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Location: Canada (Remote) Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X . We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity. This is a remote opportunity and we are looking for candidates from Canada. Residents of Quebec are not eligible for this role. The Opportunity Grafana Labs is seeking a Staff Engineer (AI & Automation) to own the AI agent infrastructure and automation platform that powers our Marketing Operations organization. You’ll build multi-agent architectures, LLM integrations, and backend services that connect AI models to internal and third-party data platforms. You’ll ship production systems that teams depend on daily. This is a high-autonomy role where you own the technical direction. You’ll identify the highest-leverage problems across Marketing, RevOps, and SDR teams, design the solutions, and ship them. You’ll define the technical direction for the automation platform (data models, API contracts, shared libraries, reference architectures) and partner with Data Engineering, GTM Systems, and Field Operations to build scalable, self-service automation that eliminates manual work and drives operational efficiency. What You'll Be Doing Agentic Systems & AI Infrastructure Own end-to-end development of multi-agent AI systems, from architecture and implementation through testing, deployment, and ongoing operation Build modular, composable agentic systems using orchestration frameworks (LangChain, CrewAI, Anthropic MCP, or similar) that operate 24/7 across teams Develop reusable agentic skills that agents invoke across interfaces (Slack, dashboards, internal apps, CLIs) Implement observability and feedback loops including logging, performance metrics, prompt iteration, model evaluation, and cost management Establish governance and compliance standards for AI workflows including access controls, audit trails, PII handling, and human-in-the-loop escalation paths Systems Integration & Backend Services Build MCP servers, APIs, CLIs, and microservices connecting AI models to business systems (BigQuery, Slack, CRMs, email, calendars, analytics tools) Architect data flows for retrieval-augmented generation (RAG), connecting LLMs to internal knowledge bases, customer data, and real-time business context Build serverless or containerized services (GCP Cloud Functions, Cloud Run) that scale with usage and integrate with Grafana's cloud infrastructure Automation & Workflow Enablement Partner with RevOps, Demand Generation, Regional Marketing, and SDR teams to scope high-impact automation problems, identify bottlenecks, and build solutions with measurable business outcomes Design and deploy workflows using orchestration tools (n8n, Workato, or custom platforms) with CI/CD, testing, and production reliability standards Build systems designed for self-service with documentation, playbooks, and enablement materials that let partner teams operate independently We invest heavily in developer productivity. You'll have access to AI coding assistants (Claude Code, Gemini CLI, OpenAI Codex, and others of your choice within security guidelines). We encourage pragmatic AI-assisted development paired with strong code review and quality standards. What Makes You a Great Fit 8+ years of software engineering experience with depth in backend development, systems integration, or data/analytics engineering 2+ years hands-on experience applying LLMs/AI to production workflows, not just prototypes Strong proficiency in Python and JavaScript/Node.js with Git-based workflows, code review practices, and testing discipline Hands-on experience with LLM frameworks and patterns including prompt engineering, RAG, function calling/tool use, structured output parsing, and evaluation Experience building and operating multi-agent systems at scale including agent decomposition, orchestration patterns (sequential chains, router/dispatcher, parallel fan-out), state management, and production monitoring You diagnose business problems before writing code. You think in workflows and outcomes, not just functions. Deep familiarity with Google Cloud Platform, BigQuery, and serverless/containerized services (Cloud Functions, Cloud Run) Understanding of LLM failure modes and production mitigations including confidence thresholds, fallback logic, human escalation, and cost/latency management Proven ability to identify high-leverage problems, push back on low-impact requests, and deliver end-to-end with minimal direction Fluent with AI-assisted development tools (GitHub Copilot, Cursor, Claude Code). You use AI to build AI systems Clear technical communicator who can explain complex systems in simple terms to both engineers and business stakeholders Bonus Points Experience with vector databases or retrieval pipelines (Pinecone, Weaviate, ChromaDB, Qdrant, pgvector) Familiarity with marketing or sales platforms (Salesforce, Customer.io, HubSpot, Marketo, Outreach) Experience with frontend frameworks (React, Slack Block Kit) for building user-facing AI tool interfaces Observability tooling for AI systems (LangSmith, Weights & Biases, custom evaluation frameworks) Experience with workflow orchestration platforms (n8n, Temporal, Prefect, Airflow) Familiarity with Model Context Protocol (MCP) or similar standards for connecting AI systems to data sources Prior work automating marketing, sales, or customer success workflows in a B2B SaaS environment Active in open-source communities. Grafana is built on OSS and we value engineers who share that DNA In Canada, the base compensation range for this role is CAD 164,490 - CAD 197,389 . Actual compensation may vary based on level, experience, and skillset as assessed throughout the interview process. All of our roles include Restricted Stock Units (RSUs), giving every team member ownership in Grafana Labs' success. We believe in shared outcomes—RSUs help us stay aligned and invested as we scale globally. *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process. Why You’ll Thrive at Grafana Labs: 100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose. Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment. Transparent Communication – Expect open decision-making and regular company-wide updates. Innovation-Driven – Autonomy and support to ship great work and try new things. Open Source Roots – Built on community-driven values that shape how we work. Empowered Teams – High trust, low ego culture that values outcomes over optics. Career Growth Pathways – Defined opportunities to grow and develop your career. Approachable Leadership – Transparent execs who are involved, visible, and human. Passionate People – Join a team of smart, supportive folks who care deeply about what they do. In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it. Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable. Equal Opportunity Employer: Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow. Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings. #LI-Remote For information about how your personal data is used once you’ve applied to a job, check out our privacy policy .

Location: Remote: United States Workplace: Remote At Render, we’re building the modern cloud platform for developers creating AI-native, full-stack, multi-service applications. Our mission is to eliminate the tradeoff between the power of hyperscalers and the simplicity of developer-friendly platforms—so teams can ship fast, scale reliably, and focus on their product, not infrastructure. Unlike complex hyperscalers or ephemeral edge/serverless solutions, Render offers a developer-first experience with persistent compute, dynamic autoscaling, built-in orchestration, and observability, allowing teams to launch, scale, and manage real-world applications without writing infrastructure code or managing servers. Whether you're building LLM-powered applications, scalable SaaS products, or async processing pipelines, Render empowers teams to move fast and scale confidently from MVP to millions of users. Our platform is trusted by over 7 million developers worldwide and continues to grow rapidly. In February 2026, we raised an additional $100M in Series C financing, bringing our total funding to $260M, to accelerate our vision of making cloud infrastructure both powerful and intuitive—designed for the speed of modern AI development. We’re a diverse and talented team that values craft, velocity, and user experience. If you’re excited to help shape the future of the intelligent cloud and empower developers everywhere, we’d love to hear from you. APPLYING TO RENDER We're seeking candidates who possess high integrity, humility, and an insatiable drive to learn. Through reasoned discussions and continuous feedback, we strive to improve both individually and collectively. We foster an environment of mutual trust and respect, empowering effective debate to achieve the best outcomes for our customers and team. We especially encourage members of underrepresented groups in the tech community to apply and understand that not all successful candidates will meet each requirement listed. Our interview process is unique to each role, and we value the candidate experience just as much as our customer experience. We hope your conversations with us reflect a thoughtful process that is illuminative, enjoyable, and respectful of your time. ABOUT THE ROLE Developers increasingly pick their tools through AI assistants and coding agents. When someone asks ChatGPT, Claude, or a coding agent where to deploy their app, we want Render to be the answer. That depends on content that exists, is accurate, and stays current. As Render’s Senior Content Engineer, you’ll own the strategy and the system behind that content. You’ll find the gaps in our content catalog based on how Render shows up in LLM and answer-engine results, decide which gaps matter most, and build and run the content factory that fills them. The role sits close to DX Engineering and is fully focused on content. You’ll work directly with the Head of Developer Experience, the DX team, Render’s docs owners, and external content partners. The primary audience for this content is coding agents and LLMs. You’ll ship focused, technically grounded pieces that help them answer developer questions and cite Render: use-case articles, stack-specific guides, comparisons, and docs. The field is still taking shape, so you’ll test what works and help write the playbook. This is a remote role within the US, with the option to work out of our headquarters in San Francisco. WHAT YOU'LL DO - Own Render’s content gap analysis. Use AEO benchmarks, citation tracking, and AI agent traffic data to find where Render is missing, wrong, or out-cited in LLM answers, and turn noisy signals into clear priorities. - Turn that analysis into a prioritized backlog across articles, guides, and docs, with clear reasoning for what ships first. - Build and improve Render’s content factory: the AI-assisted pipelines, built on Render Workflows, that research, draft, fact-check, and assist us in publishing technical content. Test changes with evals and keep the system reliable as output grows. - Own the review loop. Make expert review faster and cheaper, track factual accuracy, and keep the quality bar high at higher volume. - Run the refresh cycle for existing content so pages stay accurate as the product changes. - Manage day-to-day work with external content partners: briefs, feedback, quality, and output. - Partner with docs owners to expand docs coverage where it drives citations. - Define and report the metrics that show whether content moves Render’s visibility and signups. Volume published is one input among several. WHAT SUCCESS LOOKS LIKE - The content factory is reliable, well maintained, and keeps up as our content needs grow. - Render shows up more often in agent and LLM answers for the topics the content plan targets. - Content stays technically accurate, and expert review takes less time per piece as output grows. - The content plan responds to gaps in our catalog and to what we learn about Render’s visibility in agent and LLM answers. - We have a plan and a workflow to keep the catalog up to date as the product changes. WHAT WE'RE LOOKING FOR - 5+ years in technical content, developer education, content engineering, or software engineering with a strong content focus, ideally at a developer tools or infrastructure company. - A working understanding of AEO or generative engine optimization (GEO) and how answer engines choose sources. The field is new, so we care about what you’ve built and measured, and how fast you learn. - Strong working knowledge of AI agents. You use coding agents like Claude Code, Codex, or Cursor every day, and you know agent workloads (long-running tasks, tool calls, sandboxed code execution) well enough to judge whether content about them is correct. - A builder’s approach to AI. You’ve built content systems in code (scripts, pipelines, LLM and agent workflows) and use evals to understand what a change affects. Comfortable with Python or TypeScript, Git, and APIs. - Strong technical judgment. You can read a docs page or code sample and tell whether it’s correct. - Sharp editorial taste. You catch weak structure, generic AI-generated prose, and factual errors fast. - Comfort owning a system end to end and holding external partners to a quality bar. NICE-TO-HAVES - Experience running SEO or programmatic content at scale, especially for developer audiences. - Experience with LLM benchmarking or answer-engine measurement. - Experience building agents or MCP servers. - Familiarity with cloud hosting, deployment, or infrastructure products. - You’ve used Render before, professionally or on side projects. PROJECTS YOU MIGHT WORK ON - Sizing the long tail of developer questions where Render should be cited and isn’t, then building the plan to cover it. - Adding an automated fact-check stage to the content pipeline that verifies claims against live Render docs. - Building a refresh system that flags stale content when the product changes. - Running a recurring survey of LLM answers to measure where Render appears and who gets cited instead. If this role excites you but you don’t meet every single requirement, we’d still love to hear from you—your unique experience might be just what we need. BENEFITS - 4 weeks of paid vacation. - 14 weeks of fully paid parental leave for all parents to bond with a newly born, adopted, or fostered child. We will also work with you to create a supportive plan of return. - Long-term disability, life insurance, and 401K plans. - 100% employer-paid medical coverage and 99% employer-paid dental and vision coverage for you and a dependent. FSAs and HSAs are available as well. - Monthly lifestyle stipend for wellness, mental health and therapy, hobbies, etc. - Monthly cell phone and internet subsidy. - Commuter benefits for Renders in the Bay Area, and home office stipends for remote Renders. - Continuous learning benefits & related support. This position is generally not eligible for new visa sponsorship. At Render's discretion, the business may sponsor existing visa transfers. Applicants who require sponsorship must receive business authorization. Render is an equal-opportunity employer. We know that employing a team rich in diverse thoughts, experiences, and opinions allows our employees, product, and community to flourish. We make all employment decisions including hiring, evaluation, termination, promotional, and training opportunities, without regard to race, religion, color, sex, age, national origin, ancestry, sexual orientation, physical handicap, mental disability, medical condition, disability, gender or identity or expression, pregnancy or pregnancy-related condition, marital status, height and/or weight. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation. We encourage all who are interested to apply. We can't wait to hear from you! Render — CCPA Applicant Privacy Notice https://drive.google.com/file/d/1wKr9IejoT5McFrs9I2mahQnf6AFwb3z2/view Render — GDPR Applicant Privacy Notice https://drive.google.com/file/d/1_8jtyXQ1HdRdTdQn9sZ7n-R-zAGBmsFa/view

Location: Australia Workplace: Remote ABOUT DOCKER Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout. We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default. _______________________________________________________________________ THE ROLE Docker is launching a Professional Services organization to accelerate customer success, reduce time-to-value, and drive enterprise adoption for agentic workloads. As a Principal Solution Architect, you'll play a critical role in building and scaling this function. You will join a team of seasoned experts with deep experience backed by Docker's unmatched reach across Fortune 500 companies.   This is a high-visibility role working directly with senior leadership across revenue, product, marketing, and partner organizations. You'll shape service strategy, drive cross-functional alignment, and deliver offerings that accelerate both services revenue and platform expansion.   You'll serve as a trusted advisor to our largest and most strategic partners and enterprise customers, providing thought leadership on integrating Docker agentic solutions within enterprise environments. _______________________________________________________________________   RESPONSIBILITIES Build and Scale the Professional Services Practice - Develop and codify repeatable reference architecture patterns across Docker's core use cases including self-hosted and air-gapped deployments, MCP (model context protocol)/AI agent environments, IDP integrations, and secure supply chain workflows so that engagements scale consistently across customers and partners. - Translate reference architectures into customer-facing technical collateral, SOW templates, and success patterns that reduce scoping time and improve delivery consistency. - Collaborate with product, marketing, and revenue teams to integrate services into GTM motions and align delivery to Docker's AI platform roadmap. - Identify offerings that drive product expansion, renewals, and long-term customer value. - Support Partnerships & Alliances in selecting, onboarding, and enabling technical integration partners, system integrators (SIs), and service delivery partners. Drive Strategic Customer Outcomes - Act as a trusted advisor to enterprise customers, helping them adopt modern patterns for containerization, AI workflows, and secure software supply chains. - Lead technical discovery and architecture engagements that span enterprise integration layers - Architect and deliver self-hosted Docker deployments within air-gapped, regulated, and complex enterprise environments including local image registry setup, offline toolchain configuration, and compliance-driven infrastructure design. - Design and Guide customers through implementation of agentic AI toolchains, including MCP server/client architecture, tool orchestration, observability integration and secure deployment patterns aligned to Docker's AI platform. - Position Docker as a strategic and thought leadership partner, influencing long-term technology adoption and investment decisions. - Directly deliver or assign and oversee appropriate delivery partners to execute service engagements and ensure technical objectives are met. Enable Cross-Functional Success - Drive alignment and decision-making across multiple stakeholders and teams without direct reporting lines. - Translate field insights including enterprise integration patterns, IDP/SSO friction points, observability gaps, and AI deployment challenges into actionable product and services strategy, roadmap, and partner capabilities. _______________________________________________________________________   QUALIFICATIONS REQUIRED - 7+ years as a Professional Services Solution Architect, Technical Consultant, or similar role at a SaaS/infrastructure company or consulting firm. - Demonstrated experience architecting and deploying self-hosted and air-gapped deployment architectures: local image registries, offline toolchain configuration, network-isolated Kubernetes clusters, and compliance-driven infrastructure constraints common in regulated industries. - Enterprise integration experience across Identity Providers (Okta, Azure AD, LDAP/Active Directory) and federated identity protocols (OIDC, SAML, SSO), including RBAC design within complex, multi-tenant enterprise environments. - Working knowledge of Model Context Protocol (MCP) and its application to agentic AI toolchains including MCP server/client architecture, tool and resource orchestration, and secure containerized deployment patterns. - Hands-on experience with AI/ML workflows, LLM deployment, and agentic AI architectures in enterprise environments with awareness of Docker's AI platform roadmap including AI agent containerization, model provenance, and AI supply chain security. - Deep understanding of container and software supply chain security: Docker Hardened Images (DHI), Secure Supply Chain (SSC), SBOM generation, image signing and attestation, vulnerability management, and runtime governance. - Excellent facilitation and stakeholder management skills; able to lead executive-level architecture conversations and influence senior stakeholders without formal authority. - Direct experience delivering high-quality services engagements that achieve customer value while meeting revenue and ARR growth targets within a revenue organization. - Recognition by enterprise customers as a strategic technical advisor. BONUS - Experience architecting AI platforms in large enterprise environments LLM deployment pipelines, model provenance, artifact signing, and secure AI supply chain patterns. - Background enabling system integrators, consultancies, or partner ecosystems. - Consulting experience with Fortune 500 clients in highly regulated sectors such as financial services, healthcare, or government. - Led AI security architecture engagements that addressed model provenance, artifact signing, and supply chain integrity for containerized AI workloads including secure MCP server deployment, tool and resource access controls, secrets management within agentic pipelines, and runtime isolation patterns for LLM-based applications. _______________________________________________________________________   WHAT TO EXPECT FIRST 30 DAYS - Onboard to Docker's mission, values, and operating model. - Deeply familiarize yourself with our product portfolio, AI platform roadmap, and strategic customers. - Build strong partnerships with Product, Engineering, and Sales functions. - Plug into the team's rhythm of business (standups, reviews, shadow customer engagements). FIRST 90 DAYS - Scope, define SOWs, delivery, and oversight of customer service engagements. - Participate in the creation of reference architectures for key use cases.. - Participate in initiatives to build out and improve the services department's offerings. ONE-YEAR OUTLOOK - Successful delivery and oversight of customer service engagements. - Contribute materially to the build-out of Docker's service offerings across AI, security, and enterprise integration practices. - Institutionalize continuous improvement by providing field feedback including enterprise integration patterns, deployment blockers, and observability gaps to the product team.   Visa sponsorship: Not available for this role. ______________________________________________________________________ POSTING INFORMATION - Open vacancy: This posting is for an existing open role. - AI in hiring: Docker may use AI-assisted tools during our recruiting process. - Interview recordings: Candidates will be invited to opt in to interview recordings to support interviewer calibration and consistent evaluations. Recordings are optional and require explicit consent. ______________________________________________________________________ PERKS & BENEFITS - Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration. - Flexibility that fits your life – We trust you to manage your schedule while delivering great work. - Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break. - Home office support – Set up your workspace for comfort and success. - Technology stipend – Equivalent to US$100 net per month to help support your work. - Learning & development – Annual stipend for conferences, courses, certifications, and continued learning. - Parental leave – 16 weeks of paid parental leave after six months of employment. - Equity for all full-time employees – Share in Docker's long-term success as we continue to grow. - Comprehensive benefits – Medical, retirement, and paid holidays vary by country. - Docker swag – Because representing the whale never gets old. Docker is proud to be an equal opportunity employer. We are committed to building a team that reflects a broad range of backgrounds, experiences, and perspectives. We believe diverse teams build better products, make better decisions, and better serve our global community. #LI-REMOTE

Location: (Multiple States), United Kingdom About Improvado Improvado is a marketing data and AI analytics platform for enterprise brands and agencies. We connect 500+ marketing and sales data sources, normalize them through a governed data model, and put an AI agent on top so marketing teams can ask questions of their own data without going through BI or IT. What we sell: extraction and 500+ connectors; data transformation (SQL and dbt-compatible); Marketing Data Governance — taxonomy, naming, data-quality rules; warehouse and storage; dashboards; AI agent and MCP access to live marketing data; DECS, data engineering as a service on a 2 to 4 week SLA. Who buys it: Economic buyers: CMO, VP Marketing, VP Demand Gen, agency COO and ops leadership Technical evaluators: VP or Director of Marketing Analytics, marketing analysts, data engineering, sometimes IT and security Segments: enterprise brands, mid-market, agencies Verticals: pharma and healthcare, financial services, retail and eCommerce, gaming, agencies Why this role, now Our messaging is not aligned. Positioning, web, sales pitch, product and content each carry a different version of what Improvado is. The market categorizes us as "marketing ETL" while we position as an AI marketing analytics platform. That gap costs us deal quality and price. The category is crowded and moving fast. Battlecards exist but decay, and nobody owns keeping them true. Attribution, incrementality and causal measurement is where deals are won and lost — and it is the hardest thing to argue credibly without hand-waving. Analyst firms are a silent blocker. When an enterprise buyer asks Gartner or Forrester about Improvado, there is no briefed narrative waiting for them. You would not start from a blank page. We already have a positioning registry, roughly 11 documented buyer personas, a pain-point and value-prop library, competitor intel reports and about 10 battlecards. They are inconsistent and under-used. Your first job is to make one version true and make people use it. What you'll own Positioning and messaging. Core positioning, category framing and message hierarchy across ICPs and personas. ICP and persona documentation that is used, not filed. The messaging layer of new product and feature launches, including the internal rollout that makes the field able to sell it. Competitive intelligence and win/loss. A structured win/loss interview program with quarterly readouts. Living battlecards. Monitoring competitor positioning, pricing and product moves, and driving our counter-positioning. Sales enablement. The core pitch narrative, demo storyline and objection-handling framework. The messaging components of new-rep onboarding. A standing weekly cadence with Sales leadership — not quarterly check-ins. Direct support on competitive and enterprise deals: RFPs, security and technical evaluations, displacement plays. Market and analyst relations. The Improvado narrative for Gartner, Forrester and category influencers, so that a buyer's analyst call becomes an accelerator rather than a blocker. Feeding structured market and buyer insight back into product prioritization. What we're looking for 4 to 8 years in product marketing, or an equivalent blend of product marketing with marketing analytics, marketing or data ops, sales engineering, analytics consulting, or product management on a data product. Category fluency in marketing data and measurement: attribution models, incrementality testing, MMM, data governance and taxonomy, warehouses and ETL/ELT — including where each is honestly weak. B2B SaaS sold to marketing or data buyers. Marketing analytics, martech, measurement, CDP, BI and data-infrastructure vendors are the reference profile. Proof you have shipped, not just documented: positioning that changed the website and the pitch, battlecards reps actually opened, a win/loss program that survived past its second quarter. Writing that survives contact with a skeptical technical buyer — claim and evidence, not adjective stacking. Comfort operating close to Sales: weekly cadence, deal reviews, live calls, direct feedback. Nice to have: hands-on SQL, dbt or BI, enough to validate a claim yourself. Experience marketing AI capabilities without hype. Analyst-relations experience. Agency-side or enterprise-brand background. Vertical depth in pharma and healthcare, financial services, retail and eCommerce, or gaming. Not a fit if: your product marketing has been mostly launch logistics and content calendars; you need a fully staffed team and a finished brand system to be effective; you are uncomfortable being told in a deal review that your messaging did not work. How we measure success Win rate in competitive deals against our top 3 named competitors, baseline set in month 1. Stage-to-stage conversion on open opportunities, particularly discovery to demo to proposal. Time-to-first-deal for new reps. Field adoption of enablement assets — measured, not assumed. Win/loss program running on cadence, with themes that visibly change product and GTM decisions. Message consistency: a quarterly audit across web, deck, product UI and content. What We Offer Remote-first environment Strong product/market fit: marketing data product for US-based enterprises 20 working days of PTO per year US holidays and additional days off Professional development reimbursement

Location: (Multiple States), Germany About Improvado Improvado is a marketing data and AI analytics platform for enterprise brands and agencies. We connect 500+ marketing and sales data sources, normalize them through a governed data model, and put an AI agent on top so marketing teams can ask questions of their own data without going through BI or IT. What we sell: extraction and 500+ connectors; data transformation (SQL and dbt-compatible); Marketing Data Governance — taxonomy, naming, data-quality rules; warehouse and storage; dashboards; AI agent and MCP access to live marketing data; DECS, data engineering as a service on a 2 to 4 week SLA. Who buys it: Economic buyers: CMO, VP Marketing, VP Demand Gen, agency COO and ops leadership Technical evaluators: VP or Director of Marketing Analytics, marketing analysts, data engineering, sometimes IT and security Segments: enterprise brands, mid-market, agencies Verticals: pharma and healthcare, financial services, retail and eCommerce, gaming, agencies Why this role, now Our messaging is not aligned. Positioning, web, sales pitch, product and content each carry a different version of what Improvado is. The market categorizes us as "marketing ETL" while we position as an AI marketing analytics platform. That gap costs us deal quality and price. The category is crowded and moving fast. Battlecards exist but decay, and nobody owns keeping them true. Attribution, incrementality and causal measurement is where deals are won and lost — and it is the hardest thing to argue credibly without hand-waving. Analyst firms are a silent blocker. When an enterprise buyer asks Gartner or Forrester about Improvado, there is no briefed narrative waiting for them. You would not start from a blank page. We already have a positioning registry, roughly 11 documented buyer personas, a pain-point and value-prop library, competitor intel reports and about 10 battlecards. They are inconsistent and under-used. Your first job is to make one version true and make people use it. What you'll own Positioning and messaging. Core positioning, category framing and message hierarchy across ICPs and personas. ICP and persona documentation that is used, not filed. The messaging layer of new product and feature launches, including the internal rollout that makes the field able to sell it. Competitive intelligence and win/loss. A structured win/loss interview program with quarterly readouts. Living battlecards. Monitoring competitor positioning, pricing and product moves, and driving our counter-positioning. Sales enablement. The core pitch narrative, demo storyline and objection-handling framework. The messaging components of new-rep onboarding. A standing weekly cadence with Sales leadership — not quarterly check-ins. Direct support on competitive and enterprise deals: RFPs, security and technical evaluations, displacement plays. Market and analyst relations. The Improvado narrative for Gartner, Forrester and category influencers, so that a buyer's analyst call becomes an accelerator rather than a blocker. Feeding structured market and buyer insight back into product prioritization. What we're looking for 4 to 8 years in product marketing, or an equivalent blend of product marketing with marketing analytics, marketing or data ops, sales engineering, analytics consulting, or product management on a data product. Category fluency in marketing data and measurement: attribution models, incrementality testing, MMM, data governance and taxonomy, warehouses and ETL/ELT — including where each is honestly weak. B2B SaaS sold to marketing or data buyers. Marketing analytics, martech, measurement, CDP, BI and data-infrastructure vendors are the reference profile. Proof you have shipped, not just documented: positioning that changed the website and the pitch, battlecards reps actually opened, a win/loss program that survived past its second quarter. Writing that survives contact with a skeptical technical buyer — claim and evidence, not adjective stacking. Comfort operating close to Sales: weekly cadence, deal reviews, live calls, direct feedback. Nice to have: hands-on SQL, dbt or BI, enough to validate a claim yourself. Experience marketing AI capabilities without hype. Analyst-relations experience. Agency-side or enterprise-brand background. Vertical depth in pharma and healthcare, financial services, retail and eCommerce, or gaming. Not a fit if: your product marketing has been mostly launch logistics and content calendars; you need a fully staffed team and a finished brand system to be effective; you are uncomfortable being told in a deal review that your messaging did not work. How we measure success Win rate in competitive deals against our top 3 named competitors, baseline set in month 1. Stage-to-stage conversion on open opportunities, particularly discovery to demo to proposal. Time-to-first-deal for new reps. Field adoption of enablement assets — measured, not assumed. Win/loss program running on cadence, with themes that visibly change product and GTM decisions. Message consistency: a quarterly audit across web, deck, product UI and content. What We Offer Remote-first environment Strong product/market fit: marketing data product for US-based enterprises 20 working days of PTO per year US holidays and additional days off Professional development reimbursement

Location: (Multiple States), France About Improvado Improvado is a marketing data and AI analytics platform for enterprise brands and agencies. We connect 500+ marketing and sales data sources, normalize them through a governed data model, and put an AI agent on top so marketing teams can ask questions of their own data without going through BI or IT. What we sell: extraction and 500+ connectors; data transformation (SQL and dbt-compatible); Marketing Data Governance — taxonomy, naming, data-quality rules; warehouse and storage; dashboards; AI agent and MCP access to live marketing data; DECS, data engineering as a service on a 2 to 4 week SLA. Who buys it: Economic buyers: CMO, VP Marketing, VP Demand Gen, agency COO and ops leadership Technical evaluators: VP or Director of Marketing Analytics, marketing analysts, data engineering, sometimes IT and security Segments: enterprise brands, mid-market, agencies Verticals: pharma and healthcare, financial services, retail and eCommerce, gaming, agencies Why this role, now Our messaging is not aligned. Positioning, web, sales pitch, product and content each carry a different version of what Improvado is. The market categorizes us as "marketing ETL" while we position as an AI marketing analytics platform. That gap costs us deal quality and price. The category is crowded and moving fast. Battlecards exist but decay, and nobody owns keeping them true. Attribution, incrementality and causal measurement is where deals are won and lost — and it is the hardest thing to argue credibly without hand-waving. Analyst firms are a silent blocker. When an enterprise buyer asks Gartner or Forrester about Improvado, there is no briefed narrative waiting for them. You would not start from a blank page. We already have a positioning registry, roughly 11 documented buyer personas, a pain-point and value-prop library, competitor intel reports and about 10 battlecards. They are inconsistent and under-used. Your first job is to make one version true and make people use it. What you'll own Positioning and messaging. Core positioning, category framing and message hierarchy across ICPs and personas. ICP and persona documentation that is used, not filed. The messaging layer of new product and feature launches, including the internal rollout that makes the field able to sell it. Competitive intelligence and win/loss. A structured win/loss interview program with quarterly readouts. Living battlecards. Monitoring competitor positioning, pricing and product moves, and driving our counter-positioning. Sales enablement. The core pitch narrative, demo storyline and objection-handling framework. The messaging components of new-rep onboarding. A standing weekly cadence with Sales leadership — not quarterly check-ins. Direct support on competitive and enterprise deals: RFPs, security and technical evaluations, displacement plays. Market and analyst relations. The Improvado narrative for Gartner, Forrester and category influencers, so that a buyer's analyst call becomes an accelerator rather than a blocker. Feeding structured market and buyer insight back into product prioritization. What we're looking for 4 to 8 years in product marketing, or an equivalent blend of product marketing with marketing analytics, marketing or data ops, sales engineering, analytics consulting, or product management on a data product. Category fluency in marketing data and measurement: attribution models, incrementality testing, MMM, data governance and taxonomy, warehouses and ETL/ELT — including where each is honestly weak. B2B SaaS sold to marketing or data buyers. Marketing analytics, martech, measurement, CDP, BI and data-infrastructure vendors are the reference profile. Proof you have shipped, not just documented: positioning that changed the website and the pitch, battlecards reps actually opened, a win/loss program that survived past its second quarter. Writing that survives contact with a skeptical technical buyer — claim and evidence, not adjective stacking. Comfort operating close to Sales: weekly cadence, deal reviews, live calls, direct feedback. Nice to have: hands-on SQL, dbt or BI, enough to validate a claim yourself. Experience marketing AI capabilities without hype. Analyst-relations experience. Agency-side or enterprise-brand background. Vertical depth in pharma and healthcare, financial services, retail and eCommerce, or gaming. Not a fit if: your product marketing has been mostly launch logistics and content calendars; you need a fully staffed team and a finished brand system to be effective; you are uncomfortable being told in a deal review that your messaging did not work. How we measure success Win rate in competitive deals against our top 3 named competitors, baseline set in month 1. Stage-to-stage conversion on open opportunities, particularly discovery to demo to proposal. Time-to-first-deal for new reps. Field adoption of enablement assets — measured, not assumed. Win/loss program running on cadence, with themes that visibly change product and GTM decisions. Message consistency: a quarterly audit across web, deck, product UI and content. What We Offer Remote-first environment Strong product/market fit: marketing data product for US-based enterprises 20 working days of PTO per year US holidays and additional days off Professional development reimbursement

Location: (Multiple States), Ireland About Improvado Improvado is a marketing data and AI analytics platform for enterprise brands and agencies. We connect 500+ marketing and sales data sources, normalize them through a governed data model, and put an AI agent on top so marketing teams can ask questions of their own data without going through BI or IT. What we sell: extraction and 500+ connectors; data transformation (SQL and dbt-compatible); Marketing Data Governance — taxonomy, naming, data-quality rules; warehouse and storage; dashboards; AI agent and MCP access to live marketing data; DECS, data engineering as a service on a 2 to 4 week SLA. Who buys it: Economic buyers: CMO, VP Marketing, VP Demand Gen, agency COO and ops leadership Technical evaluators: VP or Director of Marketing Analytics, marketing analysts, data engineering, sometimes IT and security Segments: enterprise brands, mid-market, agencies Verticals: pharma and healthcare, financial services, retail and eCommerce, gaming, agencies Why this role, now Our messaging is not aligned. Positioning, web, sales pitch, product and content each carry a different version of what Improvado is. The market categorizes us as "marketing ETL" while we position as an AI marketing analytics platform. That gap costs us deal quality and price. The category is crowded and moving fast. Battlecards exist but decay, and nobody owns keeping them true. Attribution, incrementality and causal measurement is where deals are won and lost — and it is the hardest thing to argue credibly without hand-waving. Analyst firms are a silent blocker. When an enterprise buyer asks Gartner or Forrester about Improvado, there is no briefed narrative waiting for them. You would not start from a blank page. We already have a positioning registry, roughly 11 documented buyer personas, a pain-point and value-prop library, competitor intel reports and about 10 battlecards. They are inconsistent and under-used. Your first job is to make one version true and make people use it. What you'll own Positioning and messaging. Core positioning, category framing and message hierarchy across ICPs and personas. ICP and persona documentation that is used, not filed. The messaging layer of new product and feature launches, including the internal rollout that makes the field able to sell it. Competitive intelligence and win/loss. A structured win/loss interview program with quarterly readouts. Living battlecards. Monitoring competitor positioning, pricing and product moves, and driving our counter-positioning. Sales enablement. The core pitch narrative, demo storyline and objection-handling framework. The messaging components of new-rep onboarding. A standing weekly cadence with Sales leadership — not quarterly check-ins. Direct support on competitive and enterprise deals: RFPs, security and technical evaluations, displacement plays. Market and analyst relations. The Improvado narrative for Gartner, Forrester and category influencers, so that a buyer's analyst call becomes an accelerator rather than a blocker. Feeding structured market and buyer insight back into product prioritization. What we're looking for 4 to 8 years in product marketing, or an equivalent blend of product marketing with marketing analytics, marketing or data ops, sales engineering, analytics consulting, or product management on a data product. Category fluency in marketing data and measurement: attribution models, incrementality testing, MMM, data governance and taxonomy, warehouses and ETL/ELT — including where each is honestly weak. B2B SaaS sold to marketing or data buyers. Marketing analytics, martech, measurement, CDP, BI and data-infrastructure vendors are the reference profile. Proof you have shipped, not just documented: positioning that changed the website and the pitch, battlecards reps actually opened, a win/loss program that survived past its second quarter. Writing that survives contact with a skeptical technical buyer — claim and evidence, not adjective stacking. Comfort operating close to Sales: weekly cadence, deal reviews, live calls, direct feedback. Nice to have: hands-on SQL, dbt or BI, enough to validate a claim yourself. Experience marketing AI capabilities without hype. Analyst-relations experience. Agency-side or enterprise-brand background. Vertical depth in pharma and healthcare, financial services, retail and eCommerce, or gaming. Not a fit if: your product marketing has been mostly launch logistics and content calendars; you need a fully staffed team and a finished brand system to be effective; you are uncomfortable being told in a deal review that your messaging did not work. How we measure success Win rate in competitive deals against our top 3 named competitors, baseline set in month 1. Stage-to-stage conversion on open opportunities, particularly discovery to demo to proposal. Time-to-first-deal for new reps. Field adoption of enablement assets — measured, not assumed. Win/loss program running on cadence, with themes that visibly change product and GTM decisions. Message consistency: a quarterly audit across web, deck, product UI and content. What We Offer Remote-first environment Strong product/market fit: marketing data product for US-based enterprises 20 working days of PTO per year US holidays and additional days off Professional development reimbursement

Location: (Multiple States), Spain About Improvado Improvado is a marketing data and AI analytics platform for enterprise brands and agencies. We connect 500+ marketing and sales data sources, normalize them through a governed data model, and put an AI agent on top so marketing teams can ask questions of their own data without going through BI or IT. What we sell: extraction and 500+ connectors; data transformation (SQL and dbt-compatible); Marketing Data Governance — taxonomy, naming, data-quality rules; warehouse and storage; dashboards; AI agent and MCP access to live marketing data; DECS, data engineering as a service on a 2 to 4 week SLA. Who buys it: Economic buyers: CMO, VP Marketing, VP Demand Gen, agency COO and ops leadership Technical evaluators: VP or Director of Marketing Analytics, marketing analysts, data engineering, sometimes IT and security Segments: enterprise brands, mid-market, agencies Verticals: pharma and healthcare, financial services, retail and eCommerce, gaming, agencies Why this role, now Our messaging is not aligned. Positioning, web, sales pitch, product and content each carry a different version of what Improvado is. The market categorizes us as "marketing ETL" while we position as an AI marketing analytics platform. That gap costs us deal quality and price. The category is crowded and moving fast. Battlecards exist but decay, and nobody owns keeping them true. Attribution, incrementality and causal measurement is where deals are won and lost — and it is the hardest thing to argue credibly without hand-waving. Analyst firms are a silent blocker. When an enterprise buyer asks Gartner or Forrester about Improvado, there is no briefed narrative waiting for them. You would not start from a blank page. We already have a positioning registry, roughly 11 documented buyer personas, a pain-point and value-prop library, competitor intel reports and about 10 battlecards. They are inconsistent and under-used. Your first job is to make one version true and make people use it. What you'll own Positioning and messaging. Core positioning, category framing and message hierarchy across ICPs and personas. ICP and persona documentation that is used, not filed. The messaging layer of new product and feature launches, including the internal rollout that makes the field able to sell it. Competitive intelligence and win/loss. A structured win/loss interview program with quarterly readouts. Living battlecards. Monitoring competitor positioning, pricing and product moves, and driving our counter-positioning. Sales enablement. The core pitch narrative, demo storyline and objection-handling framework. The messaging components of new-rep onboarding. A standing weekly cadence with Sales leadership — not quarterly check-ins. Direct support on competitive and enterprise deals: RFPs, security and technical evaluations, displacement plays. Market and analyst relations. The Improvado narrative for Gartner, Forrester and category influencers, so that a buyer's analyst call becomes an accelerator rather than a blocker. Feeding structured market and buyer insight back into product prioritization. What we're looking for 4 to 8 years in product marketing, or an equivalent blend of product marketing with marketing analytics, marketing or data ops, sales engineering, analytics consulting, or product management on a data product. Category fluency in marketing data and measurement: attribution models, incrementality testing, MMM, data governance and taxonomy, warehouses and ETL/ELT — including where each is honestly weak. B2B SaaS sold to marketing or data buyers. Marketing analytics, martech, measurement, CDP, BI and data-infrastructure vendors are the reference profile. Proof you have shipped, not just documented: positioning that changed the website and the pitch, battlecards reps actually opened, a win/loss program that survived past its second quarter. Writing that survives contact with a skeptical technical buyer — claim and evidence, not adjective stacking. Comfort operating close to Sales: weekly cadence, deal reviews, live calls, direct feedback. Nice to have: hands-on SQL, dbt or BI, enough to validate a claim yourself. Experience marketing AI capabilities without hype. Analyst-relations experience. Agency-side or enterprise-brand background. Vertical depth in pharma and healthcare, financial services, retail and eCommerce, or gaming. Not a fit if: your product marketing has been mostly launch logistics and content calendars; you need a fully staffed team and a finished brand system to be effective; you are uncomfortable being told in a deal review that your messaging did not work. How we measure success Win rate in competitive deals against our top 3 named competitors, baseline set in month 1. Stage-to-stage conversion on open opportunities, particularly discovery to demo to proposal. Time-to-first-deal for new reps. Field adoption of enablement assets — measured, not assumed. Win/loss program running on cadence, with themes that visibly change product and GTM decisions. Message consistency: a quarterly audit across web, deck, product UI and content. What We Offer Remote-first environment Strong product/market fit: marketing data product for US-based enterprises 20 working days of PTO per year US holidays and additional days off Professional development reimbursement

Location: (Multiple States), Portugal About Improvado Improvado is a marketing data and AI analytics platform for enterprise brands and agencies. We connect 500+ marketing and sales data sources, normalize them through a governed data model, and put an AI agent on top so marketing teams can ask questions of their own data without going through BI or IT. What we sell: extraction and 500+ connectors; data transformation (SQL and dbt-compatible); Marketing Data Governance — taxonomy, naming, data-quality rules; warehouse and storage; dashboards; AI agent and MCP access to live marketing data; DECS, data engineering as a service on a 2 to 4 week SLA. Who buys it: Economic buyers: CMO, VP Marketing, VP Demand Gen, agency COO and ops leadership Technical evaluators: VP or Director of Marketing Analytics, marketing analysts, data engineering, sometimes IT and security Segments: enterprise brands, mid-market, agencies Verticals: pharma and healthcare, financial services, retail and eCommerce, gaming, agencies Why this role, now Our messaging is not aligned. Positioning, web, sales pitch, product and content each carry a different version of what Improvado is. The market categorizes us as "marketing ETL" while we position as an AI marketing analytics platform. That gap costs us deal quality and price. The category is crowded and moving fast. Battlecards exist but decay, and nobody owns keeping them true. Attribution, incrementality and causal measurement is where deals are won and lost — and it is the hardest thing to argue credibly without hand-waving. Analyst firms are a silent blocker. When an enterprise buyer asks Gartner or Forrester about Improvado, there is no briefed narrative waiting for them. You would not start from a blank page. We already have a positioning registry, roughly 11 documented buyer personas, a pain-point and value-prop library, competitor intel reports and about 10 battlecards. They are inconsistent and under-used. Your first job is to make one version true and make people use it. What you'll own Positioning and messaging. Core positioning, category framing and message hierarchy across ICPs and personas. ICP and persona documentation that is used, not filed. The messaging layer of new product and feature launches, including the internal rollout that makes the field able to sell it. Competitive intelligence and win/loss. A structured win/loss interview program with quarterly readouts. Living battlecards. Monitoring competitor positioning, pricing and product moves, and driving our counter-positioning. Sales enablement. The core pitch narrative, demo storyline and objection-handling framework. The messaging components of new-rep onboarding. A standing weekly cadence with Sales leadership — not quarterly check-ins. Direct support on competitive and enterprise deals: RFPs, security and technical evaluations, displacement plays. Market and analyst relations. The Improvado narrative for Gartner, Forrester and category influencers, so that a buyer's analyst call becomes an accelerator rather than a blocker. Feeding structured market and buyer insight back into product prioritization. What we're looking for 4 to 8 years in product marketing, or an equivalent blend of product marketing with marketing analytics, marketing or data ops, sales engineering, analytics consulting, or product management on a data product. Category fluency in marketing data and measurement: attribution models, incrementality testing, MMM, data governance and taxonomy, warehouses and ETL/ELT — including where each is honestly weak. B2B SaaS sold to marketing or data buyers. Marketing analytics, martech, measurement, CDP, BI and data-infrastructure vendors are the reference profile. Proof you have shipped, not just documented: positioning that changed the website and the pitch, battlecards reps actually opened, a win/loss program that survived past its second quarter. Writing that survives contact with a skeptical technical buyer — claim and evidence, not adjective stacking. Comfort operating close to Sales: weekly cadence, deal reviews, live calls, direct feedback. Nice to have: hands-on SQL, dbt or BI, enough to validate a claim yourself. Experience marketing AI capabilities without hype. Analyst-relations experience. Agency-side or enterprise-brand background. Vertical depth in pharma and healthcare, financial services, retail and eCommerce, or gaming. Not a fit if: your product marketing has been mostly launch logistics and content calendars; you need a fully staffed team and a finished brand system to be effective; you are uncomfortable being told in a deal review that your messaging did not work. How we measure success Win rate in competitive deals against our top 3 named competitors, baseline set in month 1. Stage-to-stage conversion on open opportunities, particularly discovery to demo to proposal. Time-to-first-deal for new reps. Field adoption of enablement assets — measured, not assumed. Win/loss program running on cadence, with themes that visibly change product and GTM decisions. Message consistency: a quarterly audit across web, deck, product UI and content. What We Offer Remote-first environment Strong product/market fit: marketing data product for US-based enterprises 20 working days of PTO per year US holidays and additional days off Professional development reimbursement

Location: (Multiple States), Netherlands About Improvado Improvado is a marketing data and AI analytics platform for enterprise brands and agencies. We connect 500+ marketing and sales data sources, normalize them through a governed data model, and put an AI agent on top so marketing teams can ask questions of their own data without going through BI or IT. What we sell: extraction and 500+ connectors; data transformation (SQL and dbt-compatible); Marketing Data Governance — taxonomy, naming, data-quality rules; warehouse and storage; dashboards; AI agent and MCP access to live marketing data; DECS, data engineering as a service on a 2 to 4 week SLA. Who buys it: Economic buyers: CMO, VP Marketing, VP Demand Gen, agency COO and ops leadership Technical evaluators: VP or Director of Marketing Analytics, marketing analysts, data engineering, sometimes IT and security Segments: enterprise brands, mid-market, agencies Verticals: pharma and healthcare, financial services, retail and eCommerce, gaming, agencies Why this role, now Our messaging is not aligned. Positioning, web, sales pitch, product and content each carry a different version of what Improvado is. The market categorizes us as "marketing ETL" while we position as an AI marketing analytics platform. That gap costs us deal quality and price. The category is crowded and moving fast. Battlecards exist but decay, and nobody owns keeping them true. Attribution, incrementality and causal measurement is where deals are won and lost — and it is the hardest thing to argue credibly without hand-waving. Analyst firms are a silent blocker. When an enterprise buyer asks Gartner or Forrester about Improvado, there is no briefed narrative waiting for them. You would not start from a blank page. We already have a positioning registry, roughly 11 documented buyer personas, a pain-point and value-prop library, competitor intel reports and about 10 battlecards. They are inconsistent and under-used. Your first job is to make one version true and make people use it. What you'll own Positioning and messaging. Core positioning, category framing and message hierarchy across ICPs and personas. ICP and persona documentation that is used, not filed. The messaging layer of new product and feature launches, including the internal rollout that makes the field able to sell it. Competitive intelligence and win/loss. A structured win/loss interview program with quarterly readouts. Living battlecards. Monitoring competitor positioning, pricing and product moves, and driving our counter-positioning. Sales enablement. The core pitch narrative, demo storyline and objection-handling framework. The messaging components of new-rep onboarding. A standing weekly cadence with Sales leadership — not quarterly check-ins. Direct support on competitive and enterprise deals: RFPs, security and technical evaluations, displacement plays. Market and analyst relations. The Improvado narrative for Gartner, Forrester and category influencers, so that a buyer's analyst call becomes an accelerator rather than a blocker. Feeding structured market and buyer insight back into product prioritization. What we're looking for 4 to 8 years in product marketing, or an equivalent blend of product marketing with marketing analytics, marketing or data ops, sales engineering, analytics consulting, or product management on a data product. Category fluency in marketing data and measurement: attribution models, incrementality testing, MMM, data governance and taxonomy, warehouses and ETL/ELT — including where each is honestly weak. B2B SaaS sold to marketing or data buyers. Marketing analytics, martech, measurement, CDP, BI and data-infrastructure vendors are the reference profile. Proof you have shipped, not just documented: positioning that changed the website and the pitch, battlecards reps actually opened, a win/loss program that survived past its second quarter. Writing that survives contact with a skeptical technical buyer — claim and evidence, not adjective stacking. Comfort operating close to Sales: weekly cadence, deal reviews, live calls, direct feedback. Nice to have: hands-on SQL, dbt or BI, enough to validate a claim yourself. Experience marketing AI capabilities without hype. Analyst-relations experience. Agency-side or enterprise-brand background. Vertical depth in pharma and healthcare, financial services, retail and eCommerce, or gaming. Not a fit if: your product marketing has been mostly launch logistics and content calendars; you need a fully staffed team and a finished brand system to be effective; you are uncomfortable being told in a deal review that your messaging did not work. How we measure success Win rate in competitive deals against our top 3 named competitors, baseline set in month 1. Stage-to-stage conversion on open opportunities, particularly discovery to demo to proposal. Time-to-first-deal for new reps. Field adoption of enablement assets — measured, not assumed. Win/loss program running on cadence, with themes that visibly change product and GTM decisions. Message consistency: a quarterly audit across web, deck, product UI and content. What We Offer Remote-first environment Strong product/market fit: marketing data product for US-based enterprises 20 working days of PTO per year US holidays and additional days off Professional development reimbursement

Location: Poland Workplace: remote Creatio is an AI CRM and workflow platform where people and AI agents work together — with no limits on users, agents, or scale. We help midsize and large organizations run customer workflows in the AI era. With a global team and a large ecosystem of partners, Creatio serves thousands of customers in over 100 countries and automates tens of millions of workflows daily. Genuine care for our clients and partners is at the heart of our DNA.We’re proud to be recognized by top industry analysts as a Leader and Strong Performer in multiple Gartner and Forrester reports. In 2025, Creatio was named to Inc.’s Best Workplaces list, recognizing our commitment to employee wellbeing and a strong workplace culture.Who We’re Looking For:We are looking for an experienced AI Tech Lead with a strong .NET engineering background and hands-on expertise in building production-grade AI solutions.In this role, you will lead the technical direction of an AI engineering team responsible for designing, developing, and operating intelligent capabilities within the Creatio platform.You will work on the AI agent platform that enables AI agents to safely perform real work within enterprise workflows — interacting with tools and APIs, accessing business data, maintaining context and memory, enforcing permissions, and collaborating with humans when needed.This is a hands-on technical leadership role that combines software architecture, advanced AI engineering, team mentorship, and active involvement in development.We are looking for someone who can make architectural decisions, solve complex engineering challenges, introduce modern AI development practices, and help the team deliver reliable, secure, and scalable AI-powered solutions.Responsibilities:Lead the development of architectural solutions, including AI-powered features, agentic workflows, RAG-based solutions, and LLM integrations.Drive continuous optimization of development processes; introduce modern tools, AI-assisted development practices, engineering standards, and quality improvements.Facilitate team ceremonies: backlog refinements, sprint planning, and sprint reviews (demos).Take an active part in backlog execution: pair programming, complex development, code reviews, and mentoring.Collaborate closely with stakeholders and product managers to define technical direction and translate business requirements into technical solutions.Guide the design and implementation of AI agent architectures, including tool calling, orchestration, context and memory management, permissions, and guardrails.Ensure high quality through automated testing, AI evaluations, observability, and continuous monitoring of production AI solutions.Monitor and guide incident response (4th-line support), ensuring SLA compliance and issue resolution.Actively contribute to knowledge sharing, team development, and continuous improvement.Requirements: Must have:6+ years of professional software engineering experience, with strong expertise in C# and .NET.3+ years of experience in a Tech Lead or Team Lead role, including architectural decision-making, technical ownership, and mentoring.Hands-on experience building and delivering LLM-powered applications to production.Strong understanding of AI agent architectures, including tool calling, orchestration, context management, and agent frameworks.Knowledge of prompt engineering, AI evaluations, observability, and AI security best practices.Proficiency with AI coding agents (Claude Code, Cursor, Codex, or similar tools) in daily development.Strong knowledge of software architecture, distributed systems, REST APIs, and backend engineering principles.Experience with relational databases, automated testing, CI/CD, and cloud-native development.English level: Upper-Intermediate or higher, with strong communication, leadership, and problem-solving skills.Nice to have:Experience with MCP, multi-agent systems, and advanced agent orchestration.Practical experience with RAG, embeddings, vector/hybrid search, and LLM integrations.Knowledge of LLMOps practices, including evaluation pipelines, monitoring, and cost optimization.Experience with AI platforms such as Anthropic API, Azure OpenAI, AWS Bedrock, or Google Vertex AI.Python experience for AI development, prototyping, or automation.Experience with Kubernetes, enterprise SaaS products, or low-code/no-code platforms.What to expect from us:Growth & Development: Clear career paths, mentorship opportunities, and access to continuous learning to help you reach your full potential.Flexibility & Well-Being: We provide flexible work arrangements and initiatives that empower you to manage your schedule effectively, stay productive, and thrive both personally and professionally.Recognition & Impact: A culture that celebrates achievements, values your ideas, and empowers you to make real contributions from day one.Innovative Culture: Be part of a company that embraces new ideas, modern technologies, and bold thinking to stay ahead of the curve.Benefits & Rewards Package: We provide competitive compensation and benefits designed to support you and your family. Our rewards approach goes beyond salary, recognizing your contributions and commitment. The exact package may vary depending on your country of residence and employment type.

Location: In-Office 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. Locations: Austin, Lisbon, San Francisco, NYC, or London About the Role Search is being rebuilt around AI. People increasingly get answers from AI instead of a list of links, agents run dozens of searches to answer a single question, and more than half of the traffic reaching sites on Cloudflare is now automated . Search is shifting from a destination to a utility, and Cloudflare is building the search layer for this agentic Internet. Agentic Search at Cloudflare gives agents everything they need to find information, whether it lives in a customer’s own data or on the open web. It spans two products: AI Search for internal data, and Web Search API for the open web. AI Search (internal data), now generally available , is the search primitive for applications and agents . It is a fully managed indexing and retrieval pipeline built on Workers AI , Vectorize , R2 , and Browser Run . Developers connect a website or R2 bucket, or upload their own files, and query them with natural language through a Workers binding, REST API, or MCP server. Under the hood: continuous indexing, hybrid vector and keyword retrieval, reranking, metadata filtering, native multimodal (image) embeddings, and OCR for scanned documents. We use it to power search on our own blog and developer docs. Web Search API (external data), now in open beta , gives agents real-time web context with a single API call. It runs on AI Gateway , so every search gets the same logging, analytics, billing, and access controls as model inference. Developers can choose from multiple search providers and always get results back in one normalized format. Your mission in this role is to make Cloudflare the default place developers and agents go to search, across both their own data and the open web, and eventually in a single call. You’ll also help build a search ecosystem that works for AI companies, site owners, and creators alike. What You’ll Do Talk directly with developers, AI companies, publishers, and customers every day. Own the strategy, roadmap, and execution for Agentic Search (AI Search and Web Search API), from ingestion and indexing through retrieval, ranking, and answer generation. Define and measure what “good search” means, including relevance, freshness, latency, and cost, and build the evals that improve it with every release. Scale AI Search for the workloads that matter most, like multi-tenant platforms, enterprise agents, and website search, with support for billions of documents, rich media, and built-in observability. Take Web Search API and shape what comes next: provider partnerships, search and page extraction in one call, blending web and private data, Own pricing and packaging, and make our products first-class for agents through MCP, agent-friendly APIs, and templates like NLWeb . Partner with engineering, ML, and product teams across Workers AI , Vectorize , AI Gateway , Browser Run , and AI Crawl Control , as well as Marketing, DevRel, BD, Sales, and Support. Represent Cloudflare at conferences, community events, and customer and partner meetings. Examples of Desirable Skills, Knowledge, and Experience Proven experience as a PM, EM, or founder shipping search, information retrieval, data infrastructure, or developer platform products. You’ve led teams to ship before and can point to impact. Deep understanding of how search works end to end: crawling, indexing, chunking, embeddings, hybrid retrieval (BM25 + vector), query rewriting, reranking, and retrieval-augmented generation (RAG). You understand the tradeoffs between relevance, freshness, latency, and cost. Experience defining and measuring search quality, including offline evals, relevance judgments, metrics like recall, MRR, and NDCG, and online experimentation. Fluency in the modern AI ecosystem: LLMs, text and multimodal embedding models, agents, tool calling, and MCP. You’ve built with them yourself and know where they break. Hands-on ability to write code and use AI and the Internet to learn new things fast. You’ve built a RAG pipeline or an agent that searches the web, and you have opinions about what made it good or bad. Deep empathy for developers and understanding of their workflows, pain points, and how they adopt new tools and platforms. Understanding of the web publishing ecosystem: crawlers, bots, SEO and answer engine optimization (AEO), and the changing economics of AI search for content creators. Comfortable working where technology, business, and policy meet. Experience with usage-based pricing, two-sided marketplaces, or partner and business development relationships, including build-vs-partner decisions, is a plus. Exceptional communication and collaboration skills. You can translate between ML research, infrastructure engineering, and business stakeholders, and align diverse teams on goals. Passion for design details and polish. You raise the bar for sweating the details. External presentation skills. You can walk into a room of developers or AI company leaders and build trust and credibility. Compensation Compensation may be adjusted depending on work location. For Seattle/NYC/California based hires - Estimated annual salary of: $172,000 - $215,000 For SF/Bay Area based hires - Estimated annual salary of: $179,000 - $224,000 For Lisbon based hires - Estimated annual salary of: €68,000 - €85,000 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.

Location: Remote, USA Workplace: remote At PointClickCare our mission is simple: to help providers deliver exceptional care. And that starts with our people. As a leading health tech company that’s founder-led and privately held, we empower our employees to push boundaries, innovate, and shape the future of healthcare.   With the largest long-term and post-acute care dataset and a Marketplace of 400+ integrated partners, our platform serves over 30,000 provider organizations, making a real difference in millions of lives. We also reinvest a significant percentage of our revenue back into research and development, ensuring our employees have the resources to innovate and make a lasting impact. Recognized by Forbes as a top private cloud company and honored as one of Canada’s Most Admired Corporate Cultures, we offer flexibility, growth opportunities, and meaningful work.    At PointClickCare, we empower our people to be the architects of a smarter healthcare future; one that is human-first and accelerated by AI to create meaningful and lasting change. Employees harness AI as a catalyst for creativity, productivity, and thoughtful decision-making. By integrating AI tools into our daily workflows, collaboration is enhanced, outcomes are improved, and every team member has the proficiency to maximize their impact. It all starts with our hiring practices where we uncover AI expertise that complements our mission, and we continue to invest in training and development to nurture innovation throughout the employee journey.   Join us in redefining healthcare — so it doesn’t just survive, it thrives. To learn more about PointClickCare, check out Life at PointClickCare and connect with us on Glassdoor and LinkedIn.     **Travel to Office expectations** For Remote Roles: If this role is remote, there will be in-office events that will require travel to and from the Mississauga and/or Salt Lake City office. These will include, but not limited to, onboarding, team events, semi-annual and annual team meetings.   For Hybrid Roles: If this role is Hybrid, there will be an expectation to reside within commutable distance to the office/location specified in the job listing. This will include, but not limited to, weekly/bi-weekly/monthly events in the office with your specific team. This is a requirement for this role. Team Summary: The AI Engineering team builds and operates AI Platform — the common foundation every engineering team uses to ship AI capabilities. The team delivers the shared infrastructure, reference patterns, and guardrails that let software engineers across the company build AI agents, MCP servers, and GenAI solutions without reinventing the foundations: model access, orchestration, evaluation, observability, and responsible AI controls. Working in close partnership with product and engineering teams, it turns proven patterns into platform capabilities that compound across the product portfolio. Job Summary: The Senior AI Architect is the senior technical leader for PointClickCare’s AI Platform, owning the architecture that enables software engineers across the company to build AI agents, MCP servers, and AI solutions on a common foundation. This role is an enabler, not a product owner: its output is a platform other teams build on, and the patterns, standards, and guardrails that make those teams faster. The Senior AI Architect works closely with product counterparts to review product roadmaps and translate them into architectural designs and decision documents and guides the AI Engineering team in building a robust, scalable agentic platform for the future of PointClickCare. Key responsibilities: Design and evolve the architecture of PointClickCare’s AI Platform — the agentic runtime, MCP integration layer, model gateway, and evaluation and observability services that engineering teams build on ensuring it scales with adoption across the product portfolio. Guide the AI Engineering team through architectural decisions, design reviews, and hands-on technical mentorship, raising the bar for how the platform is designed, built, and operated. Partner with product counterparts to review product roadmaps, translate upcoming AI capabilities into architectural requirements, and author architecture documents and decision records that de-risk delivery Enable software engineers across PointClickCare to build AI agents, MCP servers, and solutions on the platform by codifying reference architectures, reusable patterns, and paved-road templates — and by providing direct architectural guidance to consuming teams. Establish platform standards for security, responsible AI, evaluation, and observability, and run architectural review processes that keep solutions built on the platform consistent, compliant, and production-ready. Minimum qualifications and Skills: 12+ years of software engineering and platform architecture experience with deep cloud expertise (Azure preferred), including 5+ years focused on AI/ML infrastructure and GenAI solutions at scale Hands-on expertise with agentic systems — agent frameworks, multi-agent orchestration, MCP (Model Context Protocol), tool use, RAG, vector databases, and production LLMOps Proven track record designing internal platforms that other engineering teams build on, including developer experience, APIs and SDKs, and self-serve patterns Strong architectural breadth across cloud-native systems, distributed systems, data platforms, and security architecture Demonstrated ability to produce high-quality architecture documents and decision records, and to communicate design trade-offs clearly to engineering and product audiences Preferred qualifications and skills: Experience with the Azure AI stack (Azure OpenAI, AKS, APIM) and the Databricks lakehouse (Unity Catalog, model serving) Background in healthcare technology platforms or clinical workflows Experience guiding engineering teams as a senior architect or technical lead within a platform organization Expertise in advanced agentic patterns including multi-agent orchestration, tool and MCP server design, agent evaluation, and model fine-tuning pipelines Deep knowledge of AI governance, responsible AI practices, and model risk management in regulated environments   #LI-Av1 #LI-remote PointClickCare Benefits & Perks:   Benefits starting from Day 1! Retirement Plan Matching Flexible Paid Time Off Wellness Support Programs and Resources Parental & Caregiver Leaves Fertility & Adoption Support Continuous Development Support Program Employee Assistance Program Allyship and Inclusion Communities Employee Recognition … and more!   It is the policy of PointClickCare to ensure equal employment opportunity without discrimination or harassment on the basis of race, religion, national origin, status, age, sex, sexual orientation, gender identity or expression, marital or domestic/civil partnership status, disability, veteran status, genetic information, or any other basis protected by law. PointClickCare welcomes and encourages applications from people with disabilities. Accommodations are available upon request for candidates taking part in all aspects of the selection process. Please contact recruitment@pointclickcare.com should you require any accommodations. As part of our commitment to a streamlined and equitable hiring experience, PointClickCare uses AI tools to assist with candidate screening and assessment.   When you apply for a position, your information is processed and stored with Lever, in accordance with Lever’s Privacy Policy. We use this information to evaluate your candidacy for the posted position. We also store this information, and may use it in relation to future positions to which you apply, or which we believe may be relevant to you given your background. When we have no ongoing legitimate business need to process your information, we will either delete or anonymize it.  If you have any questions about how PointClickCare uses or processes your information, or if you would like to ask to access, correct, or delete your information, please contact PointClickCare’s human resources team: recruitment@pointclickcare.com    PointClickCare is committed to Information Security. By applying to this position, if hired, you commit to following our information security policies and procedures and making every effort to secure confidential and/or sensitive information. At PointClickCare, base salary is one of the many components that make up our total rewards package. The US base salary range for this position is $183,000-$229,000 (not overtime eligible) + bonus + benefits. Compensation is assessed individually and aligned to experience, skills, and market context. The posted range reflects typical expectations for this role.

Location: Remote or Mississauga Workplace: remote At PointClickCare our mission is simple: to help providers deliver exceptional care. And that starts with our people. As a leading health tech company that’s founder-led and privately held, we empower our employees to push boundaries, innovate, and shape the future of healthcare.   With the largest long-term and post-acute care dataset and a Marketplace of 400+ integrated partners, our platform serves over 30,000 provider organizations, making a real difference in millions of lives. We also reinvest a significant percentage of our revenue back into research and development, ensuring our employees have the resources to innovate and make a lasting impact. Recognized by Forbes as a top private cloud company and honored as one of Canada’s Most Admired Corporate Cultures, we offer flexibility, growth opportunities, and meaningful work.    At PointClickCare, we empower our people to be the architects of a smarter healthcare future; one that is human-first and accelerated by AI to create meaningful and lasting change. Employees harness AI as a catalyst for creativity, productivity, and thoughtful decision-making. By integrating AI tools into our daily workflows, collaboration is enhanced, outcomes are improved, and every team member has the proficiency to maximize their impact. It all starts with our hiring practices where we uncover AI expertise that complements our mission, and we continue to invest in training and development to nurture innovation throughout the employee journey.   Join us in redefining healthcare — so it doesn’t just survive, it thrives. To learn more about PointClickCare, check out Life at PointClickCare and connect with us on Glassdoor and LinkedIn.     **Travel to Office expectations** For Remote Roles: If this role is remote, there will be in-office events that will require travel to and from the Mississauga and/or Salt Lake City office. These will include, but not limited to, onboarding, team events, semi-annual and annual team meetings.   For Hybrid Roles: If this role is Hybrid, there will be an expectation to reside within commutable distance to the office/location specified in the job listing. This will include, but not limited to, weekly/bi-weekly/monthly events in the office with your specific team. This is a requirement for this role. Team Summary: The AI Engineering team builds and operates AI Platform — the common foundation every engineering team uses to ship AI capabilities. The team delivers the shared infrastructure, reference patterns, and guardrails that let software engineers across the company build AI agents, MCP servers, and GenAI solutions without reinventing the foundations: model access, orchestration, evaluation, observability, and responsible AI controls. Working in close partnership with product and engineering teams, it turns proven patterns into platform capabilities that compound across the product portfolio. Job Summary: The Senior AI Architect is the senior technical leader for PointClickCare’s AI Platform, owning the architecture that enables software engineers across the company to build AI agents, MCP servers, and AI solutions on a common foundation. This role is an enabler, not a product owner: its output is a platform other teams build on, and the patterns, standards, and guardrails that make those teams faster. The Senior AI Architect works closely with product counterparts to review product roadmaps and translate them into architectural designs and decision documents and guides the AI Engineering team in building a robust, scalable agentic platform for the future of PointClickCare. Key responsibilities: Design and evolve the architecture of PointClickCare’s AI Platform — the agentic runtime, MCP integration layer, model gateway, and evaluation and observability services that engineering teams build on ensuring it scales with adoption across the product portfolio. Guide the AI Engineering team through architectural decisions, design reviews, and hands-on technical mentorship, raising the bar for how the platform is designed, built, and operated. Partner with product counterparts to review product roadmaps, translate upcoming AI capabilities into architectural requirements, and author architecture documents and decision records that de-risk delivery Enable software engineers across PointClickCare to build AI agents, MCP servers, and solutions on the platform by codifying reference architectures, reusable patterns, and paved-road templates — and by providing direct architectural guidance to consuming teams. Establish platform standards for security, responsible AI, evaluation, and observability, and run architectural review processes that keep solutions built on the platform consistent, compliant, and production-ready. Minimum qualifications and Skills: 12+ years of software engineering and platform architecture experience with deep cloud expertise (Azure preferred), including 5+ years focused on AI/ML infrastructure and GenAI solutions at scale Hands-on expertise with agentic systems — agent frameworks, multi-agent orchestration, MCP (Model Context Protocol), tool use, RAG, vector databases, and production LLMOps Proven track record designing internal platforms that other engineering teams build on, including developer experience, APIs and SDKs, and self-serve patterns Strong architectural breadth across cloud-native systems, distributed systems, data platforms, and security architecture Demonstrated ability to produce high-quality architecture documents and decision records, and to communicate design trade-offs clearly to engineering and product audiences Preferred qualifications and skills: Experience with the Azure AI stack (Azure OpenAI, AKS, APIM) and the Databricks lakehouse (Unity Catalog, model serving) Background in healthcare technology platforms or clinical workflows Experience guiding engineering teams as a senior architect or technical lead within a platform organization Expertise in advanced agentic patterns including multi-agent orchestration, tool and MCP server design, agent evaluation, and model fine-tuning pipelines Deep knowledge of AI governance, responsible AI practices, and model risk management in regulated environments   #LI-AV1 #LI-remote PointClickCare Benefits & Perks:   Benefits starting from Day 1! Retirement Plan Matching Flexible Paid Time Off Wellness Support Programs and Resources Parental & Caregiver Leaves Fertility & Adoption Support Continuous Development Support Program Employee Assistance Program Allyship and Inclusion Communities Employee Recognition … and more!   It is the policy of PointClickCare to ensure equal employment opportunity without discrimination or harassment on the basis of race, religion, national origin, status, age, sex, sexual orientation, gender identity or expression, marital or domestic/civil partnership status, disability, veteran status, genetic information, or any other basis protected by law. PointClickCare welcomes and encourages applications from people with disabilities. Accommodations are available upon request for candidates taking part in all aspects of the selection process. Please contact recruitment@pointclickcare.com should you require any accommodations. As part of our commitment to a streamlined and equitable hiring experience, PointClickCare uses AI tools to assist with candidate screening and assessment.   When you apply for a position, your information is processed and stored with Lever, in accordance with Lever’s Privacy Policy. We use this information to evaluate your candidacy for the posted position. We also store this information, and may use it in relation to future positions to which you apply, or which we believe may be relevant to you given your background. When we have no ongoing legitimate business need to process your information, we will either delete or anonymize it.  If you have any questions about how PointClickCare uses or processes your information, or if you would like to ask to access, correct, or delete your information, please contact PointClickCare’s human resources team: recruitment@pointclickcare.com    PointClickCare is committed to Information Security. By applying to this position, if hired, you commit to following our information security policies and procedures and making every effort to secure confidential and/or sensitive information. At PointClickCare, base salary is one of the many components that make up our total rewards package. The CAD base salary range for this position is $161,000-$201,000 (not overtime eligible) + bonus + benefits. Compensation is assessed individually and aligned to experience, skills, and market context. The posted range reflects typical expectations for this role.

Location: Bellevue Workplace: OnSite LIFE AT UIPATH The people at UiPath believe in the transformative power of automation to change how the world works. We’re committed to creating category-leading enterprise software that unleashes that power. To make that happen, we need people who are curious, self-propelled, generous, and genuine. People who love being part of a fast-moving, fast-thinking growth company. And people who care—about each other, about UiPath, and about our larger purpose. Could that be you? YOUR MISSION We're seeking a Principal Product Manager to join our Governance team. You'll drive product direction across human, robot, and agent identity, delegated and scoped authorization, guardrails, and audit and attribution for non-human actors, and you'll work the patterns the industry is still standardizing right now: on-behalf-of delegation chains, OAuth flows for autonomous callers, just-in-time elevation, sandboxing, and policy-as-code for tool access. This is a high-agency, AI-native role. You will be deep in the product: testing, prototyping with coding agents, talking to customers, and turning what you learn into a coherent roadmap to build. Your north star is an agentic enterprise’ trust translating into adoption: governance with required coverage, and monitoring, for enterprises; and frictionless for builders to code it in. WHAT YOU'LL DO AT UIPATH - Own the 12–18 months roadmap for identity, auth, and access governance across UiPath's agentic platform, in coherence with company priorities and evolving standards in the ecoystem. - Evolve how identity works for agents, robots, and humans at UiPath (provisioning, scoping, delegation, attestation), ship the patterns, and drive their adoption across the product teams that build on them. - Drive the auth model for LLM tool-calling (for internal and external agents), enterprise-managed authorization, scoped consent, least-privilege execution, step-up and just-in-time elevation, and OOTB monitoring views, audit trails that hold up in front of a compliance team. - Enhance the guardrail layer around agent action: policy-as-code for tool access, sandboxing boundaries, approval and elevation flows, and the attribution model that answers "which agent, on whose behalf, under which policy" after the fact. - Define how UiPath agents present themselves to the outside world and how outside agents present themselves to UiPath: agent identities registered in enterprise directories, on-behalf-of delegation chains that survive multiple hops, and agent-to-agent trust. - Partner with our largest and most regulated customers (financial services, healthcare, public sector) on production deployments. Go deep enough to know which specific control failed and ship the fix. - Use the platform as a builder. Stand up agents, wire up auth flows, use coding agents aggressively to prototype and ship reference implementations. - Instrument and own the metrics that matter (e.g. time-to-grant, audit coverage, policy violations caught, developer friction) and prioritize against them. - Present UiPath's governance capabilities and roadmap to customers, partners, and consider authoring any external content that earns CISO trust. WHAT YOU'LL BRING TO THE TEAM - 7+ years in technical PM or engineering roles, with sustained time in the governance space: identity, access, and guardrails for enterprise software. You have shipped infrastructure that enterprises trusted with production traffic. - A visible record of innovating in agentic governance specifically: owned capabilities, reference implementations, spec or working-group contributions. - Fluency in enterprise identity and access: how users, services, and now agents authenticate, what they're allowed to do, and how actions get audited. - Working knowledge of the agent auth stack as it stands today: MCP authorization, on-behalf-of delegation, and how IdPs like Okta and Entra now model agents as identities. - Working understanding of agentic AI (tool-calling, MCP, RAG, agent design patterns) and a view on how identity, access, and guardrails should evolve to support autonomous actors. - First-principles thinker, comfortable in ambiguity. Can produce a defensible direction and can tell the difference between a problem the standards will solve for us. - Clear communicator, in writing and in person: you can write a short position doc that frames a decision, explain a concept well to a CISO or auditor, and walk a customer through a working demo without overselling it. IDEAL BACKGROUND - Several years in identity, access, or security-platform product work in enterprise vendors - hyperscaler identity team, IAM vendors, workload-identity or secrets vendor, or as an early PM at a startup in the space, with focus on agents. - Has been working on the enterprise agentic governance problem for a while: a product or feature in market, a spec or working-group contribution. - Has opinions about where agent identity, access, and guardrails are going in the next 24 months, with receipts. - Has shipped into regulated industries (financial services, healthcare, public sector) and has sat through a customer security or compliance review to shape product roadmap. - Works closely with engineering and field teams and is trusted by both to make technical trade-offs without a committee. - Prototypes before writing: has used code or coding agents to test an idea and brought the working version to the discussion. #LI-MH1 Maybe you don’t tick all the boxes above—but still think you’d be great for the job? Go ahead, apply anyway. Please. Because we know that experience comes in all shapes and sizes—and passion can’t be learned. Many of our roles allow for flexibility in when and where work gets done. Depending on the needs of the business and the role, the number of hybrid, office-based, and remote workers will vary from team to team. Applications are assessed on a rolling basis and there is no fixed deadline for this requisition. The application window may change depending on the volume of applications received or may close immediately if a qualified candidate is selected. We value a range of diverse backgrounds, experiences and ideas. We pride ourselves on our diversity and inclusive workplace that provides equal opportunities to all persons regardless of age, race, color, religion, sex, sexual orientation, gender identity, and expression, national origin, disability, neurodiversity, military and/or veteran status, or any other protected classes. Additionally, UiPath provides reasonable accommodations for candidates on request and respects applicants' privacy rights. To review these and other legal disclosures, visit our privacy policy https://www.uipath.com/legal/trust-and-security/privacy-policy.

Location: US - Remote Customers are no longer asking whether AI works—they’re asking what it will change about how they operate. As an AI Success Architect, you’ll help enterprise customers answer that question and turn Asana’s AI capabilities into measurable business results. You’ll own the post-sales relationship for a portfolio of ~50 enterprise accounts, acting as a strategic advisor with accountability for AI adoption, consumption, and commercial outcomes. In this advisory role, you’ll diagnose where AI changes how work gets done and guide the organizational change that makes it stick. This role can either be fully remote depending on which US state you live in, or based in our Chicago office with an office-centric hybrid schedule . If based in-office: The standard in-office days are Monday, Tuesday, and Thursday . Most Asanas have the option to work from home on Wednesdays . Working from home on Fridays depends on the type of work you do and the teams with which you partner . If you're interviewing for this role, your recruiter will share more about the in-office requirements . What you’ll achieve Serve as the trusted advisor and point of accountability for a portfolio of enterprise accounts across the customer lifecycle. Build joint success plans that connect strategic customer goals to measurable results, leading business reviews focused on outcomes and value rather than just usage. Diagnose customer workflows and map them to Asana’s AI capabilities (AI Studio, AI Teammates, and integrations built on the Model Context Protocol, or MCP) to replace manual effort and accelerate decision-making. Assess how customers structure their work in Asana, guiding them to establish habits and governance that supply AI models with rich, consistent context. Lead change management and enablement programs that build internal champions and ensure long-term, sustained adoption. Track AI consumption and adoption against clear baselines and 30/60/90-day benchmarks, translating usage data into a compelling business story. Identify expansion readiness for new AI use cases, products, or broader deployments, initiating conversations and partnering with the account team once validated. Monitor account health, engagement, and sentiment to proactively mitigate risks well ahead of renewals. Partner cross-functionally with Solutions Engineering, Professional Services, and Sales, while sharing structured customer insights with Product and Customer Success leadership. About you Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making. 5+ years of experience in customer success, strategic account management, or enterprise technology, with a track record of driving delivery and adoption for complex, high-value accounts. Proven background managing enterprise relationships across both technical and business stakeholders. Solid understanding of how AI agents function, workflow automation principles, and where AI provides substantial versus incremental impact. Comfort discussing pricing, ROI, and commercial outcomes with senior executives, ideally within consumption-based models. Strong competency in change management and program management across concurrent, long-term initiatives. Effective communication skills across audiences, from executive presentations to tactical working sessions with operations teams. Ability to navigate fast-paced, ambiguous environments with sound judgment. Willingness to travel up to 20% to customer sites as needed. Expe rience with enterprise AI, automation, or workflow platforms (or familiarity with MCP) is a plus. At Asana, we're committed to building teams that include a variety of backgrounds, perspectives, and skills, as this is critical to helping us achieve our mission. If you're interested in this role and don't meet every listed requirement, we still encourage you to apply. What we’ll offer Our comprehens ive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission . We bel ieve that compensation should be reflective of the value you create relative to the market value of your role . To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit . For this role, the estimated base salary range is b etween $116,800 - $148,800 . The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process . The listed range above is a guideline, and the base salary range for this role may be modified . In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits . If you're interviewing for this role, spe ak with your recruiter to learn more about the total compensation and benefits for this role . We strive to provide equitable and competitive benefits packages that support our employees worldwide and include: Mental health, wellness & fi tness benefits Career coaching & support Inclusive family building benefits Long-term savings or retirement plans In-office culinary options to cater to your dietary preferences These are just some of the benefits we offer, and benefits may vary based on role, country, and local regulations . If you're interviewing for this role, speak with your recruiter to learn more about the total compensation and benefits for this role . #LI-Hybrid About us Asana is a leading platform for human + AI collaboration. Millions of teams around the world rely on Asana to achieve their most important goals, faster. Asana has been named to Fortune's Best Workplaces for 7+ years and recognized by Fast Company, Forbes, and Gartner for excellence in workplace culture and innovation. We offer an exceptional office-centric culture while adopting the best elements of hybrid models to ensure that every one of our global team members can work together effortlessly. With 13+ offices all over the world, we are always looking for individuals who care about building technology that drives positive change in the world and a culture where everyone feels that they belong. We believe in supporting people to do their best work and thrive. Our goal is to ensure that Asana upholds an environment where all people feel that they are respected and valued, whether they are applying for an open position or working at the company. We provide equal employment opportunities to all applicants without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by law. Join Asana’s Talent Network to stay up to date on job opportunities and life at Asana.

Location: Москва Мы - команда, создающая **комплексную систему противодействия мошенничеству** и обеспечивающая online/offline безопасность миллионов клиентов банка 24/7/365, предоставляя инструменты **собственной разработки** для: * Построения графа связей (позволяет проанализировать не только объекты и их свойства, но также их связи с другими объектами различных уровней и характеристик и применяется для получения дополнительных знаний об объекте за счет извлечения знаний о его окружении, выявления наиболее значимой информации, центров влияния, групп связанных объектов, цепочек) * Геопространственой аналитики: анализа локаций, построения маршрутов и тепловых карт * Выявления и анализа попыток мошенничества и иных отклонений * Портфеля технологичных сервисов накопления и обработки больших объемов данных со сложной структурой Мы находимся на передовой технологических инноваций, соединяя возможности ИИ, современные технологии и потребности общества. Наше направление AI-трансформации — это стратегическая инициатива по интеграции LLM-агентов и мультиагентных систем в собственную аналитическую платформу: * AI-решения для глубокого анализа данных * Набор AI Tools, дающих агентам доступ к инструментам и сервисам платформы * Собственная no-code/low-code платформа для оркестрации AI-агентов и автоматизации рабочих процессов * Интеграция с внутренними LLM-шлюзами и средами исполнения агентов * RAG-системы для работы с корпоративными базами знаний и методологиями Наш передовой технологический стек: * Storage - Hadoop, Cassandra, ClickHouse, Elasticsearch, FastGraph, PostgreSQL * Big Data Engineering- Scala, Spark, Flink * Backend - GO (GIN), Scala (ZIO), Kubernetes (OpenShift, DropApp) * Fronted - React, Redux (Redux ToolKit, RTK Query), Typescript, jest. Библиотеки: react-force-graph, leaflet * AI - Python (LangChain, LangGraph, Harness), GO (mcp-go), Typescript (no code platform), ai-coding (gigacode cli, claude, codex), RAG\\GraphRag (PostgreSQL, Elasticsearch, Qdrant) * QA - Java, TestNG, Selenium, Maven, Allure * DevOps - Docker, Helm, Jenkins Обязанности * Проектирование и анализ архитектуры технического решения совместно с командой разработки * Разработка и согласование концепции, проектной документации и технической документации, описание API, ведение документации в Confluence * Развитие направления мультиагентных решений обеспечивая полный цикл реализации * Проведение исследовательских работ и тестирование новых подходов и техник AI * Анализ источников данных, разработка моделей данных, логики алгоритмов и интеграций * Документирование и обеспечение соблюдения правил сбора, хранения и использования данных * Участие в полном цикле разработки и внедрения Требования * Умение быстро погружаться в исследуемую область и оперативно переключаться на новое направление * Навыки интеграции решений на основе ML/AI в реальные производственные системы * Опыт проектирования логической и физической моделей данных. Языки SQL: понимание работы ETL-инструментов, умение писать SQL-запросы различной сложности * Знание форматов JSON/XML и навыки проектирование REST API * Способность обрабатывать и структурировать большой объем сложной информации, доступно и наглядно ее презентовать * Сбор, анализ и документирование бизнес-требований, описание use case, генерация идей, проработка технических решений, интеграционных взаимодействий * Коммуникативные навыки, достаточные для выстраивания конструктивного взаимодействия со смежными подразделениями и внутри команды Будет плюсом * Понимание ключевых алгоритмов и подходов в AI/GenAI (LLM, vector search, NLP, context engineering и др.) * Понимание архитектуры AI/GenAI решений, LLM, RAG, BI и DataOps * Наличие опыта разработки собственных библиотек и инструментов для AI * Опыт успешного внедрения AI-решений, знание инструментов AI на рынке * Опыт программирования на любом языке и способность анализировать код * Владение инструментами Big Data (Hadoop, AirFlow, Spark, Kafka) * Понимание принципов работы NoSQL баз данных (Cassandra, ClickHouse, ElasticSearch, Qdrant, Neo4j) Условия * Комфортный современный офис (ст.м.Кутузовская) * ежегодный пересмотр зарплаты, годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * программа адаптации и помощь руководителя на старте * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * бесплатная подписка СберПрайм+, скидки на продукты компаний-партнеров * вознаграждение за рекомендацию друзей в команду Сбера.

Location: Paris, France Workplace: Hybrid We’re a team of experts pushing the limits of what’s possible, united by our common goal to unlock true freedom through digital ownership, making technology accessible for all. We believe in a world where users, creators and enterprises manage their value with ownership and freedom. Our curiosity drives us to innovate, empowering individuals on a global scale. We believe change is constant and our team moves forward as one, with a culture of problem-solving where every employee is empowered and supported to challenge tradition and create solutions. Our mission is simple: to make self-custody accessible and give people the keys to their own financial futures. If you want to make a true impact, we want you to join us at Ledger. At Ledger, we’re proud to be the global platform for digital assets and Web3, with over 20% of the world’s crypto assets secured through our Ledger devices. With our headquarters in Paris, and offices in Vierzon, Grenoble, Montpellier, London, Portland, Geneva, Zurich and Central Singapore, we have a team of around 600 professionals developing a variety of products and services to enable individuals and companies to securely buy, store, swap, grow and manage crypto assets – including the Ledger hardware wallets line with more than 7.5 millions units already sold in 200 countries. The team As a Product Analytics Engineer Intern, you will join the Product Analytics team supporting Ledger Wallet across Product, Business, and Growth/CRM teams. Reporting directly to the Product Data Analytics Manager, you will play a key role in ensuring tracking data quality, and scaling our analytics infrastructure to support company-wide data-driven decision-making. What you’ll be doing - Cross-Functional Collaboration: Work closely with Product Managers, Data Engineers, and Data Scientists to deliver insights and support Growth/CRM personalization pipelines. - Experimentation & A/B Testing: Specify and support A/B test setups, funnel evaluation, and advanced statistical analysis for product features. - AI Governance & Automation: Help establish governance, guardrails, and custom skills for users querying analytics platforms (Mixpanel, Snowflake MCP) via AI tools, and contribute to building end-to-end AI-assisted tracking workflows. - Tracking Quality & Investigations: Triage, investigate, and follow up on tracking issues to maintain data sanity. - Documentation & Enablement: Develop comprehensive documentation and data models (dbt/data mart) to empower stakeholders - Privacy & Compliance: Maintain standard privacy-aware constraints across all data modeling and analytics workflows. What we're looking for - Final-year student in Engineering, Computer Science, Data Science, or a related technical field seeking an end-of-studies internship. - Strong proficiency in SQL, Python scripting, and data modeling concepts. - Analytics engineering mindset with a focus on data quality, reliability, reproducibility, and documentation. - Understanding of A/B testing methodologies, statistical analysis, and funnel evaluation. - Familiarity with Product Analytics tools (e.g., Mixpanel, Amplitude) and data visualization tools is a strong plus - Hands-on experience or deep curiosity regarding AI agents and workflow automation is a strong plus. - Excellent written and verbal communication skills in English. - Interest in Web3, digital assets, and crypto is a plus. At Ledger, we are dedicated to continually investing in our employees which is why we offer more than just salaries; we provide comprehensive compensation packages that include a wide range of benefits. Here are some of the benefits you can look forward to: - Flexible work options - Our hybrid policy allows employees to work from home up to 3 times per week - Health & Wellness support - Health and Life Insurance. - Financial growth opportunities - Employees can become shareholders in Ledger as well as other financial benefits depending on your country of work. - Commuter allowance - Ledger offers a commuter allowance to contribute to your preferred means of transportation. - Learning & Development - A comprehensive suite of training solutions providing a personalised learning experience for every employee. For regionally specific benefits, your Talent Acquisition contact will be able to provide you with more information. We’re committed to building an inclusive hiring process. If you need any adjustments or accommodations, just let us know, we’ll do our best to support you.