisions a day. Cast Pilot is the team building the intelligence layer on top of that: AI assistants for Kubernetes and the cloud itself . Our assistant already answers thousands of questions a month from hundreds of organizations. Now we're opening the platform up: a public, permission-aware MCP server so customers can plug CAST AI straight into their own AI clients and agents, deeper connectivity across all three major clouds (AWS, GCP, Azure), and a continuous push to make our agents smarter, better grounded, and more capable. This is greenfield AI platform work on top of battle-tested infrastructure. Most features ship in 1 to 4 weeks. This is a location-specific opportunity. We are currently accepting applications from candidates residing in the following European countries: Bulgaria, Croatia, Estonia, Greece, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Cyprus, Malta, Finland, Sweden, Ireland, Moldova, North Macedonia, Montenegro, Slovenia, and Ukraine. Requirements Strong software engineering fundamentals: you design clean abstractions, write maintainable code, and can justify your architecture choices, not just make something work. You're a generalist who is as comfortable debugging a distributed system as designing an auth flow or tuning an agent's behavior. Production experience with Go is strongly preferred; candidates without Go should demonstrate strong systems programming skills in a comparable language. Experience building or operating large-scale SaaS platforms in production: multi-tenant systems, high volumes, and the failure modes that only show up at scale. Solid understanding of Kubernetes. Our entire platform runs on it, and the assistants we build answer questions about it. You should be at home with autoscaling, scheduling, and networking concepts. You've personally driven a complex project end-to-end. Hands-on experience with AI coding agents and agentic development workflows. This is how we build, not just what we build. You've used observability tooling in production. CI/CD and DevOps practices experience. Strong English skills, both verbal and written. Startup mindset: adaptable, proactive, and comfortable with ambiguity. What will make you stand out You've built agentic systems that shipped : MCP servers or clients, agent gateways, tool-use orchestration, RAG pipelines, evaluation frameworks, and you can talk about what broke in production and how you found out. This is the single biggest differentiator for our team. Deep hands-on experience with one or more of AWS, GCP, or Azure, with real understanding of IAM, compute, networking, and their APIs, not just console-level usage. Experience with LLM application quality: evaluations, prompt engineering at scale, latency and cost optimization of agent loops. Knowledge of OAuth 2.0 / OIDC and multi-tenant authorization design. Deep knowledge of EKS, GKE, or AKS internals. Kubernetes or cloud-native OSS contributions. Responsibilities Design and build the systems behind our AI assistant: agent flows, context retrieval, and the data connections that let it reason about live Kubernetes infrastructure. Build and evolve our public, permission-aware MCP server : curated tools, identity, audit, and strict safety gates, so customers can use CAST AI from their own AI clients. Develop and maintain cloud connectivity across AWS, GCP, and Azure, and the data foundations our agents build on. Write production Go services that interact with cloud provider APIs, the Kubernetes control plane, and LLM APIs in real time. Own features end-to-end: from design through implementation, testing, and production rollout (most projects ship in 1 to 4 weeks). Debug novel problems: an agent giving a wrong answer, a cross-cloud permission edge case, a data freshness issue that only appears at scale. Build the quality harness: evals, telemetry, feedback loops, that let us ship agent improvements without regressions. Contribute to product direction and backlog. Shape what gets built next, not just how it's built. Participate in the team's on-call rotation. Tools We Use Daily Programming Languages: Go AI & Agents: MCP (servers and clients), agent gateways, LLM provider APIs, RAG, evaluation pipelines Cloud & Orchestration: Kubernetes, AWS, GCP, Azure Infrastructure as Code: Terraform Databases & Storage: PostgreSQL, Cloud Object Storage, ClickHouse Workflows & APIs: Temporal, GCP Pub/Sub, gRPC, REST Observability & Product Analytics: Prometheus, Grafana, Loki, Tempo, PostHog CI/CD & GitOps: GitLab/GitHub CI with ArgoCD and Kargo What's in it for you? Competitive salary (€6,500 to €9,000 gross, depending on the level of experience) Work on genuinely new problems: production MCP platforms and AI assistants for Kubernetes and cloud infrastructure are not solved domains. You'll be defining them, not following a playbook. Equity options. Real users, fast: your work ships to hundreds of organizations in weeks, not quarters. Enjoy a flexible, remote-first global environment. Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology. Spend 10% of your work time on personal projects or self-improvement. Learning budget for professional and personal development, including access to international conferences and courses. Annual hackathon to spark new ideas and strengthen team bonds. Team-building budget and company events to connect with your colleagues. Equipment budget to ensure you have everything you need. Extra days off to help maintain a healthy work-life balance. Hiring process Screening call with Recruiter Hiring Manager interview Technical interview (system design) Live coding Culture Check interview with an executive As part of our standard hiring process, a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr. Please note that Cast AI does not provide any form of visa sponsorship/work permit. #LI-Remote

Location: San Francisco; New York City In 2026, we launched Computer, the defining product for the new era of agentic AI. We’ve scaled beyond the millions of people using Perplexity every day for research, shopping, investing, and curiosity into a new paradigm of using AI to transform knowledge into action. Thousands of attorneys, Am Law firms, and corporate legal teams already rely on Perplexity every week—and Legal is one of our highest-conviction enterprise verticals. Following the playbook that scaled Perplexity Finance, we are looking for an entrepreneurial Product Manager to build and scale our Legal vertical from the ground up. Product Managers at Perplexity work closely with design, engineering, research, and go-to-market teams to turn frontier AI capabilities into indispensable daily workflows. Whether you have a couple of years of product experience at a legal AI or B2B software company, or you are an early-career builder or operator with high agency and a steep trajectory, this role offers rare end-to-end ownership of a flagship vertical. In your application, please highlight a product, workflow, or agent system you’ve built—or a specific legal problem you believe AI is uniquely positioned to solve. THE ROLE Legal work sits at the exact intersection where Perplexity shines: high-stakes research, multi-document synthesis, verifiable citations, and multi-step execution across specialized systems. Winning in Legal requires clearing an uncompromising bar for accuracy, source authority, document fidelity, and enterprise governance—without sacrificing the speed and simplicity that make Perplexity magical. Sitting within our AI Capabilities & Verticals PM team, you will be the dedicated product owner for Perplexity’s Legal vertical. Rather than building an isolated point solution, you will shape how core Perplexity surfaces—Computer, Search, Teammates, Projects, Plugins, Skills, and Artifacts—come together into a cohesive, trusted experience for litigators, transactional counsel, and in-house legal teams. You will partner across Engineering, Design, AI Research, Partnerships, Sales, and Product Marketing to close product and data gaps, co-design with leading law firms and legal departments, and scale Legal into one of Perplexity’s flagship enterprise businesses. WHAT YOU’LL DO - Own the Legal vertical roadmap end-to-end: Define and execute product strategy across litigation research, M&A and transactional diligence, contract review and drafting, and in-house legal workflows—translating attorney pain points into modular capabilities that benefit the entire platform. - Ship core legal primitives and entrypoints: Partner with Engineering and Design to build the product surfaces high-stakes legal work demands—including structured multi-document review tables for diligence and discovery, passage-level inline citations with side-by-side source verification across PDFs/DOCX/spreadsheets, precision redlining and document comparison, and seamless workflows inside Microsoft Word, Outlook/email, and Slack. - Expand the legal data and connector ecosystem: Work closely with Business Development/Partnerships and Engineering to prioritize, integrate, and launch authoritative legal research sources (case law, citators, dockets, secondary sources) and system-of-record connectors across DMS, VDRs, CLM, e-discovery, and practice management (e.g., LexisNexis, Westlaw, iManage, NetDocuments, Datasite, Intralinks, Ironclad, Clio). - Build Legal Skills, Plugins, Teammates, and tailored onboarding: Design out-of-the-box legal workflows, domain-specific Skills, and tailored onboarding flows that ingest a lawyer’s or firm’s clause playbooks, precedent templates, and drafting conventions for immediate time-to-value. - Set the bar for accuracy, evaluations, and enterprise trust: Partner with AI Research and Engineering to build realistic, workflow-level legal benchmarks and evaluation harnesses (measuring citation fidelity, retrieval recall, tabular extraction, and redline quality), alongside enterprise controls for permissions, matter-level governance, and data handling. - Co-design with customers and accelerate vertical GTM: Build design partnerships with leading law firms and corporate legal teams, join strategic customer calls to turn live blockers into shipped product, and partner with Sales, Applied AI, and Product Marketing to craft category-defining demos, case studies, and self-serve and enterprise growth loops. QUALIFICATIONS - 1–4+ years of experience in product management, founding/early-stage product building, forward-deployed product/solutions, or a high-intensity analytical/operating role (such as startup operations, strategy consulting, or investment banking) paired with hands-on product shipping. We index heavily on slope, curiosity, and execution speed rather than years on a resume. - No JD or formal legal degree required—though genuine curiosity about how legal professionals research, analyze risk, negotiate, and deliver work is essential. - AI-native builder: You actively build with LLMs and agents. You are comfortable writing and tuning prompts and Skills, prototyping workflows end-to-end, reasoning about tool calls and context budgets, and designing evaluations and human-in-the-loop safeguards for non-deterministic systems. - Analytical and data-fluent: Comfortable writing SQL, pulling your own cohorts, instrumenting failure modes, running guarded experiments, and pairing warehouse metrics with qualitative user research to focus on what drives retention and repeat high-value usage. - Crisp communicator and high-velocity executor: Strong written and verbal communication; comfortable moving directly from a partner call with an Am Law firm into writing a tight spec with engineers and shipping iterations the same week. - High-ownership operator: Thrives in a small, agile, low-ego team where processes are still being defined and you own the full stack of the outcome—from multi-quarter vertical strategy down to dogfooding edge cases in redlined Word documents. NICE TO HAVE - Experience building or operating at a legal AI, legal tech, e-discovery, CLM, or vertical enterprise AI company (or working directly with law firms and corporate legal departments). - Familiarity with real-world legal workflows and tooling—such as litigation cite-checking (Shepard’s/KeyCite), M&A virtual data rooms, contract redlining playbooks, DMS/CLM integrations, or Microsoft Office add-ins. - Technical foundation (CS, engineering, data science, or dual technical/business training) with comfort reading API documentation, MCP/connector schemas, and system architectures.

Location: San Francisco; New York City In 2026, we launched Computer, the defining product for the new era of agentic AI. We’ve scaled beyond the millions of people using Perplexity every day for research, shopping, investing, and curiosity into a new paradigm of using AI to transform knowledge into action. Thousands of attorneys, Am Law firms, and corporate legal teams already rely on Perplexity every week—and Legal is one of our highest-conviction enterprise verticals. Following the playbook that scaled Perplexity Finance, we are looking for an entrepreneurial Product Manager to build and scale our Legal vertical from the ground up. Product Managers at Perplexity work closely with design, engineering, research, and go-to-market teams to turn frontier AI capabilities into indispensable daily workflows. Whether you have a couple of years of product experience at a legal AI or B2B software company, or you are an early-career builder or operator with high agency and a steep trajectory, this role offers rare end-to-end ownership of a flagship vertical. In your application, please highlight a product, workflow, or agent system you’ve built—or a specific legal problem you believe AI is uniquely positioned to solve. THE ROLE Legal work sits at the exact intersection where Perplexity shines: high-stakes research, multi-document synthesis, verifiable citations, and multi-step execution across specialized systems. Winning in Legal requires clearing an uncompromising bar for accuracy, source authority, document fidelity, and enterprise governance—without sacrificing the speed and simplicity that make Perplexity magical. Sitting within our AI Capabilities & Verticals PM team, you will be the dedicated product owner for Perplexity’s Legal vertical. Rather than building an isolated point solution, you will shape how core Perplexity surfaces—Computer, Search, Teammates, Projects, Plugins, Skills, and Artifacts—come together into a cohesive, trusted experience for litigators, transactional counsel, and in-house legal teams. You will partner across Engineering, Design, AI Research, Partnerships, Sales, and Product Marketing to close product and data gaps, co-design with leading law firms and legal departments, and scale Legal into one of Perplexity’s flagship enterprise businesses. WHAT YOU’LL DO - Own the Legal vertical roadmap end-to-end: Define and execute product strategy across litigation research, M&A and transactional diligence, contract review and drafting, and in-house legal workflows—translating attorney pain points into modular capabilities that benefit the entire platform. - Ship core legal primitives and entrypoints: Partner with Engineering and Design to build the product surfaces high-stakes legal work demands—including structured multi-document review tables for diligence and discovery, passage-level inline citations with side-by-side source verification across PDFs/DOCX/spreadsheets, precision redlining and document comparison, and seamless workflows inside Microsoft Word, Outlook/email, and Slack. - Expand the legal data and connector ecosystem: Work closely with Business Development/Partnerships and Engineering to prioritize, integrate, and launch authoritative legal research sources (case law, citators, dockets, secondary sources) and system-of-record connectors across DMS, VDRs, CLM, e-discovery, and practice management (e.g., LexisNexis, Westlaw, iManage, NetDocuments, Datasite, Intralinks, Ironclad, Clio). - Build Legal Skills, Plugins, Teammates, and tailored onboarding: Design out-of-the-box legal workflows, domain-specific Skills, and tailored onboarding flows that ingest a lawyer’s or firm’s clause playbooks, precedent templates, and drafting conventions for immediate time-to-value. - Set the bar for accuracy, evaluations, and enterprise trust: Partner with AI Research and Engineering to build realistic, workflow-level legal benchmarks and evaluation harnesses (measuring citation fidelity, retrieval recall, tabular extraction, and redline quality), alongside enterprise controls for permissions, matter-level governance, and data handling. - Co-design with customers and accelerate vertical GTM: Build design partnerships with leading law firms and corporate legal teams, join strategic customer calls to turn live blockers into shipped product, and partner with Sales, Applied AI, and Product Marketing to craft category-defining demos, case studies, and self-serve and enterprise growth loops. QUALIFICATIONS - 1–4+ years of experience in product management, founding/early-stage product building, forward-deployed product/solutions, or a high-intensity analytical/operating role (such as startup operations, strategy consulting, or investment banking) paired with hands-on product shipping. We index heavily on slope, curiosity, and execution speed rather than years on a resume. - No JD or formal legal degree required—though genuine curiosity about how legal professionals research, analyze risk, negotiate, and deliver work is essential. - AI-native builder: You actively build with LLMs and agents. You are comfortable writing and tuning prompts and Skills, prototyping workflows end-to-end, reasoning about tool calls and context budgets, and designing evaluations and human-in-the-loop safeguards for non-deterministic systems. - Analytical and data-fluent: Comfortable writing SQL, pulling your own cohorts, instrumenting failure modes, running guarded experiments, and pairing warehouse metrics with qualitative user research to focus on what drives retention and repeat high-value usage. - Crisp communicator and high-velocity executor: Strong written and verbal communication; comfortable moving directly from a partner call with an Am Law firm into writing a tight spec with engineers and shipping iterations the same week. - High-ownership operator: Thrives in a small, agile, low-ego team where processes are still being defined and you own the full stack of the outcome—from multi-quarter vertical strategy down to dogfooding edge cases in redlined Word documents. NICE TO HAVE - Experience building or operating at a legal AI, legal tech, e-discovery, CLM, or vertical enterprise AI company (or working directly with law firms and corporate legal departments). - Familiarity with real-world legal workflows and tooling—such as litigation cite-checking (Shepard’s/KeyCite), M&A virtual data rooms, contract redlining playbooks, DMS/CLM integrations, or Microsoft Office add-ins. - Technical foundation (CS, engineering, data science, or dual technical/business training) with comfort reading API documentation, MCP/connector schemas, and system architectures.

Location: Remote - US Who we are At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences. Our dedication to remote-first work , and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands. . Hiring and how we work We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions! Also, while we are a remote-first company, you may be asked to report in person on an ad-hoc basis for team gatherings, functional off-sites or customer meetings. . See yourself at Twilio Join the team as Twilio’s next Architect on our Data Substrate team About the job Twilio runs on data, and the platform underneath it is entering a major shift. Open table formats, the convergence of lakes and warehouses, tightening privacy regulation, and AI workloads are all changing what a data platform has to do. We’re hiring an Architect to set our direction through that shift and to make sure the systems we build over the next 3-5 years are the right ones. You’ll own the technical strategy for our data platform, spanning storage, lake and lakehouse architecture, catalog and governance, and privacy-by-design. You’ll work across org boundaries, setting standards that dozens of teams build on and raising the technical bar for the engineers around you. Responsibilities In this role, you’ll: Own the architecture and multi-year technical strategy for the data platform, including the lake/lakehouse, ClickHouse, Elasticsearch, and governance, and keep them coherent as one platform rather than separate systems. Define where each engine fits (for example, ClickHouse versus open table formats on object storage) and the migration path between them. Make and document the major design decisions (ADRs, RFCs) on storage and open table formats, catalog strategy, compute engines, tenancy, data placement, and build-versus-adopt tradeoffs, with cost and performance at petabyte scale as explicit design constraints. Set the reference architectures for how our core storage and query engines (ClickHouse, Elasticsearch, and lake engines) are deployed, tuned, scaled and operated as shared platforms, including capacity, cost, tenant isolation, and upgrade strategy. Define the reliability model for the platform: availability targets, failure domains, disaster recovery, observability, and incident response patterns that teams can adopt. Build privacy and compliance into the architecture, not onto it. Design deletion and right-to-erasure, retention, data residency, and PII classification so they work across the platform’s storage layers, backups, and derived datasets, including data that arrives from upstream streaming systems. Drive data governance: classification, catalog and metadata, lineage, access control integrated with our authentication and authorization systems, data contracts, quality and integrity standards, and a catalog teams actually use. Review designs and technical direction across the org, and act as the escalation point on hard distributed-systems and performance problems. Mentor principal and senior engineers, and grow architectural judgment across the org, not only within one squad. Partner with product, security, infrastructure and consuming teams to turn business needs into platform roadmaps, and say no or re-sequence when the tradeoffs require it. Track emerging data technologies (such as streaming-first architectures, federated query, and AI-ready data layers) and bring forward the ones worth adopting, with evidence from prototypes or benchmarks. Qualifications Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table! Required: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience. 15+ years of experience in software development or a related field, with at least 8 years in an architecture or senior technical leadership role. Proven track record of architecting and delivering large-scale data platforms and setting their technical strategy, on cloud infrastructure such as AWS, deployed with Kubernetes, Terraform and Helm. Deep expertise in storage and compute for analytical data: columnar and open table formats, lake and lakehouse architecture, partitioning, indexing, query planning, and how the choices affect cost and performance at petabyte scale. Breadth across data storage and retrieval technologies, with hands-on depth in at least two of: analytical/OLAP engines (e.g., ClickHouse), search engines (e.g., ElasticSearch/OpenSearch), and lake or distributed processing engines (e.g., Spark, Trino, Flink). You can reason about when to use each, how they interoperate, and how to migrate between them. Working knowledge of streaming systems (e.g., Kafka) and how they interact with downstream storage. Practical experience designing data governance at scale: data classification, catalog and metadata management, lineage, and access control integrated with authentication and authorization systems. Practical experience implementing privacy and compliance requirements (deletion, retention, residency) across a large, heterogeneous data estate. Proficiency in one or more of Python, Java, and Go. Track record of writing and driving architecture decisions across multiple teams, and of changing the direction of an organization’s technical roadmap through influence rather than authority. Experience elevating engineering standards and mentoring senior engineers across teams. Demonstrated commitment to operational excellence: architecting for high availability, observability and incident response in distributed systems, and being credible when a platform is failing in production. Strong written and verbal communication, including making a complex tradeoff clear to engineers and to senior leadership. Desired: Experience operating one of these engines (e.g., ClickHouse, ElasticSearch) at scale, including replication, sharding, ingestion behavior, and multi-tenant isolation. Experience with catalog and metadata systems (e.g., Unity Catalog, Glue, Polaris, DataHub) and open table format catalog strategy. Experience with a platform migration across domains or ownership models, such as moving from central to domain-owned data. A track record of measurable cost optimization on large data platforms. Networking and network security knowledge. Location This role will be remote, and based in the United States. Travel We prioritize connection and opportunities to build relationships with our customers and each other. For this role, you may be required to travel occasionally to participate in project or team in-person meetings. What We Offer Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location Compensation *Please note this role is open to candidates outside of California, Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, New Jersey, New York, Vermont, Washington D.C., and Washington State. The information below is provided for candidates hired in those locations only. The estimated pay ranges for this role are as follows: Based in Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, Vermont or Washington D.C. : $207,200 - $233,100. Based in New York, New Jersey, Washington State, or California (outside of the San Francisco Bay area): $219,360 - $246,780. Based in the San Francisco Bay area, California: $243,680 - $274,140. This role may be eligible to participate in Twilio’s equity plan and corporate bonus plan. All roles are generally eligible for the following benefits: health care insurance, 401(k) retirement account, paid sick time, paid personal time off, paid parental leave. The successful candidate’s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location. Application deadline information Applications for this role are intended to be accepted until 1/4/2027 but may change based on business needs. Twilio thinks big. Do you? We like to solve problems, take initiative, pitch in when needed, and are always up for trying new things. That's why we seek out colleagues who embody our values — something we call Twilio Magic . Additionally, we empower employees to build positive change in their communities by supporting their volunteering and donation efforts. So, if you're ready to unleash your full potential, do your best work, and be the best version of yourself, apply now! If this role isn't what you're looking for, please consider other open positions. . Stay alert to recruitment fraud We care about your safety. Scammers sometimes impersonate Twilio recruiters through fake job postings, emails, websites, or messages. Please ensure you are engaging with an official @ twilio.com email address. We will never ask for payment, gift cards, cryptocurrency, or banking information during the recruiting process. We do not make job offers without a formal interview process or conduct interviews exclusively through text-based messaging apps. . Twilio is proud to be an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Additionally, Twilio participates in the E-Verify program in certain locations, as required by law.

Location: San Francisco WHY HARVEY At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. ROLE OVERVIEW Harvey is redefining what’s possible in legal work by combining cutting-edge AI with intuitive product experiences. As we scale rapidly and take on increasingly complex use cases, we’re expanding our product engineering team to accelerate our ability to ship fast, delight users, and build infrastructure that scales with us. Agents at Harvey let lawyers turn their expertise into reusable, automated work: custom agents and workflows that draft, review and analyze across a firm’s documents. The Agents team owns Agent Builder, the Agents experience, workflows and the foundations underneath them: orchestration, durable execution, permissions and reliability. Other Harvey products build on this platform as well. As Engineering Manager, you’ll lead a large, senior team of full-stack and backend engineers through the shift from single-turn assistants to long-running, multi-agent systems that firms trust with their most sensitive work. This role is equal parts product judgment and systems depth. We move with urgency, bias toward simplicity, and expect our leaders to be hands-on when needed. If you’re energized by ownership, decisive execution, and solving real user problems, we'd love to hear from you. WHY NOW - Agents are how firms put Harvey to work: lawyers are turning their expertise into reusable agents and workflows that run across their documents and matters. - The work is moving from single-turn assistance to long-running, scheduled and multi-agent work. That demands durable execution, sandboxed tools and recovery from failure at scale. - Agents now reach deep into a firm’s most sensitive data, so permissions, tenant isolation and governance have to hold everywhere an agent can act. - Other Harvey products are building on this platform, so its quality and speed set the pace for much of the company. - We need a leader who can raise the bar on reliability and evaluation while the team keeps shipping quickly. WHAT YOU’LL DO - Lead the Agents engineering team, a group of senior full-stack and backend engineers building Agent Builder, the Agents experience, workflows and the runtime underneath them. - Own reliability and quality for agent and workflow execution, including on-call health, incident follow-through, SLOs and evals as part of how the team ships. - Set technical direction for orchestration, durable execution and agent composition, and stay close enough to the code to make sound architecture calls and unblock hard problems. - Hold a high bar on security and customer data boundaries, so permissions, isolation and admin controls are designed in from the start rather than patched later. - Partner with Product, Design and Data Science on what agents should do for lawyers. Work with Agent Platform, Infrastructure and Security on the shared foundations. - Shape how the team builds with AI coding agents: review practices, verification and test infrastructure that keep quality high as output grows. - Hire, develop and retain strong engineers, grow tech leads, and build a team culture of ownership and candor. WHAT YOU HAVE - You have 3+ years managing engineering teams, including teams of 10 or more, and 5+ years as a backend or full-stack engineer before that. - You’ve shipped LLM-powered or agentic products in production and understand orchestration, tool use, evals, and latency and cost trade-offs from experience. - You’ve operated multi-tenant systems with strict security, permission or compliance requirements, and you treat a permissions bug as a trust issue. - You’re comfortable going deep on distributed systems: workflow engines such as Temporal, queues, sandboxing and long-running jobs. - You have strong product judgment and can weigh speed, quality and user impact in a domain where accuracy matters. - You lead by raising the bar on quality without slowing the team down. You know when to step in and when to let your tech leads lead. - Nice to have: experience with builder, low-code or automation tools for non-engineers, or with legal or other professional-services workflows. COMPENSATION RANGE $260,000 - $330,000 USD   DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES [HERE https://www.notion.so/harveyai/Harvey-Candidate-Privacy-Policies-319ac3fcdd7a803bb807d5094f249922].   #LI-ML1 Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

Location: United States How We Build Babylist is in the middle of a fundamental shift in how software gets made, and we are not tiptoeing into it. We are rebuilding our engineering culture around a simple belief: AI changes everything. How teams are structured, how decisions get made, how fast ideas become working software. Our engineers own problems end to end, working directly with product, design, and business partners with short feedback loops and real stakeholder access. We ship, learn, and iterate fast. When something is not working, we throw it out and start over — project failure and personal failure are not the same thing here. AI tools are as natural to our workflow as an IDE or version control. We are not exploring this, we are living it. Our engineers use AI to explore tradeoffs, pressure-test designs, and move from problem to solution in hours instead of days. They generate code with AI so they can stay focused on the decisions that actually require human judgment — not the routine ones. More velocity means more time for craft: better test coverage, stronger architecture, and deeper customer understanding. We hold ourselves to a higher quality bar because of AI, not in spite of it. We are building this playbook in real time, and we are looking for people who want to build it with us. If you have already changed how you work because of AI — or you are ready to — and you care more about shipping something great than following a prescribed process, we should talk. Our Tech Stack Ruby on Rails AWS Sidekiq MySQL Redis What the Role Is Babylist's Platform team is the foundation every engineering team builds on — and this role is at the center of keeping it reliable, fast, scalable, and secure. As a Staff SRE, you'll own the infrastructure and reliability practices that support 9 million+ users and the engineers who build for them. You'll bring strong software engineering skills and experience building security into production systems, turning that experience into code, automation, and secure defaults. You'll evolve our AWS infrastructure, CI systems, and developer tooling as Babylist grows across e-commerce, registry, health, media, and mobile. You'll share the team's core SRE responsibilities and bring particular depth in security engineering, leading security improvements alongside reliability, developer experience, and platform initiatives. Who You Are Strong software engineering skills — you've shipped and operated production-quality tools or services, with tests, code review, and maintainable interfaces Experience building security into production systems — you've personally designed, implemented, and operated controls for access, workload identity, secrets, or network isolation Deep hands-on Terraform expertise — you own IaC, not just contribute to it Proven AWS experience at scale — EKS, RDS, cloud networking, DNS, CDNs, load balancers — you know the gotchas Experienced operating Kubernetes in production — you've debugged the hard stuff, not just deployed the easy stuff Comfortable designing and improving CI/CD systems — CircleCI, GitHub Actions, or similar; you care about developer velocity, not just pipeline uptime Strong observability instincts — Datadog, Sentry, PagerDuty, Cronitor — you build alerting that's actionable, not noisy Experienced with on-call and incident management — you've run the post-mortems and actually changed things afterward Comfortable supporting developers across local, staging, and production — you're a resource, not a gatekeeper You naturally reach for AI in your work — at Babylist, every team uses AI daily. You're already using it to move faster and improve your output, and you stay curious about what's coming next. How You Will Make An Impact Infrastructure ownership — manage and evolve our AWS environment using Terraform, keeping EKS clusters, databases, and core services current, performant, and secure Software and automation — ship tested tools and services with runbooks and self-service workflows that other engineers can adopt and operate Secure infrastructure defaults — build versioned, tested Terraform modules for least-privilege access, secrets, and workload isolation, with automated checks for configuration drift CI/CD reliability — keep delivery fast and dependable across Engineering, integrating dependency and container scanning, secret detection, and short-lived deployment credentials Developer support — be the person engineers turn to when environments break; unblock them fast across local, staging, and production Monitoring & alerting standards — define service-level objectives (SLOs) and actionable alerting with engineering teams, using incident trends to prioritize reliability improvements Recovery readiness — validate backups, restore procedures, and failover paths through regular recovery tests Incident response — lead or support incident response, drive post-incident reviews, and close the loop so the same thing doesn't happen twice Platform strategy — shape our long-term infrastructure roadmap and lead cross-team initiatives from design through rollout, adoption, and ongoing operation, mentoring engineers along the way Why This Role Platform is the team every engineering team depends on — your work has outsized leverage across the entire product org, not just one area The infrastructure is solid and actively evolving — you'll shape how reliability and security are built into the platform as it grows This is a staff-level role with real cross-team visibility — you'll influence how Babylist engineers build and ship, not just keep the lights on You'll work on systems that support millions of families at a high-stakes life moment — the scale is real and the product context makes the reliability work matter About Compensation We use a market-based approach to compensation. The starting salary range for this role is: $226,673 to $271,991 + target 20% annual bonus and competitive equity Your starting salary will be based on your location, experience, and qualifications, with increases over time tied to performance, role growth, and internal pay equity. Who We Are Babylist is the leading platform for expecting and new families. More than 10 million people shop with Babylist every year, making it the go-to destination for seamless purchasing, guidance, and expert recommendations. As a modern, AI-forward tech company, Babylist has expanded from a universal registry into a full ecosystem — the Babylist Shop, Babylist Health, Babylist Money, NYC and LA showrooms, branded content, and more — generating $750M in revenue in 2025. Building the generational brand in baby, Babylist is reshaping the $235B kids and baby market and helping parents feel confident, connected, and cared for at every step. Our Ways of Working Babylist is remote-first with team members across the U.S. and Canada who move fast, think smart, and use AI as part of how they work every day — not as an experiment, as an expectation. We come together twice a year to build the relationships behind the work, and we hire people who are genuinely excited about what's possible and prove it through how they show up. Why You Will Love Working At Babylist Our Culture We work with focus and intention, then step away to recharge We believe in exceptional management, and we invest in the tools and the time to connect with colleagues We build products that positively impact millions of people's lives AI is part of how we work, not a side experiment. You'll have leading tools like Claude and ChatGPT from day one, with no waiting on access, so the busywork gets handled and your judgment goes where it counts Growth & Development Competitive pay and meaningful opportunities for career advancement We believe technology and data can solve hard problems We're committed to career progression and performance-based advancement Benefits Company-paid medical, dental, and vision insurance Retirement savings plan with company matching and flexible spending accounts Generous paid parental leave and PTO Winter Wonder Week: the whole company takes a paid week off at the end of the year, whether or not you celebrate anything, so everyone's out at once and comes back refreshed Remote work stipend to set up your office Perks for physical, mental, and emotional health, parenting, childcare, and financial planning Important Notices Recorded Interviews. Babylist uses an interview recording tool to record and transcribe interviews for evaluation purposes in accordance with applicable privacy laws. By participating in an interview, you consent to this recording and transcription. Interview Integrity. AI is part of how we work at Babylist. We expect you to use it too. Your application and interviews should still reflect you and your own thinking. We'll tell you when AI is encouraged. Misrepresentation at any stage may result in removal from consideration for this and future roles. How We Review Applications We use AI throughout our hiring process to help review, screen, and assess applications. These tools support our team's review; they do not replace it, and every hiring decision is made by a person. Connections at Babylist. If you have a family member or close personal relationship with a current Babylist employee, please let your recruiter know. This helps us keep our process fair and transparent for everyone. Protect Yourself from Scams. All official outreach comes from the Babylist Talent Team via @babylist.com email addresses only. We will never ask for payment or personal financial information. If you receive outreach via WhatsApp, Telegram, or a non-Babylist email, it's not us. Verify open roles at babylist.com/careers.

Location: United States Workplace: Remote BUILDING THE FUTURE OF OPEN FINANCE Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system. THE TEAM Founded in 2011, Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients. Kraken’s Core Infrastructure Engineering team builds and operates the shared data systems behind critical production services. Our estate spans on-premises and cloud infrastructure, with MariaDB at its centre and Kafka, Redis and Elasticsearch across the wider platform. We’re hiring a Principal Database Engineer to bring long-term experience and technical judgment to this estate. You’ll assess it, set the goals and direction, and work hands-on with the team to deliver measurable improvements. This is an individual contributor role with influence across teams and several quarters of work.   THE OPPORTUNITY - Review the estate against business needs and production evidence. Judge reliability, scale, cost and operational complexity, identifying what should be preserved and where investment or simplification would make a difference. - Define the target architecture and measurable goals. Agree a prioritised roadmap with engineering leads and dependent teams, explaining the trade-offs and sequencing work around delivery risks. - Execute that roadmap with the team through design, implementation and adoption. Stay personally involved in difficult migrations and scaling decisions, with representative benchmarks, data-integrity checks and credible cutover and rollback plans. Adapt the plan as evidence changes and verify the results in production before calling the work complete. - Investigate difficult MariaDB failures and performance limits through the engine, storage and application behaviour. Improve fleet reliability through useful observability, safer changes and tested backup, restore and disaster recovery procedures. Set recovery objectives with service owners and prove them through exercises. - Build and maintain production software for database provisioning, upgrades and routine maintenance. Make self-service workflows safe and auditable, incorporating access controls and change evidence with Security and Compliance. - Work with application teams on schemas, transaction boundaries, queries and data-store choices. Make the operational consequences clear and resolve dependencies that span teams. - Mentor engineers across the team through design reviews, pairing and incident analysis. Help them deepen their database expertise and take ownership of technical decisions. - Participate in on-call and incident response, leaving clear operational ownership and following through on lessons from production.   WHAT YOU BRING - 8+ years operating and evolving production database estates at scale. You have assessed inherited systems, set technical direction and delivered improvements with engineering teams, and can explain how those decisions held up over time. - Strong understanding of high availability, replication and distributed database failure modes. You can explain consistency and availability trade-offs and reason about transaction boundaries and reliable event delivery, including transactional outbox patterns. - Deep, recent hands-on MariaDB expertise, including InnoDB, MVCC and transaction isolation, locking, query optimisation, binary logs and MariaDB GTID replication. You can explain the mechanisms and diagnostic evidence behind your decisions. - Personal ownership of MariaDB incident diagnosis, performance tuning and tested restore or point-in-time recovery. You can explain what you did, how you established data integrity and what remained uncertain. - Strong software engineering skills in Python, Go, Rust or a comparable language. You have personally built and maintained production software or automation for database workflows such as provisioning, failover, online schema changes and self-service operations, using version control, code review and delivery pipelines, with tested failure handling. - Strong low-level Linux, Kernel, storage and networking fundamentals, with the ability to investigate problems beyond the database process. - Clear written technical judgment and demonstrated delivery across teams without reporting-line authority. You help stakeholders make sound database design and lifecycle decisions, and develop experienced engineers through shared delivery.   NICE TO HAVES - Experience operating databases in containerised, hybrid on-premises/cloud or multi-region environments. Familiarity with Kubernetes, infrastructure as code or GitOps, including their operational trade-offs. - Experience with database proxies or load-balancing layers (MaxScale, HAProxy, ProxySQL, or similar). - Experience with PostgreSQL, Vitess, TiDB, ScyllaDB, ClickHouse or internal database platforms; operational knowledge of Kafka, Redis/Valkey or Elasticsearch/OpenSearch. - Experience in regulated environments or contributions to database engines, operators and other infrastructure software. Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis. Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution. We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. OUR COMMITMENT Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto. We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision. As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws. Stay connected Follow us on X https://twitter.com/krakenfx Learn on the Kraken Blog https://blog.kraken.com/#:~:text=Enter%20your%20email%20address Connect on LinkedIn https://www.linkedin.com/company/kraken-exchange/ Candidate Privacy Notice https://www.kraken.com/legal/candidate-privacy-notice

Location: San Francisco; New York Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. PRODUCT AT BASETEN Baseten is building a new cloud for AI. Our ambition is to make inference, training, and agent execution part of one coherent platform, and to shape how the next generation of AI products gets built. Product decisions here reach from the economics of GPU infrastructure to the abstractions developers build on every day. We’re hiring builders and tastemakers with the ambition to help create that future. You should bring a strong point of view about what should exist, the taste to make complex technology feel simple, and the technical judgment to build it alongside engineers, researchers, and designers. You’ll work directly with customers and forward deployed teams, turn emerging capabilities into new possibilities for developers, and carry an idea from early conviction through to production and adoption. THE ROLE Help make training and fine-tuning AI models dramatically easier. Training a model is hard enough. Developers shouldn't have to spend their time wrestling with infrastructure, waiting for GPUs, or figuring out why a job failed. We're building a training platform that lets AI teams focus on improving their models instead of managing the systems underneath them. As Product Manager for Training Platform, you'll own the developer experience for running training jobs on Baseten, from environment setup and job submission to scheduling, debugging, checkpointing, and recovery. You'll work alongside engineers and researchers solving some of the hardest problems in distributed training, helping turn that complexity into a product developers can depend on. RESPONSIBILITIES - Own the product experience for training jobs, from setup and submission through execution, monitoring, and recovery - Make distributed training easier to use, with intuitive workflows for scheduling, GPU availability, logs, checkpoints, and debugging - Work closely with research and infrastructure teams to support different training workloads, including supervised fine-tuning and reinforcement learning - Help developers recover from failures, reproduce experiments, and spend less time waiting on infrastructure - Connect training with the rest of Baseten's platform, including Loops, model evaluation, and inference deployment - Work directly with customers to understand how they train and adapt models, then turn those insights into product improvements REQUIREMENTS - Experience building and shipping AI/ML products or developer platforms - A technical background in software engineering, ML engineering, research, or equivalent hands-on work - Direct experience working with teams that train, fine-tune, or adapt machine learning models - Strong understanding of distributed training concepts, including GPU memory, scheduling, data access, checkpointing, and fault recovery - Familiarity with the infrastructure needs of supervised fine-tuning and reinforcement learning - Strong product instincts for developer workflows and the ability to simplify technically complex systems - Experience partnering with researchers and engineers to take new capabilities from concept to production NICE TO HAVE - Hands-on experience running distributed training, building ML developer tools, or working with trainer and sampler systems for reinforcement learning. WHAT SUCCESS LOOKS LIKE AI teams can run more experiments, recover from failures faster, and spend more of their time improving models instead of managing compute. Baseten becomes a natural place to train, fine-tune, and deploy custom AI models. BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: Intellias Meet your recruiter Dariia Ulianova dariia.ulianova@intellias.com https://www.linkedin.com... Vacancy details Business Analysis Business Analyst Senior Business Analyst Bulgaria, Croatia, Poland, Portugal, Spain, Ukraine, United Kingdom Remote APPLY NOW REFER A FRIEND We are hiring a Business Analyst to join an Intellias delivery team on a large-scale enterprise data platform migration programme for a financial services client. You will bridge the client’s domain owners and stewards on one side and the delivery engineers on the other, and you will own the backlog in Azure DevOps. What project we have for you Our client is an independent, active global asset manager with over R3 trillion in assets under management. They are executing a firm-wide data strategy to govern, manage and engineer data as a product across more than 70 business-owned sub-domains. As part of this, they are migrating to Databricks as the foundational layer of their Enterprise Data Platform, adopting a lakehouse architecture built on open formats, declarative pipelines and Unity Catalog. What you will do Data Modelling Run data modelling workshops with business SMEs, domain owners, analysts. Design conceptual and logical data models across multiple business domains, working from business definitions as well as from existing data structures in mastering systems. Model business complexity appropriately: e.g. class hierarchies, inheritance, controlled vocabularies, reusable patterns, shared data domains, business rules, and define where cross-domain references exist. Present models back to stakeholders for review, information-sharing, and agreement Ensure every model element traces back to a business term from data governance, and that the trace survives all the way to the delivered column. Help to resolve conflicts or missing inputs/outputs where they exist Review other domain data models from the modelling team. We envisage a small team of modellers who contribute to the federated data model as a whole. Standards and federation Contribute to and enforce the modelling standards that make federated delivery safe: naming conventions, data type standards, model layering rules, and the conventions that prevent domains colliding as the model grows Define reusable enterprise-level structures — shared types, reusable/common patterns, balancing core versus domain-local Delivery and automation Work in Git and GitHub as your primary environment: branches, pull requests, code review, releases Review model changes raised by others — including, ultimately, any changes drafted by AI agents — and apply the judgement that automated checks cannot Version models, assess the impact of breaking changes on downstream consumers in order for migration planning Contribute to the automated checks that enforce standards in CI, in collaboration with engineering Have input into the logical-to-physical mapping — deciding and documenting where a normalised structure can/should be denormalised for query performance or analytics (e.g. a data product), an define agreed and named patterns for these transformations rather than ad-hoc judgement so they can be automated. What you need for this Key Responsibilities Substantial data modelling experience, with a track record of conceptual, logical modelling that powered physical models that went into production, consumed, iterated upon & versioned accordingly. You must be competent in the principles of abstraction, inheritance, normalisation. Experience with dimensional/denormalization techniques. Demonstrable domain knowledge in asset/investment management, or a closely related financial services area — sufficient to hold a credible conversation with a SME, e.g. a portfolio manager, a fund accountant or a risk analyst about what their data actually means. We are building out domain by domain. You would be expected to develop working depth across more than one area. We expect some in depth asset management knowledge in at least 3 of these areas: Instrument/Security reference, Index & Benchmarks, Party, Counterparty/ Client, Portfolio, Holdings & Valuations, Execution, Trade Life cycle, Performance & Attribution, ESG/sustainability, Fund Accounting, Sales & Marketing Working fluency with Git and GitHub: branching, pull requests, resolving conflicts, reviewing others’ changes. You do not need to be a software engineer, but you must be comfortable that your model lives in a repository and moves through code review. Comfort authoring in YAML, and working with JSON data – plus the willingness to learn a schema language – prior exposure is welcome but not expected. Experience establishing or working to modelling standards — naming conventions, data dictionaries, glossaries, and the ability to add/enhance those standards as part of the platform maturation and greater automation. Soft Skills: The ability to run a workshop with business stakeholders and leave with clarity, and not a list of open questions. Precision with language. Dealing with ambiguity. Much of this role is writing definitions that all stakeholders can agree on. Nice to have: Databricks, Delta Lake or a comparable Lakehouse platform Data contracts, particularly ODCS, or equivalent interface-versioning practice CI/CD concepts Experience of developing/using agentic workflows for delivering model artefacts Experience of a federated or data mesh operating model, and its failure modes Traditional modelling tools such as Erwin, ER/Studio is useful, for reference, however our way of working will be different. What it’s like to work at Intellias At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth. We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law. We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success. Skills Fintech

Location: Hybrid About Us At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company. At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in. Location: Austin, San Francisco or New York About the role Cloudflare is hiring a Data Center Architect to define and deliver the physical infrastructure behind high-density compute and GPU deployments across our global network. You'll own 3 connected domains: the liquid cooling chain, the low-voltage connectivity layer, and the MV/LV electrical architecture that powers both. This is a senior individual-contributor role spanning architecture, detailed design, technical qualification, design governance, commissioning, and operational readiness. You're Cloudflare's owner-side technical lead in these domains: the person who connects what our hardware needs with what colocation providers, equipment manufacturers, and delivery partners can actually build. Scope runs from a single rack in commercial colocation to multi-megawatt compute deployments. You'll design power, cooling, and cabling as one system so they don't fight each other at the rack, in the white space, or during maintenance. If your background is only HVAC design, only cold-plate research, or only utility-scale generation, this role will be wider than you expect. We need someone who can hold the electrical, cooling, and cabling layers together. About the team We work with engineering, capacity planning, network strategy, supply chain, and operations to grow Cloudflare's data center and PoP footprint. With colocation providers, hardware suppliers, and delivery partners worldwide, we turn infrastructure requirements into deployments that come online faster, cost less, and work the first time. What you'll do Architecture and reference designs Own the physical-infrastructure architecture. Build reference designs for power, liquid cooling, and connectivity for AI and high-density compute, including how they interface at rack, row, and site level. Maintain the standards, templates, and libraries that deployment, operations, and partner teams build from. Translate hardware and capacity needs into engineering requirements. Turn heat loads, electrical loads, port counts, network topologies, and growth plans into power, cooling, and connectivity requirements and into site and rack qualification criteria. Qualify sites and facility interfaces. Assess provider power and cooling availability, utility and backup capacity, water supply and return conditions, hydraulic capacity, upstream heat rejection, expansion headroom, maintenance constraints, and contractual boundaries. Give go/no-go recommendations with the risks written down. Electrical power architecture (MV/LV) Lead MV and LV electrical architecture: single-line diagrams, power distribution, switchgear and UPS topology, busway and PDU design, grounding and bonding. Design physical power infrastructure, AC and DC, including power conversion, backup generation, energy storage, and distribution, with attention to fault levels, selectivity, and maintainability. Validate designs with modeling: load-flow, short-circuit, arc-flash, and selectivity studies, checked against measured performance where possible. Define digital power requirements for monitoring, metering, protection coordination, and control. Work with controls and operations teams on alarm thresholds, trend retention, remote monitoring, and BMS/SCADA integration. Fold emerging standards (NEC, NFPA, UL, OCP power and rack specs) into forward-looking electrical designs. Liquid cooling Own the liquid-cooling architecture and roadmap. Develop repeatable direct-to-chip designs and evaluate liquid-to-liquid, liquid-to-air, rear-door, and other approaches against deployment needs. Design and validate the hydraulic system. Flow and pressure-drop calculations, pipe sizing, pump selection, balancing, and control requirements. Validate at partial load, during expansion and maintenance, and in failure scenarios, not just at nameplate. Specify equipment and rack integration. Qualify CDUs, heat exchangers, pumps, manifolds, hoses, quick-disconnects, valves, and instrumentation. Coordinate rack access, piping routes, service clearances, and installation sequencing with the electrical, cabling, hardware, and structural disciplines. Own coolant integrity and serviceability. Set manufacturer-aligned requirements for fluid quality, material compatibility, cleanliness, filtration, corrosion control, condensation prevention, and leak detection. Make isolation, fluid handling, component replacement, and servicing safe and maintainable. Low-voltage connectivity and structured cabling Own the physical-layer architecture. Reference designs for rack, row, cage, and site connectivity: copper and fiber distribution, patch-panel placement, cross-connect demarcations, diverse routes, and reserved expansion capacity. Engineer fiber and copper connectivity. Specify media, connectors, trunks, cassettes, and patching for equipment reach and performance. Validate optical loss budgets, connector counts, polarity, breakouts, bend radius, and compatibility across hardware generations. Produce buildable designs. Pathway layouts, fiber schedules, port-to-port patching plans, cable-length schedules, bills of materials, and installation specs. Connect to colocation and carrier infrastructure. Qualify meet-me-room access, provider pathways, cross-connect options, demarcation points, and route diversity. Define handoffs with data center providers, carriers, ISPs, and Cloudflare's network strategy team. Integration, controls, and resilience Coordinate white-space interfaces. Layouts that account for rack access, airflow, liquid-cooling pipes and manifolds, power segregation, pathway capacity, and expansion. Coordinate supports, bonding, grounding, and firestopping with the responsible disciplines and providers. Design for resilience and controlled failure. Evaluate redundancy, shared failure dependencies, cooling and power interruptions, and thermal ride-through. Agree protective responses with hardware and operations teams for pump or CDU failure, loss of facility cooling, leaks, sensor faults, control failures, and power events. Define controls and operational visibility: temperatures, pressures, flows, power metering, leak alarms, equipment status, and capacity telemetry. Governance, delivery, and acceptance Be Cloudflare's owner-side design authority. Own basis-of-design documents, single-line diagrams, P&IDs, cabling and equipment schedules, interface requirements, scopes, responsibility matrices, review gates, and acceptance criteria. Review partner designs and contractor submittals, resolve RFIs and technical disputes, and drive deviations to documented closure. Lead delivery and live-site changes. Guide contractors and remote hands through new deployments, expansions, migrations, and remediation. Work with deployment and operations on installation sequencing, methods of procedure, change controls, and rollback plans that protect running services. Lead commissioning and acceptance. Define factory and site acceptance tests across electrical, cooling, and connectivity: cleanliness and leak-test evidence, flow balancing, loaded performance tests, failure-mode testing, and copper and fiber certification (fiber inspection and cleaning, insertion-loss testing, OTDR where appropriate). Track deficiencies and verify corrective work before sign-off. Keep the physical source of truth accurate. Define labeling and connectivity-record standards. Make sure as-builts, power and cooling records, patching schedules, cross-connect inventories, and test records reconcile with Cloudflare's infrastructure inventory and DCIM. Oversee handover: deficiency closure, operator training, maintenance procedures, spares, and turnover documentation before production. Cost, efficiency, and standards Support sourcing. RFPs, technical bid evaluation, technical negotiations, supplier qualification, and lifecycle cost analysis. Partner with supply chain on prefabricated assemblies, preterminated cabling, rack integration, lead times, and alternatives that cut field labor without cutting quality. Reduce energy and water use. Evaluate phased deployment, consumption, and retrofit options. Evolve standards from evidence. Investigate incidents and recurring installation defects with network and operations teams. Feed commissioning and operating results back into designs, standards, and quality checks. What you'll bring 8+ years in data center mechanical, electrical, or physical-layer infrastructure, critical-facility cooling, or structured cabling, including architecture or technical design leadership. Bachelor's in Electrical or Mechanical Engineering or a related field, or equivalent practical experience. Delivered liquid-cooled compute infrastructure from requirements through commissioning or production handover. Conventional HVAC experience alone doesn't qualify. Create and review electrical single-line diagrams and schematics, with hands-on MV/LV system design including protection, selectivity, and grounding. Strong command of thermodynamics, heat transfer, fluid mechanics, hydraulic calculations, pump and heat-exchanger selection, and cooling performance under variable conditions. Practical experience with CDUs, facility and technology cooling loops, rack distribution, coolant compatibility, leak detection, and the interfaces between liquid-cooled hardware and facility systems. Strong knowledge of copper Ethernet, single-mode and multimode fiber, patching systems, LC and MPO/MTP connectivity, optical loss budgets, polarity, cable management, and the applicable test methods. Experience in colocation environments: cross-connect delivery, diverse physical paths, and the practical constraints of building inside third-party facilities. Able to write and critically review basis-of-design documents, P&IDs, electrical and mechanical specifications, equipment selections, operating sequences, and test plans. Working knowledge of NEC, NFPA, UL, mechanical and plumbing codes, TIA and ISO/IEC structured-cabling standards, relevant ASHRAE data center guidance, and manufacturer operating requirements, and the ability to apply them with qualified local engineering partners. Experience evaluating resilience and maintainability, participating in commissioning, and resolving system-level problems across equipment and organizational boundaries. Experience directing design consultants, contractors, installation partners, or remote hands, with clear ownership of technical decisions and acceptance outcomes. Clear written and verbal communication across disciplines and time zones, and able to run several projects with limited oversight. Legally authorized to work in the United States on a continuing and permanent basis without company sponsorship. [Confirm wording with recruiting.] Bonus points PE, Chartered Engineer, or equivalent registration in electrical or mechanical engineering. BICSI RCDD, DCDC, or a comparable credential. High-density GPU platforms, OCP rack, power, and cooling interfaces, or qualification across multiple hardware and cooling suppliers. Hydraulic and electrical modeling tools (AFT Fathom, PIPE-FLO, ETAP, SKM), thermal or CFD modeling, and validating models against measured performance. High-density optical distribution, parallel optics, preterminated assemblies, and cabling transitions across successive network generations. Modular or prefabricated power or cooling infrastructure, live-site retrofits, DCIM platforms, automated connectivity or telemetry analysis, or lifecycle energy and water performance. Familiarity with Cloudflare-relevant network environments: optical transport, ISP interconnection, out-of-band management, and liquid-cooled rack integration. Travel Travel for site assessments, vendor reviews, factory testing, commissioning, and deployment support, including international travel. What success looks like Sites are qualified against real hardware requirements. Power, cooling, and connectivity responsibilities are unambiguous. Systems prove their electrical, thermal, and connectivity performance, including failure behavior, before handover. Operations has the monitoring, procedures, training, and spares to run them. Why Cloudflare Your work shapes how Cloudflare deploys physical infrastructure across a global network, from long-term architectural choices to getting the next cage online. Strong candidates take different paths. If your experience shows the core capabilities but doesn't match every line above, apply anyway. Compensation Compensation may be adjusted depending on work location. For San Francisco Bay Area based hires: Estimated annual salary of $165,000 - $205,000. For New York based hires: Estimated annual salary of $158,000 - $195,000. Equity This role is eligible to participate in Cloudflare's equity plan. Benefits Cloudflare offers a complete package of benefits and programs to support you and your family. Our benefits programs can help you pay health care expenses, support caregiving, build capital for the future and make life a little easier and fun! The below is a description of our benefits for employees in the United States, and benefits may vary for employees based outside the U.S. Health & Welfare Benefits Medical/Rx Insurance Dental Insurance Vision Insurance Flexible Spending Accounts Commuter Spending Accounts Fertility & Family Forming Benefits On-demand mental health support and Employee Assistance Program Global Travel Medical Insurance Financial Benefits Short and Long Term Disability Insurance Life & Accident Insurance 401(k) Retirement Savings Plan Employee Stock Participation Plan Time Off Flexible paid time off covering vacation and sick leave Leave programs, including parental, pregnancy health, medical, and bereavement leave What Makes Cloudflare Special? We’re not just a highly ambitious, large-scale technology company. We’re a highly ambitious, large-scale technology company with a soul. Fundamental to our mission to help build a better Internet is protecting the free and open Internet. Project Galileo : Since 2014, we've equipped more than 2,400 journalism and civil society organizations in 111 countries with powerful tools to defend themselves against attacks that would otherwise censor their work, technology already used by Cloudflare’s enterprise customers--at no cost. Athenian Project : In 2017, we created the Athenian Project to ensure that state and local governments have the highest level of protection and reliability for free, so that their constituents have access to election information and voter registration. Since the project, we've provided services to more than 425 local government election websites in 33 states. 1.1.1.1 : We released 1.1.1.1 to help fix the foundation of the Internet by building a faster, more secure and privacy-centric public DNS resolver. This is available publicly for everyone to use - it is the first consumer-focused service Cloudflare has ever released. Here’s the deal - we don’t store client IP addresses never, ever. We will continue to abide by our privacy commitment and ensure that no user data is sold to advertisers or used to target consumers. Sound like something you’d like to be a part of? We’d love to hear from you! Please note that applicants who progress to the offer stage of the interview process may be asked to attend an in-person interview within one of the Cloudflare Offices or Cloudflare Hubs.  More details about this will be available at that stage of the interview process. This position may require access to information protected under U.S. export control laws, including the U.S. Export Administration Regulations. Please note that any offer of employment may be conditioned on your authorization to receive software or technology controlled under these U.S. export laws without sponsorship for an export license. Cloudflare is proud to be an equal opportunity employer.  We are committed to providing equal employment opportunity for all people and place great value in both diversity and inclusiveness.  All qualified applicants will be considered for employment without regard to their, or any other person's, perceived or actual race, color, religion, sex, gender, gender identity, gender expression, sexual orientation, national origin, ancestry, citizenship, age, physical or mental disability, medical condition, family care status, or any other basis protected by law. We are an AA/Veterans/Disabled Employer. Cloudflare provides reasonable accommodations to qualified individuals with disabilities.  Please tell us if you require a reasonable accommodation to apply for a job. Examples of reasonable accommodations include, but are not limited to, changing the application process, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment.  If you require a reasonable accommodation to apply for a job, please contact us via e-mail at hr@cloudflare.com or via mail at 101 Townsend St. San Francisco, CA 94107.