As a member of the Design team, you'll play a critical role in shaping the experience business owners and aspiring entrepreneurs will have when using Durable. You'll craft beautiful experiences that intelligently and intuitively blend agentic workflows and "traditional" ui.

We're looking for designers who want to push technology while deeply empathizing with real customer problems. You'll work across all teams at Durable to define and deliver what the future of AI UX looks like. You'll be responsible for execution, holding everyone to a high standard of quality.

This is not a role where you'll spend your day in Figma. You'll be prototyping directly with the latest models, experimenting, learning their capabilities, and uncovering powerful opportunities to push innovative UX to our customers.

What we're looking for:

• 3+ years of product design experience on shipped B2C products, with a portfolio you can speak to in depth
• Comfortable producing in code or with AI-assisted coding tools (Cursor, Claude Code, or equivalent)
• Fluent with the current generation of AI creative tooling (image gen, video gen, voice) and opinionated about where they're useful
• Experience designing AI or generative experiences: prompt interfaces, automated output, multi-modal interactions
• Systems thinking: design patterns and component libraries that scaled beyond the features you built them for
• Bonus: you have an eye for exceptional brand design and motion and want to help us push the Durable brand further (in product and across marketing)
• Bonus: startup experience or having launched something of your own

Fine print

This role is based in Vancouver. We currently work in-office two days per week on Mondays & Thursdays. 

Compensation is $130,000–$180,000 CAD base plus equity, for Vancouver-based candidates, depending on seniority. Actual salary takes experience, location, and other factors into account.

Your role
At Dialpad, we are building the future of AI-driven communication. As a Software Development Engineer in Test (SDET), you will lead the charge in building scalable, world-class mobile test automation frameworks that empower our engineering teams to ship with confidence and speed.

We are looking for a quality advocate who bridges development and testing. You bring excellent written and verbal communication skills and the ability to collaborate with a geo-distributed team on a shared vision. You will enhance and maintain mobile testing frameworks, lead design decisions, and work closely with other senior developers.

This position reports to a Quality Engineering Manager in the USA.

What you’ll do

• Design and optimize high-performance mobile automation frameworks (iOS/Android) that are fast, reliable, and scalable.
• Maintain performant and reliable CI/CD pipelines.
• Independently analyze test results and investigate failures to identify potential root causes and provide detailed reports.
• Build advanced reporting and tools to provide real-time visibility into product health and failure patterns.
• Develop and execute system performance testing against a variety of systems.
• Work closely with mobile engineers, QA partners, and product teams to ensure features are testable and automation-ready.
• Develop and execute a comprehensive test strategy.
• Perform functional, regression, and performance testing using automation tools.
• Lead the AI Frontier and integrate AI-powered tooling into the testing lifecycle to accelerate defect detection and script generation.
• Advocate for doing the right thing even if it’s difficult.

Skills you’ll bring

• 4+ years of experience as an SDET, Software Engineer, or Test Automation Engineer in SaaS environments.
• Strong programming experience in any top language, such as Python or Java.
• Experience with AI code generation, subagents, and modern code generation workflows.
• Deep, hands-on experience building scalable frameworks from scratch. The ability to articulate complex technical trade-offs to both engineers and non-technical stakeholders across global time zones.
• Highly organized with excellent written and verbal communication skills.
• Experience with cloud-based mobile device testing platforms like LambdaTest, BrowserStack, etc.
• Direct experience applying testing methodologies, including regression, integration, and performance testing
• Extensive knowledge of cloud technologies, including the testing of REST services.
• Strong people skills, as you'll work with other teams in different geographies.
• The "Plus" Factor includes: Experience with mobile programming languages Kotlin or Swift. Application of UX/Accessibility standards and a proactive approach to using Generative AI to optimize development workflows.

Your role
At Dialpad, we are building the future of AI-driven communication. As a Software Development Engineer in Test (SDET), you will lead the charge in building scalable, world-class mobile test automation frameworks that empower our engineering teams to ship with confidence and speed.

We are looking for a quality advocate who bridges development and testing. You bring excellent written and verbal communication skills and the ability to collaborate with a geo-distributed team on a shared vision. You will enhance and maintain mobile testing frameworks, lead design decisions, and work closely with other senior developers.

This position reports to a Quality Engineering Manager in the USA.

What you’ll do

• Design and optimize high-performance mobile automation frameworks (iOS/Android) that are fast, reliable, and scalable.
• Maintain performant and reliable CI/CD pipelines.
• Independently analyze test results and investigate failures to identify potential root causes and provide detailed reports.
• Build advanced reporting and tools to provide real-time visibility into product health and failure patterns.
• Develop and execute system performance testing against a variety of systems.
• Work closely with mobile engineers, QA partners, and product teams to ensure features are testable and automation-ready.
• Develop and execute a comprehensive test strategy.
• Perform functional, regression, and performance testing using automation tools.
• Lead the AI Frontier and integrate AI-powered tooling into the testing lifecycle to accelerate defect detection and script generation.
• Advocate for doing the right thing even if it’s difficult.

Skills you’ll bring

• 4+ years of experience as an SDET, Software Engineer, or Test Automation Engineer in SaaS environments.
• Strong programming experience in any top language, such as Python or Java.
• Experience with AI code generation, subagents, and modern code generation workflows.
• Deep, hands-on experience building scalable frameworks from scratch. The ability to articulate complex technical trade-offs to both engineers and non-technical stakeholders across global time zones.
• Highly organized with excellent written and verbal communication skills.
• Experience with cloud-based mobile device testing platforms like LambdaTest, BrowserStack, etc.
• Direct experience applying testing methodologies, including regression, integration, and performance testing
• Extensive knowledge of cloud technologies, including the testing of REST services.
• Strong people skills, as you'll work with other teams in different geographies.
• The "Plus" Factor includes: Experience with mobile programming languages Kotlin or Swift. Application of UX/Accessibility standards and a proactive approach to using Generative AI to optimize development workflows.

About this position:

We’re looking for a Machine Learning Infrastructure Engineer to join our growing Data & Platform team and build the foundation that powers our AI and machine learning capabilities across Later’s product portfolio. As our first dedicated ML Infrastructure Engineer, you will own the systems that support model experimentation, training, deployment, and monitoring at scale.

This role is critical to accelerating our data science initiatives and enabling future AI innovation. You’ll design and operate reliable, secure, and scalable ML infrastructure that empowers data scientists and engineers to ship high-impact models with confidence. If you’re excited about building robust ML systems in a fast-moving environment—and want to define the standard for ML Ops at Later—this is your opportunity.

What you'll be doing:

Strategy

• Define and own the long-term ML infrastructure roadmap, ensuring it supports both current experimentation needs and future AI initiatives.
• Establish best practices for model lifecycle management, deployment standards, monitoring, and governance. 
• Identify infrastructure gaps and proactively design scalable solutions to enable high-velocity ML development.
• Contribute to cross-functional technical planning, ensuring ML systems align with product and platform strategy.

Technical/ Execution

• Design, build, and maintain production-grade model deployment and inference systems using CI/CD pipelines, containerized services (Docker), and API frameworks (e.g., Flask).
• Automate end-to-end ML lifecycle workflows including training pipelines, model validation, registry management, deployment, and rollback strategies.
• Implement robust monitoring systems for model performance, latency, drift detection, and infrastructure health using tools such as CloudWatch, Prometheus, and Grafana.
• Operate across AWS and GCP environments to manage training and inference workloads, including GPU-based infrastructure and BigQuery datasets.
• Develop and maintain infrastructure-as-code (Terraform, CloudFormation) to ensure scalable, repeatable, and secure cloud environments.
• Implement and optimize CI/CD workflows (e.g., GitHub Actions, GitLab CI, Bitbucket Pipelines) for ML and infrastructure automation.

Team / Collaboration

• Partner closely with Data Scientists, Analysts, Platform Engineers, and Product Engineers to support end-to-end ML workflows.
• Translate data science experimentation needs into production-ready infrastructure solutions.
• Serve as the technical bridge between ML experimentation and productized deployment.
• Share knowledge and best practices to elevate ML maturity across teams.

Research/Best Practices

• Stay current on emerging ML Ops practices, tools, and frameworks to continuously improve system reliability and efficiency.
• Evaluate and implement model-serving frameworks (e.g., TorchServe, Seldon, TensorRT) where appropriate.
• Contribute to governance, reproducibility, and auditability standards for ML systems.
• Experiment with new tooling and workflows to improve reproducibility, performance, and developer velocity.

What success looks like:

• ML models move from experimentation to production quickly and reliably, with minimal manual intervention.
• CI/CD pipelines enable safe, repeatable deployments with clear rollback strategies.
• Model performance, drift, and infrastructure health are proactively monitored and observable.
• Infrastructure supports scalable GPU training and real-time inference without bottlenecks.
• Data scientists report improved velocity, reproducibility, and confidence in deploying models.
• ML systems are secure, compliant, and aligned with evolving product and AI strategy.

What you bring:

• 4+ years of experience in ML Ops, ML infrastructure, backend engineering, or related roles supporting production ML systems.
• Experience working in cloud-native environments (AWS and/or GCP) with hands-on deployment of ML workloads.
• Proven track record designing and implementing CI/CD pipelines for ML systems.
• Strong experience with Amazon SageMaker, Docker, Flask-based APIs, and infrastructure automation tools.
• Hands-on experience with ML lifecycle tooling such as MLflow, SageMaker Studio, or Weights & Biases.
• Experience managing container orchestration platforms (Kubernetes, EKS, or GKE).
• Strong programming experience in Python (additional experience in Go, Java, or Scala is a plus).
• Experience working with infrastructure-as-code tools such as Terraform or CloudFormation.
• Familiarity with observability tools such as CloudWatch, Prometheus, Grafana, Datadog, or centralized logging platforms.
• Experience managing GPU-based workloads and scaling training/inference systems.
• Familiarity with data infrastructure tools such as BigQuery and cloud-native data pipelines.
• Bonus: Experience supporting LLMs or generative AI pipelines, distributed training systems, feature stores (e.g., Feast), real-time inference systems, or ML governance frameworks.
• A mindset focused on automation, reliability, performance, and continuous improvement in fast-scaling environments.

How you work: 

• Driven by Impact: You deliver results that matter—prioritizing high-value work, meeting deadlines, and adapting quickly while keeping outcomes clear.
• Strategic & Customer-Centric: You anticipate risks and opportunities, connect decisions to long-term growth, and build trust through proactive insights.
• Curious & Growth-Oriented: You seek knowledge, ask sharp questions, and apply learnings fast—challenging the status quo with a mindset of improvement.
• Collaborative & Resilient: You thrive in change by staying resourceful, solution-focused, and positive—removing roadblocks, sharing insights, and keeping morale high.
• Accountable & Honest: You own your work, hold yourself and others to a high bar, and use transparent feedback to drive growth.
• Emotionally Intelligent: You build trust through empathy and collaboration, foster inclusion, and inspire others with grit, optimism, and integrity.

Our approach to compensation:

We take a market-based & data-driven approach to compensation. We leverage data from trusted third-party compensation sources to help us understand the market value of a role based on function, level, geographic location, and scope. We evaluate compensation bi-annually, including performance and market-related factors.

Our salaries are benchmarked against market Total Cash Compensation for the geographic location of our job posting. Compensation for some roles is structured as On Target Earnings (OTE = base + commission/variable) while for others it is structured as Salary only.

To comply with local legislation and ensure transparency, we share salary ranges on all job postings. Skills, experience and other factors help determine the final salary we offer which may vary from the original range posted. 

Additionally, all permanent team members are eligible to participate in various benefits plans as part of their overall compensation package.

Salary Range: 

$ 145,000 -165,000 

#LI-remote

About this position:

We’re looking for a Machine Learning Infrastructure Engineer to join our growing Data & Platform team and build the foundation that powers our AI and machine learning capabilities across Later’s product portfolio. As our first dedicated ML Infrastructure Engineer, you will own the systems that support model experimentation, training, deployment, and monitoring at scale.

This role is critical to accelerating our data science initiatives and enabling future AI innovation. You’ll design and operate reliable, secure, and scalable ML infrastructure that empowers data scientists and engineers to ship high-impact models with confidence. If you’re excited about building robust ML systems in a fast-moving environment—and want to define the standard for ML Ops at Later—this is your opportunity.

What you'll be doing:

Strategy

• Define and own the long-term ML infrastructure roadmap, ensuring it supports both current experimentation needs and future AI initiatives.
• Establish best practices for model lifecycle management, deployment standards, monitoring, and governance. 
• Identify infrastructure gaps and proactively design scalable solutions to enable high-velocity ML development.
• Contribute to cross-functional technical planning, ensuring ML systems align with product and platform strategy.

Technical/ Execution

• Design, build, and maintain production-grade model deployment and inference systems using CI/CD pipelines, containerized services (Docker), and API frameworks (e.g., Flask).
• Automate end-to-end ML lifecycle workflows including training pipelines, model validation, registry management, deployment, and rollback strategies.
• Implement robust monitoring systems for model performance, latency, drift detection, and infrastructure health using tools such as CloudWatch, Prometheus, and Grafana.
• Operate across AWS and GCP environments to manage training and inference workloads, including GPU-based infrastructure and BigQuery datasets.
• Develop and maintain infrastructure-as-code (Terraform, CloudFormation) to ensure scalable, repeatable, and secure cloud environments.
• Implement and optimize CI/CD workflows (e.g., GitHub Actions, GitLab CI, Bitbucket Pipelines) for ML and infrastructure automation.

Team / Collaboration

• Partner closely with Data Scientists, Analysts, Platform Engineers, and Product Engineers to support end-to-end ML workflows.
• Translate data science experimentation needs into production-ready infrastructure solutions.
• Serve as the technical bridge between ML experimentation and productized deployment.
• Share knowledge and best practices to elevate ML maturity across teams.

Research/Best Practices

• Stay current on emerging ML Ops practices, tools, and frameworks to continuously improve system reliability and efficiency.
• Evaluate and implement model-serving frameworks (e.g., TorchServe, Seldon, TensorRT) where appropriate.
• Contribute to governance, reproducibility, and auditability standards for ML systems.
• Experiment with new tooling and workflows to improve reproducibility, performance, and developer velocity.

What success looks like:

• ML models move from experimentation to production quickly and reliably, with minimal manual intervention.
• CI/CD pipelines enable safe, repeatable deployments with clear rollback strategies.
• Model performance, drift, and infrastructure health are proactively monitored and observable.
• Infrastructure supports scalable GPU training and real-time inference without bottlenecks.
• Data scientists report improved velocity, reproducibility, and confidence in deploying models.
• ML systems are secure, compliant, and aligned with evolving product and AI strategy.

What you bring:

• 4+ years of experience in ML Ops, ML infrastructure, backend engineering, or related roles supporting production ML systems.
• Experience working in cloud-native environments (AWS and/or GCP) with hands-on deployment of ML workloads.
• Proven track record designing and implementing CI/CD pipelines for ML systems.
• Strong experience with Amazon SageMaker, Docker, Flask-based APIs, and infrastructure automation tools.
• Hands-on experience with ML lifecycle tooling such as MLflow, SageMaker Studio, or Weights & Biases.
• Experience managing container orchestration platforms (Kubernetes, EKS, or GKE).
• Strong programming experience in Python (additional experience in Go, Java, or Scala is a plus).
• Experience working with infrastructure-as-code tools such as Terraform or CloudFormation.
• Familiarity with observability tools such as CloudWatch, Prometheus, Grafana, Datadog, or centralized logging platforms.
• Experience managing GPU-based workloads and scaling training/inference systems.
• Familiarity with data infrastructure tools such as BigQuery and cloud-native data pipelines.
• Bonus: Experience supporting LLMs or generative AI pipelines, distributed training systems, feature stores (e.g., Feast), real-time inference systems, or ML governance frameworks.
• A mindset focused on automation, reliability, performance, and continuous improvement in fast-scaling environments.

How you work: 

• Driven by Impact: You deliver results that matter—prioritizing high-value work, meeting deadlines, and adapting quickly while keeping outcomes clear.
• Strategic & Customer-Centric: You anticipate risks and opportunities, connect decisions to long-term growth, and build trust through proactive insights.
• Curious & Growth-Oriented: You seek knowledge, ask sharp questions, and apply learnings fast—challenging the status quo with a mindset of improvement.
• Collaborative & Resilient: You thrive in change by staying resourceful, solution-focused, and positive—removing roadblocks, sharing insights, and keeping morale high.
• Accountable & Honest: You own your work, hold yourself and others to a high bar, and use transparent feedback to drive growth.
• Emotionally Intelligent: You build trust through empathy and collaboration, foster inclusion, and inspire others with grit, optimism, and integrity.

Our approach to compensation:

We take a market-based & data-driven approach to compensation. We leverage data from trusted third-party compensation sources to help us understand the market value of a role based on function, level, geographic location, and scope. We evaluate compensation bi-annually, including performance and market-related factors.

Our salaries are benchmarked against market Total Cash Compensation for the geographic location of our job posting. Compensation for some roles is structured as On Target Earnings (OTE = base + commission/variable) while for others it is structured as Salary only.

To comply with local legislation and ensure transparency, we share salary ranges on all job postings. Skills, experience and other factors help determine the final salary we offer which may vary from the original range posted. 

Additionally, all permanent team members are eligible to participate in various benefits plans as part of their overall compensation package.

Salary Range: 

$ 145,000 -165,000 

#LI-remote

About this position:

We’re looking for a Machine Learning Infrastructure Engineer to join our growing Data & Platform team and build the foundation that powers our AI and machine learning capabilities across Later’s product portfolio. As our first dedicated ML Infrastructure Engineer, you will own the systems that support model experimentation, training, deployment, and monitoring at scale.

This role is critical to accelerating our data science initiatives and enabling future AI innovation. You’ll design and operate reliable, secure, and scalable ML infrastructure that empowers data scientists and engineers to ship high-impact models with confidence. If you’re excited about building robust ML systems in a fast-moving environment—and want to define the standard for ML Ops at Later—this is your opportunity.

What you'll be doing:

Strategy

• Define and own the long-term ML infrastructure roadmap, ensuring it supports both current experimentation needs and future AI initiatives.
• Establish best practices for model lifecycle management, deployment standards, monitoring, and governance. 
• Identify infrastructure gaps and proactively design scalable solutions to enable high-velocity ML development.
• Contribute to cross-functional technical planning, ensuring ML systems align with product and platform strategy.

Technical/ Execution

• Design, build, and maintain production-grade model deployment and inference systems using CI/CD pipelines, containerized services (Docker), and API frameworks (e.g., Flask).
• Automate end-to-end ML lifecycle workflows including training pipelines, model validation, registry management, deployment, and rollback strategies.
• Implement robust monitoring systems for model performance, latency, drift detection, and infrastructure health using tools such as CloudWatch, Prometheus, and Grafana.
• Operate across AWS and GCP environments to manage training and inference workloads, including GPU-based infrastructure and BigQuery datasets.
• Develop and maintain infrastructure-as-code (Terraform, CloudFormation) to ensure scalable, repeatable, and secure cloud environments.
• Implement and optimize CI/CD workflows (e.g., GitHub Actions, GitLab CI, Bitbucket Pipelines) for ML and infrastructure automation.

Team / Collaboration

• Partner closely with Data Scientists, Analysts, Platform Engineers, and Product Engineers to support end-to-end ML workflows.
• Translate data science experimentation needs into production-ready infrastructure solutions.
• Serve as the technical bridge between ML experimentation and productized deployment.
• Share knowledge and best practices to elevate ML maturity across teams.

Research/Best Practices

• Stay current on emerging ML Ops practices, tools, and frameworks to continuously improve system reliability and efficiency.
• Evaluate and implement model-serving frameworks (e.g., TorchServe, Seldon, TensorRT) where appropriate.
• Contribute to governance, reproducibility, and auditability standards for ML systems.
• Experiment with new tooling and workflows to improve reproducibility, performance, and developer velocity.

What success looks like:

• ML models move from experimentation to production quickly and reliably, with minimal manual intervention.
• CI/CD pipelines enable safe, repeatable deployments with clear rollback strategies.
• Model performance, drift, and infrastructure health are proactively monitored and observable.
• Infrastructure supports scalable GPU training and real-time inference without bottlenecks.
• Data scientists report improved velocity, reproducibility, and confidence in deploying models.
• ML systems are secure, compliant, and aligned with evolving product and AI strategy.

What you bring:

• 4+ years of experience in ML Ops, ML infrastructure, backend engineering, or related roles supporting production ML systems.
• Experience working in cloud-native environments (AWS and/or GCP) with hands-on deployment of ML workloads.
• Proven track record designing and implementing CI/CD pipelines for ML systems.
• Strong experience with Amazon SageMaker, Docker, Flask-based APIs, and infrastructure automation tools.
• Hands-on experience with ML lifecycle tooling such as MLflow, SageMaker Studio, or Weights & Biases.
• Experience managing container orchestration platforms (Kubernetes, EKS, or GKE).
• Strong programming experience in Python (additional experience in Go, Java, or Scala is a plus).
• Experience working with infrastructure-as-code tools such as Terraform or CloudFormation.
• Familiarity with observability tools such as CloudWatch, Prometheus, Grafana, Datadog, or centralized logging platforms.
• Experience managing GPU-based workloads and scaling training/inference systems.
• Familiarity with data infrastructure tools such as BigQuery and cloud-native data pipelines.
• Bonus: Experience supporting LLMs or generative AI pipelines, distributed training systems, feature stores (e.g., Feast), real-time inference systems, or ML governance frameworks.
• A mindset focused on automation, reliability, performance, and continuous improvement in fast-scaling environments.

How you work: 

• Driven by Impact: You deliver results that matter—prioritizing high-value work, meeting deadlines, and adapting quickly while keeping outcomes clear.
• Strategic & Customer-Centric: You anticipate risks and opportunities, connect decisions to long-term growth, and build trust through proactive insights.
• Curious & Growth-Oriented: You seek knowledge, ask sharp questions, and apply learnings fast—challenging the status quo with a mindset of improvement.
• Collaborative & Resilient: You thrive in change by staying resourceful, solution-focused, and positive—removing roadblocks, sharing insights, and keeping morale high.
• Accountable & Honest: You own your work, hold yourself and others to a high bar, and use transparent feedback to drive growth.
• Emotionally Intelligent: You build trust through empathy and collaboration, foster inclusion, and inspire others with grit, optimism, and integrity.

Our approach to compensation:

We take a market-based & data-driven approach to compensation. We leverage data from trusted third-party compensation sources to help us understand the market value of a role based on function, level, geographic location, and scope. We evaluate compensation bi-annually, including performance and market-related factors.

Our salaries are benchmarked against market Total Cash Compensation for the geographic location of our job posting. Compensation for some roles is structured as On Target Earnings (OTE = base + commission/variable) while for others it is structured as Salary only.

To comply with local legislation and ensure transparency, we share salary ranges on all job postings. Skills, experience and other factors help determine the final salary we offer which may vary from the original range posted. 

Additionally, all permanent team members are eligible to participate in various benefits plans as part of their overall compensation package.

Salary Range: 

$ 145,000 -165,000 

#LI-remote

Marketing at Brex

Marketing tells the story of Brex to the world. From acquisition to activation, we translate product value into business results. Our team spans Revenue, Product, and Brand Marketing, and works closely with nearly every function at Brex. We move fast, experiment often, and think deeply about customer behavior. If you want your creativity to drive growth and shape perception, this is the place.

What you’ll do

The Brex Marketing team is looking for an experienced Senior Marketing Operations Manager to own the systems, data infrastructure, and digital growth engine powering our Product-Led Growth (PLG) motion. This role is central to how Brex scales digital acquisition, optimizes self-serve onboarding flows, and unlocks marketing performance through automation, experimentation, and insights.

The ideal candidate is passionate about building a best-in-class marketing tech stack—including structuring event schemas, improving attribution, unlocking insights, and driving efficiency. This person is also excited about how AI and agentic workflows can transform our operational processes, improve personalization, accelerate experimentation velocity, and automate routine tasks. You will help define and execute our future-state marketing operations architecture, modernizing systems, processes, and data across paid, web, product, and lifecycle channels.

Where you’ll work

This role will be based in our New York City office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of two coordinated days in the office per week, Wednesday and Thursday. Starting February 2, 2026, we will require three days per week in office - Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Own and evolve the PLG martech ecosystem—including Twilio Segment, Google Analytics, Marketo, Sanity CMS, Salesforce, and paid-channel integrations—to ensure a best-in-class, scalable, and reliable infrastructure.
• Define and execute a future-state roadmap for PLG operations, leveraging AI-driven automation, agentic workflows, and scalable systems foundations.
• Build and optimize automated lifecycle and activation programs using AI-assisted segmentation, predictive scoring, and personalized content delivery.
• Partner with Web, Product, and Engineering teams to modernize event tracking frameworks, ensuring clean, structured, privacy-aligned data flows through Segment, GA, and in-product analytics.
• Support and scale experimentation by integrating event tracking, metadata, and insights with AI-enabled analysis and rapid test iteration.
• Collaborate with Paid Growth to ensure high-quality tagging, attribution, and channel measurement across Google Ads, LinkedIn Ads, Meta Ads, and Reddit Ads.
• Partner cross-functionally with CX, Operations, Sales, and Web teams to support chatbot and live chat experiences on Brex.com — including qualification logic, routing workflows, data capture, and integration with downstream teams. Serve as the Marketing Operations lead ensuring technical implementation, measurement, workflow orchestration, and operational governance, even in a co-owned model.
• Build dashboards and insights leveraging AI-enhanced analytics to monitor PLG health, funnel friction, conversion behavior, and growth loops.
• Identify opportunities to automate manual processes using Zapier, Segment, Marketo programs, and AI agents to improve speed, accuracy, and scale.
• Troubleshoot and resolve issues across systems (Segment, GA, Marketo, Salesforce), maintaining a high-quality data environment and rapid operational velocity.

Requirements

• 4+ years in Marketing Operations, Growth Operations, or Digital Systems roles supporting PLG or digital-first acquisition funnels.
• Hands-on experience with Segment, Google Analytics, Marketo, and event-based tracking frameworks.
• Strong analytical capabilities related to experimentation, attribution, and funnel performance measurement.
• Experience supporting paid acquisition workflows across Google, LinkedIn, Meta, and other digital channels.
• Experience partnering with cross-functional teams (CX, Operations, Sales, Web) to manage or enhance chatbot and/or live chat experiences—including qualification, routing, data models, and workflows—even when operational ownership is distributed across teams.
• Demonstrated experience driving operational efficiency and automation through workflow orchestration tools (Zapier, agentic AI systems, CDP-triggered workflows).
• Track record of evolving or modernizing a marketing tech stack toward a future-state architecture.
• Experience collaborating closely with Product, Web Engineering, and Data teams.

Bonus Points

• Experience at FinTech or SaaS companies with PLG or self-serve onboarding models.
• Experience using AI and automation to scale marketing workflows, such as generative personalization, predictive scoring, and automated experiment QA.
• Comfort building integrated workflows between CMS (Sanity) and acquisition tracking systems.
• Familiarity with customer journey analytics tools such as Amplitude, Mixpanel, or similar.
• Demonstrated ability to document architecture, propose long-term solutions, and operationalize complex systems with cross-functional partners.
• Understanding of digital identity verification steps and risk-aware conversion optimization.
• Familiarity with Lead-to-Product connective processes (where website signups eventually feed the GTM funnel).
• Knowledge of ABM or enterprise programs is a plus for hybrid funnel interactions.

Compensation

The expected salary range for this role is $134,696 - $168,370.  However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Marketing at Brex

Marketing tells the story of Brex to the world. From acquisition to activation, we translate product value into business results. Our team spans Revenue, Product, and Brand Marketing, and works closely with nearly every function at Brex. We move fast, experiment often, and think deeply about customer behavior. If you want your creativity to drive growth and shape perception, this is the place.

What you’ll do

The Brex Marketing team is looking for an experienced Senior Marketing Operations Manager to own the systems, data infrastructure, and digital growth engine powering our Product-Led Growth (PLG) motion. This role is central to how Brex scales digital acquisition, optimizes self-serve onboarding flows, and unlocks marketing performance through automation, experimentation, and insights.

The ideal candidate is passionate about building a best-in-class marketing tech stack—including structuring event schemas, improving attribution, unlocking insights, and driving efficiency. This person is also excited about how AI and agentic workflows can transform our operational processes, improve personalization, accelerate experimentation velocity, and automate routine tasks. You will help define and execute our future-state marketing operations architecture, modernizing systems, processes, and data across paid, web, product, and lifecycle channels.

Where you’ll work

This role will be based in our Seattle office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of two coordinated days in the office per week, Wednesday and Thursday. Starting February 2, 2026, we will require three days per week in office - Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Own and evolve the PLG martech ecosystem—including Twilio Segment, Google Analytics, Marketo, Sanity CMS, Salesforce, and paid-channel integrations—to ensure a best-in-class, scalable, and reliable infrastructure.
• Define and execute a future-state roadmap for PLG operations, leveraging AI-driven automation, agentic workflows, and scalable systems foundations.
• Build and optimize automated lifecycle and activation programs using AI-assisted segmentation, predictive scoring, and personalized content delivery.
• Partner with Web, Product, and Engineering teams to modernize event tracking frameworks, ensuring clean, structured, privacy-aligned data flows through Segment, GA, and in-product analytics.
• Support and scale experimentation by integrating event tracking, metadata, and insights with AI-enabled analysis and rapid test iteration.
• Collaborate with Paid Growth to ensure high-quality tagging, attribution, and channel measurement across Google Ads, LinkedIn Ads, Meta Ads, and Reddit Ads.
• Partner cross-functionally with CX, Operations, Sales, and Web teams to support chatbot and live chat experiences on Brex.com — including qualification logic, routing workflows, data capture, and integration with downstream teams. Serve as the Marketing Operations lead ensuring technical implementation, measurement, workflow orchestration, and operational governance, even in a co-owned model.
• Build dashboards and insights leveraging AI-enhanced analytics to monitor PLG health, funnel friction, conversion behavior, and growth loops.
• Identify opportunities to automate manual processes using Zapier, Segment, Marketo programs, and AI agents to improve speed, accuracy, and scale.
• Troubleshoot and resolve issues across systems (Segment, GA, Marketo, Salesforce), maintaining a high-quality data environment and rapid operational velocity.

Requirements

• 4+ years in Marketing Operations, Growth Operations, or Digital Systems roles supporting PLG or digital-first acquisition funnels.
• Hands-on experience with Segment, Google Analytics, Marketo, and event-based tracking frameworks.
• Strong analytical capabilities related to experimentation, attribution, and funnel performance measurement.
• Experience supporting paid acquisition workflows across Google, LinkedIn, Meta, and other digital channels.
• Experience partnering with cross-functional teams (CX, Operations, Sales, Web) to manage or enhance chatbot and/or live chat experiences—including qualification, routing, data models, and workflows—even when operational ownership is distributed across teams.
• Demonstrated experience driving operational efficiency and automation through workflow orchestration tools (Zapier, agentic AI systems, CDP-triggered workflows).
• Track record of evolving or modernizing a marketing tech stack toward a future-state architecture.
• Experience collaborating closely with Product, Web Engineering, and Data teams.

Bonus Points

• Experience at FinTech or SaaS companies with PLG or self-serve onboarding models.
• Experience using AI and automation to scale marketing workflows, such as generative personalization, predictive scoring, and automated experiment QA.
• Comfort building integrated workflows between CMS (Sanity) and acquisition tracking systems.
• Familiarity with customer journey analytics tools such as Amplitude, Mixpanel, or similar.
• Demonstrated ability to document architecture, propose long-term solutions, and operationalize complex systems with cross-functional partners.
• Understanding of digital identity verification steps and risk-aware conversion optimization.
• Familiarity with Lead-to-Product connective processes (where website signups eventually feed the GTM funnel).
• Knowledge of ABM or enterprise programs is a plus for hybrid funnel interactions.

Compensation

The expected salary range for this role is $134,696 - $168,370.  However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Marketing at Brex

Marketing tells the story of Brex to the world. From acquisition to activation, we translate product value into business results. Our team spans Revenue, Product, and Brand Marketing, and works closely with nearly every function at Brex. We move fast, experiment often, and think deeply about customer behavior. If you want your creativity to drive growth and shape perception, this is the place.

What you’ll do

The Brex Marketing team is looking for an experienced Senior Marketing Operations Manager to own the systems, data infrastructure, and digital growth engine powering our Product-Led Growth (PLG) motion. This role is central to how Brex scales digital acquisition, optimizes self-serve onboarding flows, and unlocks marketing performance through automation, experimentation, and insights.

The ideal candidate is passionate about building a best-in-class marketing tech stack—including structuring event schemas, improving attribution, unlocking insights, and driving efficiency. This person is also excited about how AI and agentic workflows can transform our operational processes, improve personalization, accelerate experimentation velocity, and automate routine tasks. You will help define and execute our future-state marketing operations architecture, modernizing systems, processes, and data across paid, web, product, and lifecycle channels.

Where you’ll work

This role will be based in our San Francisco office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of two coordinated days in the office per week, Wednesday and Thursday. Starting February 2, 2026, we will require three days per week in office - Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Own and evolve the PLG martech ecosystem—including Twilio Segment, Google Analytics, Marketo, Sanity CMS, Salesforce, and paid-channel integrations—to ensure a best-in-class, scalable, and reliable infrastructure.
• Define and execute a future-state roadmap for PLG operations, leveraging AI-driven automation, agentic workflows, and scalable systems foundations.
• Build and optimize automated lifecycle and activation programs using AI-assisted segmentation, predictive scoring, and personalized content delivery.
• Partner with Web, Product, and Engineering teams to modernize event tracking frameworks, ensuring clean, structured, privacy-aligned data flows through Segment, GA, and in-product analytics.
• Support and scale experimentation by integrating event tracking, metadata, and insights with AI-enabled analysis and rapid test iteration.
• Collaborate with Paid Growth to ensure high-quality tagging, attribution, and channel measurement across Google Ads, LinkedIn Ads, Meta Ads, and Reddit Ads.
• Partner cross-functionally with CX, Operations, Sales, and Web teams to support chatbot and live chat experiences on Brex.com — including qualification logic, routing workflows, data capture, and integration with downstream teams. Serve as the Marketing Operations lead ensuring technical implementation, measurement, workflow orchestration, and operational governance, even in a co-owned model.
• Build dashboards and insights leveraging AI-enhanced analytics to monitor PLG health, funnel friction, conversion behavior, and growth loops.
• Identify opportunities to automate manual processes using Zapier, Segment, Marketo programs, and AI agents to improve speed, accuracy, and scale.
• Troubleshoot and resolve issues across systems (Segment, GA, Marketo, Salesforce), maintaining a high-quality data environment and rapid operational velocity.

Requirements

• 4+ years in Marketing Operations, Growth Operations, or Digital Systems roles supporting PLG or digital-first acquisition funnels.
• Hands-on experience with Segment, Google Analytics, Marketo, and event-based tracking frameworks.
• Strong analytical capabilities related to experimentation, attribution, and funnel performance measurement.
• Experience supporting paid acquisition workflows across Google, LinkedIn, Meta, and other digital channels.
• Experience partnering with cross-functional teams (CX, Operations, Sales, Web) to manage or enhance chatbot and/or live chat experiences—including qualification, routing, data models, and workflows—even when operational ownership is distributed across teams.
• Demonstrated experience driving operational efficiency and automation through workflow orchestration tools (Zapier, agentic AI systems, CDP-triggered workflows).
• Track record of evolving or modernizing a marketing tech stack toward a future-state architecture.
• Experience collaborating closely with Product, Web Engineering, and Data teams.

Bonus Points

• Experience at FinTech or SaaS companies with PLG or self-serve onboarding models.
• Experience using AI and automation to scale marketing workflows, such as generative personalization, predictive scoring, and automated experiment QA.
• Comfort building integrated workflows between CMS (Sanity) and acquisition tracking systems.
• Familiarity with customer journey analytics tools such as Amplitude, Mixpanel, or similar.
• Demonstrated ability to document architecture, propose long-term solutions, and operationalize complex systems with cross-functional partners.
• Understanding of digital identity verification steps and risk-aware conversion optimization.
• Familiarity with Lead-to-Product connective processes (where website signups eventually feed the GTM funnel).
• Knowledge of ABM or enterprise programs is a plus for hybrid funnel interactions.

Compensation

The expected salary range for this role is $134,696 - $168,370.  However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

As Marqeta’s  Manager of Service Delivery & Partner Performance you'll be at the forefront of transforming customer support into a competitive advantage. This role puts you in the driver's seat to revolutionize how we deliver exceptional cardholder experiences through data-driven insights, cutting-edge technology, and strategic partnerships.

You'll have the autonomy to identify opportunities, architect solutions, and implement change that measurably elevates our support operations and cardholder’s experience. Working with talented cross-functional teams and strategic BPO partners, you'll not only meet KPIs and SLAs—you'll redefine what excellence looks like in fintech customer support.

This is your opportunity to make a tangible impact on cardholders while building a high-performing support ecosystem. You'll shape performance standards, drive operational transformation, and create the frameworks that scale as Marqeta grows. If you thrive on turning data into action, building collaborative partnerships, and seeing your strategies deliver real results, this role is your platform to shine.

We work Flexible First. This role can be performed remotely anywhere within Ontario or British Columbia, Canada. We’d love for you to join us!

This position is not for an existing vacancy.

The Impact You’ll Have

• Performance Fanatic: You don’t sit around and wait for things to happen. You strategize, plan, and monitor a path to operational success based on the right data.
• BPO Vendor Management: Manage the operational success of multiple programs across multiple products through building and maintaining effective relationships with operational BPO site leadership
• Performance Analysis & Reporting: Monitor and analyze contact center data (KPIs, metrics) to identify trends and areas for improvement.
• Process Optimization: Identify gaps, develop and implement sustainable and scalable solutions  to enhance operational efficiency, workflows, and customer satisfaction.
• Quality Assurance & Compliance: Define what great looks like and collaborate with QA and Complaints teams to ensure adherence to quality standards and compliance requirements.
• Technology Implementation: Utilize and drive enhancements through new tooling and AI solutions across our telephony, IVR and CRM system to improve agent efficiency and effectiveness 
• Leadership & Coaching: Motivate staff, provide coaching, and influence positive outcomes to cultivate a high-performing culture.
• Escalation Management: Resolve complex customer issues during moments of truth.
• Cardholder Experience Optimization: Foster strong relationships with key Program stakeholders to collaborate on enhancing cardholder experience through sharing expertise, CSAT/QA results and data drive operational efficiencies
• Change Management: Central role to new program launches and existing program refreshes
• Marqeta Culture Carrier: Champion culture cross-functionally through actively embodying Marqeta values, enhancing engagement, and facilitating culture-building activities 

Who You Are

• 7+ years of Customer Support Operations with equivalent years of experience in BPO industry or management of BPOs
• Strong communication skills (interpersonal, verbal, presentation, written, email) and track record of creating and executing strategic operational efficiencies 
• Demonstrated ability to drive customer satisfaction and experience using people, processes or technology to deliver exception outcomes
• Proven ability to influence and manage stakeholders (internal and external) to achieve positive outcomes
• Experience using data to drive insights and recommend changes for improvement
• Strong technical aptitude including Google Suite, Salesforce, Slack and contact center telephony systems (ex. Amazon Connect)
• Familiarity and first-hand knowledge in fintech, banking or payments
• Positive attitude, team player, adaptable, and resourceful
• Detail-oriented, organized, and adept at managing competing priorities
• Exercises sound judgement and decision-making across diverse scenarios
• Ability to travel globally

Nice-To-Haves

• Deep knowledge of payment processing, program management and/or issuing of debit and credit cards
• Demonstrated ability to manage and operate Amazon Connect
• Strong operational and customer-facing documentation skills with the ability to produce clear, engaging internal and external support guides
• Experience implementing and growing communication channels beyond phone and email
• Proven success in integrating AI solutions into BPO operations from generative AI tooling to agentic implementation of voice or chatbots

Your Manager

• Jena Baker, Ops Director of Global Customer Support Operations

Typical Process

• Application Submission
• Recruiter video call
• Hiring manager video call
• Virtual “Onsite” consisting of 4-5, 45 min calls

Compensation and Benefits

Marqeta is a Flex First company which allows you to choose your best working environment, whether that be from home or at a company office. To support Flex First, we calibrate pay to a competitive value according to working location. 

When determining salaries, we consider several factors including, but not limited to, skills, prior experience, and work location. The new-hire base salary range for this position, reflected in CAD,  is: 114,500 - 143,000

We also believe in recognizing the contributions of our people. That's why we award annual bonuses to eligible employees, rewarding both individual performance and the success of the entire company.

Along with monetary compensation, Marqeta offers

• Multiple health insurance options
• Flexible vacation time
• Retirement savings program with company contribution
• Equity in a publicly-traded company 
• Monthly stipend to support our remote work model
• Annual “development dollars” to support our people growth and development
• Family-forming benefits and up to 20 weeks of Parental Leave

As VP of Search, you’ll set the vision and direction for our global Search practice—leading best-in-class SEO, SEM, and Generative Engine Optimization (GEO) strategies across a diverse portfolio of clients and regions. You are the global leader and point of contact for Search within the agency, responsible for practice leadership, quality standards, capability growth, and operational excellence.

You’ll translate the evolving search landscape—including AI-powered discovery (AI Overviews, LLMs, and “answer engines”)—into actionable strategies, scalable frameworks, and measurable business outcomes. You balance executive-level client counsel with hands-on strategic depth, while building and sustaining a high-performing global team through strategic talent planning, staffing, and resourcing.

You’ll play a pivotal role in expanding our Search services and capabilities and helping our clients achieve top-tier performance. You define what great looks like, ensure we deliver it consistently, and evolve our offering to keep CM at the forefront of the industry.

*This is a one-year contract opportunity*

You Will: 

Practice leadership & operations

• Serve as the discipline lead and global point of contact for the Search practice—representing CM’s Search capabilities across agency leadership, cross-functional partners, and the broader Omnicom network.
• Define and lead the agency-wide vision for best-in-class SEO, SEM, and GEO—developing strategic POVs, frameworks, and standardized processes across regions and accounts.
• Act as a strategic thought leader, innovator, and champion for the role of search across the modern digital ecosystem.
• Spearhead and deliver educational Search presentations, developing internal slideware to keep other disciplines updated on search news, trends, best practices, and “what it means for your clients” opportunities.
• Own staffing strategy and resourcing across the global Search practice and client portfolio, partnering with Operations and account leaders to forecast needs, allocate talent, and address coverage gaps proactively.
• Lead administrative and operational oversight for the discipline (e.g., capacity planning, utilization, role mix, and scalable delivery models, performance reviews, capability roadmaps).

Client leadership & business growth

• Act as the executive Search lead for priority accounts, guiding senior stakeholders and ensuring Search programs align to business objectives, scope and measurable outcomes.
• Lead the creation, definition, execution, and optimization of holistic search strategies (SEO + SEM + GEO), including multi-year roadmaps.
• Proactively drive new business growth—shaping offerings, scoping work, mapping pricing/LOEs, supporting new business pitches, and identifying organic growth opportunities.
• Communicate complex search concepts and performance narratives in a concise, compelling, executive-ready manner, transforming search data insights into strategic opportunities.

Innovation, AI search & future-proofing

• Lead and implement AI Search Optimization / GEO strategies, ensuring clients are discoverable across AI Overviews and LLMs (ChatGPT, Perplexity, Gemini, AI Mode, etc.).
• Build frameworks and processes to systematically track and improve search performance, including GEO visibility metrics, attribution impacts, and content/technical readiness.
• Keep the agency ahead of search shifts (AI/ML automation, SERP changes, visual/voice/social search) and translate those shifts into new service offerings.

Strategy & execution

• Utilize cross-channel search data to understand user intent, shape content strategy, and identify business opportunities.
• Advise on technical website development to maximize indexability and visibility, including JavaScript SEO and accessibility considerations for both users and LLM crawlers.
• Define search-driven guidelines and requirements for content, page speed, accessibility, structured data, site architecture, URL structure, metadata, internal linking, sitemaps, etc.
• Conduct regular SEO/SEM/GEO audits and competitive analyses, translating insights into prioritized, executable roadmaps.
• Deliver actionable performance insights and strategic recommendations through clear, visually compelling reports—communicating complex concepts in a concise and easy-to-understand manner
• Collaborate with cross-functional teams to incorporate SEO strategies and best practices.
• Optimize social search channels (e.g., YouTube, TikTok) to maximize brand and content visibility across the digital landscape.
• Define success metrics and translate SEO/SEM/GEO results to business objectives.

You Have:

• 10–15+ years of Search experience, including 5+ years leading high-performing Search teams across multiple accounts.
• Experience managing department-level staffing, resourcing and operations.
• Strong communication and data storytelling skills (written and verbal), with confidence presenting to executive clients and agency leadership.
• Deep expertise in SEO (technical + content + UX + measurement) and experience overseeing SEM strategy or managing large-budget paid search campaigns.
• Experience integrating paid and organic search strategies and workflows to reduce costs while maximizing key business outcomes.
• Proven track record of driving measurable performance improvements.
• Strong organizational and project management skills, with experience leading multiple workstreams, teams, and deadlines simultaneously.
• Experience with global brands and international SEO (multi-region, multi-language sites).
• Experience managing SEO strategies for large-scale website migrations and redesigns.
• Experience with GEO and AI search optimization for both AI Overviews and LLMs (ChatGPT, Perplexity, Gemini, AI Mode, etc.).
• Experience defining and documenting cross-disciplinary internal processes, playbooks, and best practices to improve search implementation and deliverable quality.
• Deep understanding of search algorithms and ranking factors across modern search ecosystems (traditional search, social search & AI search).
• Proficiency in 3rd party SEO/SEM tools such as SEMrush, BrightEdge, Ahrefs, Screaming Frog, and similar platforms.
• Proficiency in analytics and visualization tools such as Google Analytics, Looker Studio (Data Studio), Adobe Analytics, Google Search Console, Tableau, etc.
• Experience with GEO/AI search tracking tools such as Profound, BlueFish, BrightEdge AI Catalyst, or similar solutions.
• Strong analytical skills, with the ability to interpret data, identify trends, and make data-driven decisions.
• Strong Excel skills (pivot tables, VLOOKUP/XLOOKUP, large datasets) and experience analyzing and reporting on performance data.
• Experience developing and executing search-driven content strategies that improve visibility, traffic, engagement, and conversion.
• Experience testing and leveraging AI to improve search workflows, efficiencies, and quality.
• A proactive, self-starter attitude and a passion for staying current in a rapidly evolving digital landscape.

As VP of Search, you’ll set the vision and direction for our global Search practice—leading best-in-class SEO, SEM, and Generative Engine Optimization (GEO) strategies across a diverse portfolio of clients and regions. You are the global leader and point of contact for Search within the agency, responsible for practice leadership, quality standards, capability growth, and operational excellence.

You’ll translate the evolving search landscape—including AI-powered discovery (AI Overviews, LLMs, and “answer engines”)—into actionable strategies, scalable frameworks, and measurable business outcomes. You balance executive-level client counsel with hands-on strategic depth, while building and sustaining a high-performing global team through strategic talent planning, staffing, and resourcing.

You’ll play a pivotal role in expanding our Search services and capabilities and helping our clients achieve top-tier performance. You define what great looks like, ensure we deliver it consistently, and evolve our offering to keep CM at the forefront of the industry.

*This is a one-year contract opportunity*

You Will: 

Practice leadership & operations

• Serve as the discipline lead and global point of contact for the Search practice—representing CM’s Search capabilities across agency leadership, cross-functional partners, and the broader Omnicom network.
• Define and lead the agency-wide vision for best-in-class SEO, SEM, and GEO—developing strategic POVs, frameworks, and standardized processes across regions and accounts.
• Act as a strategic thought leader, innovator, and champion for the role of search across the modern digital ecosystem.
• Spearhead and deliver educational Search presentations, developing internal slideware to keep other disciplines updated on search news, trends, best practices, and “what it means for your clients” opportunities.
• Own staffing strategy and resourcing across the global Search practice and client portfolio, partnering with Operations and account leaders to forecast needs, allocate talent, and address coverage gaps proactively.
• Lead administrative and operational oversight for the discipline (e.g., capacity planning, utilization, role mix, and scalable delivery models, performance reviews, capability roadmaps).

Client leadership & business growth

• Act as the executive Search lead for priority accounts, guiding senior stakeholders and ensuring Search programs align to business objectives, scope and measurable outcomes.
• Lead the creation, definition, execution, and optimization of holistic search strategies (SEO + SEM + GEO), including multi-year roadmaps.
• Proactively drive new business growth—shaping offerings, scoping work, mapping pricing/LOEs, supporting new business pitches, and identifying organic growth opportunities.
• Communicate complex search concepts and performance narratives in a concise, compelling, executive-ready manner, transforming search data insights into strategic opportunities.

Innovation, AI search & future-proofing

• Lead and implement AI Search Optimization / GEO strategies, ensuring clients are discoverable across AI Overviews and LLMs (ChatGPT, Perplexity, Gemini, AI Mode, etc.).
• Build frameworks and processes to systematically track and improve search performance, including GEO visibility metrics, attribution impacts, and content/technical readiness.
• Keep the agency ahead of search shifts (AI/ML automation, SERP changes, visual/voice/social search) and translate those shifts into new service offerings.

Strategy & execution

• Utilize cross-channel search data to understand user intent, shape content strategy, and identify business opportunities.
• Advise on technical website development to maximize indexability and visibility, including JavaScript SEO and accessibility considerations for both users and LLM crawlers.
• Define search-driven guidelines and requirements for content, page speed, accessibility, structured data, site architecture, URL structure, metadata, internal linking, sitemaps, etc.
• Conduct regular SEO/SEM/GEO audits and competitive analyses, translating insights into prioritized, executable roadmaps.
• Deliver actionable performance insights and strategic recommendations through clear, visually compelling reports—communicating complex concepts in a concise and easy-to-understand manner
• Collaborate with cross-functional teams to incorporate SEO strategies and best practices.
• Optimize social search channels (e.g., YouTube, TikTok) to maximize brand and content visibility across the digital landscape.
• Define success metrics and translate SEO/SEM/GEO results to business objectives.

You Have:

• 10–15+ years of Search experience, including 5+ years leading high-performing Search teams across multiple accounts.
• Experience managing department-level staffing, resourcing and operations.
• Strong communication and data storytelling skills (written and verbal), with confidence presenting to executive clients and agency leadership.
• Deep expertise in SEO (technical + content + UX + measurement) and experience overseeing SEM strategy or managing large-budget paid search campaigns.
• Experience integrating paid and organic search strategies and workflows to reduce costs while maximizing key business outcomes.
• Proven track record of driving measurable performance improvements.
• Strong organizational and project management skills, with experience leading multiple workstreams, teams, and deadlines simultaneously.
• Experience with global brands and international SEO (multi-region, multi-language sites).
• Experience managing SEO strategies for large-scale website migrations and redesigns.
• Experience with GEO and AI search optimization for both AI Overviews and LLMs (ChatGPT, Perplexity, Gemini, AI Mode, etc.).
• Experience defining and documenting cross-disciplinary internal processes, playbooks, and best practices to improve search implementation and deliverable quality.
• Deep understanding of search algorithms and ranking factors across modern search ecosystems (traditional search, social search & AI search).
• Proficiency in 3rd party SEO/SEM tools such as SEMrush, BrightEdge, Ahrefs, Screaming Frog, and similar platforms.
• Proficiency in analytics and visualization tools such as Google Analytics, Looker Studio (Data Studio), Adobe Analytics, Google Search Console, Tableau, etc.
• Experience with GEO/AI search tracking tools such as Profound, BlueFish, BrightEdge AI Catalyst, or similar solutions.
• Strong analytical skills, with the ability to interpret data, identify trends, and make data-driven decisions.
• Strong Excel skills (pivot tables, VLOOKUP/XLOOKUP, large datasets) and experience analyzing and reporting on performance data.
• Experience developing and executing search-driven content strategies that improve visibility, traffic, engagement, and conversion.
• Experience testing and leveraging AI to improve search workflows, efficiencies, and quality.
• A proactive, self-starter attitude and a passion for staying current in a rapidly evolving digital landscape.

*Please note, the pay range noted below is hourly*

As VP of Search, you’ll set the vision and direction for our global Search practice—leading best-in-class SEO, SEM, and Generative Engine Optimization (GEO) strategies across a diverse portfolio of clients and regions. You are the global leader and point of contact for Search within the agency, responsible for practice leadership, quality standards, capability growth, and operational excellence.

You’ll translate the evolving search landscape—including AI-powered discovery (AI Overviews, LLMs, and “answer engines”)—into actionable strategies, scalable frameworks, and measurable business outcomes. You balance executive-level client counsel with hands-on strategic depth, while building and sustaining a high-performing global team through strategic talent planning, staffing, and resourcing.

You’ll play a pivotal role in expanding our Search services and capabilities and helping our clients achieve top-tier performance. You define what great looks like, ensure we deliver it consistently, and evolve our offering to keep CM at the forefront of the industry.

*This is a one-year contract opportunity*

You Will: 

Practice leadership & operations

• Serve as the discipline lead and global point of contact for the Search practice—representing CM’s Search capabilities across agency leadership, cross-functional partners, and the broader Omnicom network.
• Define and lead the agency-wide vision for best-in-class SEO, SEM, and GEO—developing strategic POVs, frameworks, and standardized processes across regions and accounts.
• Act as a strategic thought leader, innovator, and champion for the role of search across the modern digital ecosystem.
• Spearhead and deliver educational Search presentations, developing internal slideware to keep other disciplines updated on search news, trends, best practices, and “what it means for your clients” opportunities.
• Own staffing strategy and resourcing across the global Search practice and client portfolio, partnering with Operations and account leaders to forecast needs, allocate talent, and address coverage gaps proactively.
• Lead administrative and operational oversight for the discipline (e.g., capacity planning, utilization, role mix, and scalable delivery models, performance reviews, capability roadmaps).

Client leadership & business growth

• Act as the executive Search lead for priority accounts, guiding senior stakeholders and ensuring Search programs align to business objectives, scope and measurable outcomes.
• Lead the creation, definition, execution, and optimization of holistic search strategies (SEO + SEM + GEO), including multi-year roadmaps.
• Proactively drive new business growth—shaping offerings, scoping work, mapping pricing/LOEs, supporting new business pitches, and identifying organic growth opportunities.
• Communicate complex search concepts and performance narratives in a concise, compelling, executive-ready manner, transforming search data insights into strategic opportunities.

Innovation, AI search & future-proofing

• Lead and implement AI Search Optimization / GEO strategies, ensuring clients are discoverable across AI Overviews and LLMs (ChatGPT, Perplexity, Gemini, AI Mode, etc.).
• Build frameworks and processes to systematically track and improve search performance, including GEO visibility metrics, attribution impacts, and content/technical readiness.
• Keep the agency ahead of search shifts (AI/ML automation, SERP changes, visual/voice/social search) and translate those shifts into new service offerings.

Strategy & execution

• Utilize cross-channel search data to understand user intent, shape content strategy, and identify business opportunities.
• Advise on technical website development to maximize indexability and visibility, including JavaScript SEO and accessibility considerations for both users and LLM crawlers.
• Define search-driven guidelines and requirements for content, page speed, accessibility, structured data, site architecture, URL structure, metadata, internal linking, sitemaps, etc.
• Conduct regular SEO/SEM/GEO audits and competitive analyses, translating insights into prioritized, executable roadmaps.
• Deliver actionable performance insights and strategic recommendations through clear, visually compelling reports—communicating complex concepts in a concise and easy-to-understand manner
• Collaborate with cross-functional teams to incorporate SEO strategies and best practices.
• Optimize social search channels (e.g., YouTube, TikTok) to maximize brand and content visibility across the digital landscape.
• Define success metrics and translate SEO/SEM/GEO results to business objectives.

You Have:

• 10–15+ years of Search experience, including 5+ years leading high-performing Search teams across multiple accounts.
• Experience managing department-level staffing, resourcing and operations.
• Strong communication and data storytelling skills (written and verbal), with confidence presenting to executive clients and agency leadership.
• Deep expertise in SEO (technical + content + UX + measurement) and experience overseeing SEM strategy or managing large-budget paid search campaigns.
• Experience integrating paid and organic search strategies and workflows to reduce costs while maximizing key business outcomes.
• Proven track record of driving measurable performance improvements.
• Strong organizational and project management skills, with experience leading multiple workstreams, teams, and deadlines simultaneously.
• Experience with global brands and international SEO (multi-region, multi-language sites).
• Experience managing SEO strategies for large-scale website migrations and redesigns.
• Experience with GEO and AI search optimization for both AI Overviews and LLMs (ChatGPT, Perplexity, Gemini, AI Mode, etc.).
• Experience defining and documenting cross-disciplinary internal processes, playbooks, and best practices to improve search implementation and deliverable quality.
• Deep understanding of search algorithms and ranking factors across modern search ecosystems (traditional search, social search & AI search).
• Proficiency in 3rd party SEO/SEM tools such as SEMrush, BrightEdge, Ahrefs, Screaming Frog, and similar platforms.
• Proficiency in analytics and visualization tools such as Google Analytics, Looker Studio (Data Studio), Adobe Analytics, Google Search Console, Tableau, etc.
• Experience with GEO/AI search tracking tools such as Profound, BlueFish, BrightEdge AI Catalyst, or similar solutions.
• Strong analytical skills, with the ability to interpret data, identify trends, and make data-driven decisions.
• Strong Excel skills (pivot tables, VLOOKUP/XLOOKUP, large datasets) and experience analyzing and reporting on performance data.
• Experience developing and executing search-driven content strategies that improve visibility, traffic, engagement, and conversion.
• Experience testing and leveraging AI to improve search workflows, efficiencies, and quality.
• A proactive, self-starter attitude and a passion for staying current in a rapidly evolving digital landscape.

As VP of Search, you’ll set the vision and direction for our global Search practice—leading best-in-class SEO, SEM, and Generative Engine Optimization (GEO) strategies across a diverse portfolio of clients and regions. You are the global leader and point of contact for Search within the agency, responsible for practice leadership, quality standards, capability growth, and operational excellence.

You’ll translate the evolving search landscape—including AI-powered discovery (AI Overviews, LLMs, and “answer engines”)—into actionable strategies, scalable frameworks, and measurable business outcomes. You balance executive-level client counsel with hands-on strategic depth, while building and sustaining a high-performing global team through strategic talent planning, staffing, and resourcing.

You’ll play a pivotal role in expanding our Search services and capabilities and helping our clients achieve top-tier performance. You define what great looks like, ensure we deliver it consistently, and evolve our offering to keep CM at the forefront of the industry.

*This is a one-year contract opportunity*

You Will: 

Practice leadership & operations

• Serve as the discipline lead and global point of contact for the Search practice—representing CM’s Search capabilities across agency leadership, cross-functional partners, and the broader Omnicom network.
• Define and lead the agency-wide vision for best-in-class SEO, SEM, and GEO—developing strategic POVs, frameworks, and standardized processes across regions and accounts.
• Act as a strategic thought leader, innovator, and champion for the role of search across the modern digital ecosystem.
• Spearhead and deliver educational Search presentations, developing internal slideware to keep other disciplines updated on search news, trends, best practices, and “what it means for your clients” opportunities.
• Own staffing strategy and resourcing across the global Search practice and client portfolio, partnering with Operations and account leaders to forecast needs, allocate talent, and address coverage gaps proactively.
• Lead administrative and operational oversight for the discipline (e.g., capacity planning, utilization, role mix, and scalable delivery models, performance reviews, capability roadmaps).

Client leadership & business growth

• Act as the executive Search lead for priority accounts, guiding senior stakeholders and ensuring Search programs align to business objectives, scope and measurable outcomes.
• Lead the creation, definition, execution, and optimization of holistic search strategies (SEO + SEM + GEO), including multi-year roadmaps.
• Proactively drive new business growth—shaping offerings, scoping work, mapping pricing/LOEs, supporting new business pitches, and identifying organic growth opportunities.
• Communicate complex search concepts and performance narratives in a concise, compelling, executive-ready manner, transforming search data insights into strategic opportunities.

Innovation, AI search & future-proofing

• Lead and implement AI Search Optimization / GEO strategies, ensuring clients are discoverable across AI Overviews and LLMs (ChatGPT, Perplexity, Gemini, AI Mode, etc.).
• Build frameworks and processes to systematically track and improve search performance, including GEO visibility metrics, attribution impacts, and content/technical readiness.
• Keep the agency ahead of search shifts (AI/ML automation, SERP changes, visual/voice/social search) and translate those shifts into new service offerings.

Strategy & execution

• Utilize cross-channel search data to understand user intent, shape content strategy, and identify business opportunities.
• Advise on technical website development to maximize indexability and visibility, including JavaScript SEO and accessibility considerations for both users and LLM crawlers.
• Define search-driven guidelines and requirements for content, page speed, accessibility, structured data, site architecture, URL structure, metadata, internal linking, sitemaps, etc.
• Conduct regular SEO/SEM/GEO audits and competitive analyses, translating insights into prioritized, executable roadmaps.
• Deliver actionable performance insights and strategic recommendations through clear, visually compelling reports—communicating complex concepts in a concise and easy-to-understand manner
• Collaborate with cross-functional teams to incorporate SEO strategies and best practices.
• Optimize social search channels (e.g., YouTube, TikTok) to maximize brand and content visibility across the digital landscape.
• Define success metrics and translate SEO/SEM/GEO results to business objectives.

You Have:

• 10–15+ years of Search experience, including 5+ years leading high-performing Search teams across multiple accounts.
• Experience managing department-level staffing, resourcing and operations.
• Strong communication and data storytelling skills (written and verbal), with confidence presenting to executive clients and agency leadership.
• Deep expertise in SEO (technical + content + UX + measurement) and experience overseeing SEM strategy or managing large-budget paid search campaigns.
• Experience integrating paid and organic search strategies and workflows to reduce costs while maximizing key business outcomes.
• Proven track record of driving measurable performance improvements.
• Strong organizational and project management skills, with experience leading multiple workstreams, teams, and deadlines simultaneously.
• Experience with global brands and international SEO (multi-region, multi-language sites).
• Experience managing SEO strategies for large-scale website migrations and redesigns.
• Experience with GEO and AI search optimization for both AI Overviews and LLMs (ChatGPT, Perplexity, Gemini, AI Mode, etc.).
• Experience defining and documenting cross-disciplinary internal processes, playbooks, and best practices to improve search implementation and deliverable quality.
• Deep understanding of search algorithms and ranking factors across modern search ecosystems (traditional search, social search & AI search).
• Proficiency in 3rd party SEO/SEM tools such as SEMrush, BrightEdge, Ahrefs, Screaming Frog, and similar platforms.
• Proficiency in analytics and visualization tools such as Google Analytics, Looker Studio (Data Studio), Adobe Analytics, Google Search Console, Tableau, etc.
• Experience with GEO/AI search tracking tools such as Profound, BlueFish, BrightEdge AI Catalyst, or similar solutions.
• Strong analytical skills, with the ability to interpret data, identify trends, and make data-driven decisions.
• Strong Excel skills (pivot tables, VLOOKUP/XLOOKUP, large datasets) and experience analyzing and reporting on performance data.
• Experience developing and executing search-driven content strategies that improve visibility, traffic, engagement, and conversion.
• Experience testing and leveraging AI to improve search workflows, efficiencies, and quality.
• A proactive, self-starter attitude and a passion for staying current in a rapidly evolving digital landscape.

As a member of the Design team, you'll play a critical role in shaping the experience business owners and aspiring entrepreneurs will have when using Durable. You'll craft beautiful experiences that intelligently and intuitively blend agentic workflows and "traditional" ui.

We're looking for designers who want to push technology while deeply empathizing with real customer problems. You'll work across all teams at Durable to define and deliver what the future of AI UX looks like. You'll be responsible for execution, holding everyone to a high standard of quality.

This is not a role where you'll spend your day in Figma. You'll be prototyping directly with the latest models, experimenting, learning their capabilities, and uncovering powerful opportunities to push innovative UX to our customers.

What we're looking for:

• 5+ years of product design experience on shipped B2C products, with a portfolio you can speak to in depth
• Comfortable producing in code or with AI-assisted coding tools (Cursor, Claude Code, or equivalent)
• Fluent with the current generation of AI creative tooling (image gen, video gen, voice) and opinionated about where they're useful
• Experience designing AI or generative experiences: prompt interfaces, automated output, multi-modal interactions
• Systems thinking: design patterns and component libraries that scaled beyond the features you built them for
• Bonus: you have an eye for exceptional brand design and motion and want to help us push the Durable brand further (in product and across marketing)
• Bonus: startup experience or having launched something of your own

Fine print

This role is based in Vancouver. We currently work in-office two days per week on Mondays & Thursdays. 

Compensation is $150,000–$210,000 CAD base plus equity, for Vancouver-based candidates, depending on seniority. Actual salary takes experience, location, and other factors into account.

ZoomInfo is how businesses go to market (GTM) and we’re on a mission to modernize go-to-market for everyone. Powered by real-time data and insights, our unified GTM intelligence platform helps sales and marketing teams find, acquire, and grow customers. You will lead a team of talented designers, engineers, marketers, and analysts to help build the best product, enabling our customers to unlock insights, engage customers, and win faster.

We're seeking a Principal Product Manager to lead the transformation of ZoomInfo's apps for the era of AI agents and generative AI. In this role, you'll reimagine how go-to-market teams—across sales, marketing, and customer success—discover, engage, and convert their target audiences by leveraging cutting-edge AI technologies to create intelligent, autonomous workflows that power the full revenue lifecycle.

Why ZoomInfo

• Unmatched Data Moat: You’ll build AI on top of the biggest context graph in enterprise - 600+ million contacts, 100m+ companies, 1.5 billion signals. The kind of proprietary foundation that makes AI actually work at scale.
• This Is the Bet: AI is not a side initiative here. It's central to the company's next chapter, with executive sponsorship, dedicated AI/ML engineering teams, and real investment behind it.
• Ship Fast, Learn Fast: We operate with a builder's mentality — rapid experimentation, short feedback loops, and a culture that rewards velocity and iteration over perfection.
• Greenfield Opportunity: You won't be maintaining legacy features. You'll be defining entirely new AI-native experiences for the GTM category, with the autonomy to shape what gets built and how.

What You'll Do

• Own the AI Product Lifecycle: Drive AI-native products from ideation through launch and iteration, leveraging generative AI, autonomous agents, and LLMs.
• Set Vision and Roadmap: Define a compelling vision for how AI agents will reshape GTM workflows and translate it into a strategic, aligned roadmap.
• Engage Customers: Partner with sales, marketing, and CS users to identify where AI-driven automation delivers the most value.
• Measure What Matters: Define and track AI-centric metrics—agent task completion, model accuracy, automation rates—and turn insights into action using tools like Amplitude and Tableau.
• Champion the User: Ensure AI capabilities solve real user problems, not just showcase technical possibilities.
• Lead Cross-Functionally: Rally engineers, AI/ML specialists, designers, and GTM teams to ship intelligent, best-in-class experiences.
• Align Stakeholders: Communicate AI product strategy clearly and compellingly to executives and cross-functional partners through regular written updates.

What You’ll Bring:

• AI Builder at Heart: You don't just manage AI products — you build with them. You vibe code prototypes on weekends, tinker with the latest AI tools for fun, and have a graveyard of side projects to prove it. That hands-on instinct makes you a better PM and a more credible partner to engineering and design.
• AI-Native Mindset: You've built products using LLMs, autonomous agents, and generative AI — and AI is woven into how you think, work, and solve problems. You stay current on emerging capabilities and know how to translate the latest AI advancements into real product value for users.
• GTM Fluency: You know how sales, marketing, and customer success teams actually work — their workflows, tools, metrics, and pain points. You can walk into a room of revenue leaders and immediately earn credibility.
• UX Obsession: You believe AI is only as good as the experience it enables. You have a sharp eye for design and a bias toward simplicity — making complex, intelligent capabilities feel effortless to the end user.

What Does Success Look Like:

• Ship AI-native GTM products: Build on ZoomInfo's context graph and agent platform that don't just keep pace with the competition — they redefine the category.
• Change How People Work: The products you build make GTM professionals measurably more effective. Users don't just adopt them — they can't imagine going back.
• Drive Revenue Impact: Your products aren't science projects. They generate real, measurable revenue growth — through new customer acquisition, expansion, and retention.

How We Work:

• Be Relentless. We will be relentless: when we deliver value to clients; when we compete; when we run into difficult problems. We will outpace and outcompete our competition. We are smart, clever, and resourceful in everything we do. Competing with us for the same customers will be a daunting experience.
• Be Entrepreneurs. Entrepreneurs hustle, move fast, take ownership, they have autonomy, and make decisions. They are accountable, but they do not operate in fear, they aren’t afraid to fail. They are resilient, resourceful, and solutions-oriented - even when conditions say otherwise. We will entrust, and expect, our leadership and our teams to operate as entrepreneurs.
• Be Experts. Winning for our customers requires that we understand them deeply. Winning for our business requires us to be experts in our domain areas. Great companies solve complex and costly problems for their customers - you can’t do this without being an expert in your customers’ day to day workflow. We will demand this level of customer and business expertise from everyone at the company.
• Be Innovators. Innovating is who we are, it is how we have gotten here. But not just with our product and how we define what GTM means for the future. We innovate to be leaner and more efficient in the way we operate, we will find ways to drive outcomes no one thought were possible - from marketing and lead generation to legal, finance, and procurement. Through innovation, we will set a new standard for how great companies operate with discipline.
• Be a Team. We can’t win if we act like a random assortment of siloed groups. We are one team, working together to win. We collaborate and lean in to help each other.

#LI-RB1  #LI-hybrid  #LI-remote

High-Level Overview

Benevity is hiring a Growth Marketing Manager to own paid media and organic discovery as a connected growth engine, with a strong focus on account-based marketing (ABM) and strategic accounts. This role will report to the Sr. Manager, Digital Marketing on Benevity’s Growth Marketing team.

This role is responsible for building awareness with Tier 1 and Tier 2 target accounts, capturing intent signals, and influencing pipeline through integrated paid media, SEO, AEO and GEO strategies. This role is ideal for a hands-on marketer who wants to learn fast, test aggressively and grow into broader ownership, while partnering closely with sales, product marketing, marketing ops and ABM stakeholders.

What you'll do:

Paid media 

• Plan, execute, and optimize paid media programs across:
• Paid search
• Paid social (especially LinkedIn)
• Retargeting
• Prioritize Tier 1 and Tier 2 target accounts and high-intent audiences
• Balance awareness, intent capture, and efficiency across long sales cycles
• Monitor performance daily and proactively course-correct inefficiencies
• Partner with sales and ops to improve lead quality and pipeline influence

Organic search (SEO, AEO, GEO)

• Support and execute organic discovery strategy, including:
• SEO fundamentals
• Answer Engine Optimization (AEO)
• Generative Engine Optimization (GEO)
• Optimize content to answer buyer questions clearly and accurately
• Help ensure Benevity appears favorably in AI-powered search experiences
• Partner with content and product marketing to structure content for authority and trust
• Identify keyword gaps and provide recommendations for new, high-authority content

Measurement, learning & optimization

• Track performance against baselines and identify trends over time
• Measure success beyond traffic and CPL, including:
• Qualified leads
• Pipeline influence
• Account warming signals
• Contribute to dashboards and reporting in HubSpot
• Turn insights into clear, actionable recommendations and drive follow-through on next steps

Experimentation & Growth

• Run structured experiments to identify what works and why
• Test new:
• Audiences
• Ad formats
• Content structures
• Messaging hypotheses
• Use winning insights to drive core strategy while maintaining testing momentum
• Help evolve strategy toward an 80/20 performance-to-experimentation model

Cross-functional partnership

• Work closely with:
• Demand Gen/ABM team on campaign strategy and execution
• Sales and BDR teams on account priorities and feedback
• Marketing Ops on attribution, tracking and data quality
• Communicate clearly when inputs or alignment are missing

What you'll bring:

• 3–5 years of experience in growth, performance or digital marketing
• Hands-on experience managing paid media campaigns
• Working knowledge of SEO fundamentals
• Strong analytical and problem-solving skills
• Comfort working with performance data and dashboards
• Ability to communicate clearly about what’s working and what’s not
• Exposure to long sales cycles and account-based marketing
• Ideal tech stack experience: HubSpot, 6Sense, Google Ads, Google Search Console, LinkedIn Ads, YouTube, Semrush, Hockeystack

At Robots & Pencils, we build meaningful, scalable digital products that solve real business problems. We are looking for a Staff Product Manager who combines deep Generative and Agentic AI fluency with hands-on building ability to own AI product outcomes end-to-end. As a Staff PM, you're accountable for initiative-level outcomes, stakeholder satisfaction, and contributing to R&P's AI product practice. You think in systems, work backwards from the customer problem, and stay relentlessly curious about what's next in AI

Enterprise clients want to deploy Agents -  moving from a promising demo to a production system that works at scale, meets security and compliance requirements, and delivers measurable business value is hard. This role owns that problem. You'll be part of a GenAI initiative within the AWS ecosystem, building the evals, tools, patterns, and reference architectures that make AI deployment repeatable.  The mindset: prove it works, test assumptions early, and document while building.

Key Responsibilities

Product Strategy & AI Vision

• Define and drive the product vision, strategy, and roadmap for GenAI solutions - with agentic AI (agent orchestration, tool use, multi-step workflows) as the primary focus - connecting AI capabilities to enterprise business outcomes
• Translate enterprise problems into structured product requirements; reframe feature requests into outcome-driven priorities with explicit tradeoffs on invest in vs. defer
• Balance near-term deployment milestones with long-term platform scalability and sustainability
• Monitor the competitive GenAI landscape and emerging agentic patterns to inform roadmap and technology decisions

Discovery & Validation

• Research how enterprise users interact with AI agents and where they lose trust; frame the riskiest assumptions as testable hypotheses and de-risk them first
• Design and run experiments - POCs, pilot deployments, scenario-based testing of multi-step workflows, edge cases, and failure recovery - to validate agentic solutions where non-deterministic output makes traditional QA insufficient
• Distill research, experiments, and competitive intelligence into clear insights that pave the path for a successful product
• Agent Design, Prototyping & Production
• Define agent behavior and prototype system prompts and tool schemas; partner with engineering on context management - summarization, working memory, and information flow across multi-step tasks
• Drive multi-model architecture tradeoffs with engineering - define the quality, cost, and latency targets that determine which model serves each step in the agent workflow
• Build AI prototypes to validate hypotheses; define human-in-the-loop boundaries and guardrails - when the agent acts autonomously, when it escalates, and how to handle non-deterministic output
• Establish agent evaluation frameworks - task completion, reasoning quality, tool selection, failure recovery, safety - and partner with engineering on production readiness (observability, drift, responsible AI, prompt versioning)
• Define success metrics at the agent level - task completion rate, cost per task (not per inference), escalation rate, time to resolution, and customer trust alongside business KPIs
• Delivery & Execution
• Own the end-to-end product lifecycle from discovery through phased rollouts; establish the metrics framework (north star, input, guardrail metrics) and report product impact to leadership
• Manage the product backlog, scope, dependencies, and risks; drive agile ceremonies and produce high-quality PRDs, product briefs, and decision logs
• Evaluate technology and platform decisions from a product perspective; create deployment playbooks, reference architectures, and knowledge transfer materials so teams sustain solutions independently
• Use AI to accelerate product work - research, analysis, prototyping, documentation - with judgment on when it needs human oversight; onboard rapidly to new domains and support team members across the initiative

Stakeholder Management

• Build trusted relationships with stakeholders and executives; serve as the go-to product advisor and primary contact for AI product direction and deployment strategy
• Partner with AWS Solution Architects and account teams to align on technical approach, service selection, and go-to-market for GenAI solutions
• Manage expectations on scope, timelines, and tradeoffs; facilitate decisions across competing priorities using data, alternatives, and clear rationale
• Frame AI capabilities and limitations for non-technical stakeholders - manage hype cycles, set realistic expectations; surface unmet needs that deepen relationships and grow the account

Required Skills

• 8-12+ years in product management, forward deployment, or solutions engineering; must have shipped AI products from prototype through production at scale
• Strong product sense - ability to identify what matters to users and the business, make prioritization calls with incomplete information, and shape products that deliver real outcomes
• Deep GenAI fluency - LLMs, RAG, fine-tuning, prompt engineering, context engineering, evals - with hands-on experience building or shipping agentic systems (planning, tool use, HITL, guardrails)
• Proven ability to prototype AI solutions using AI tools (Cursor, Claude, Copilot) to validate hypotheses and de-risk product decisions
• Experience deploying AI solutions in enterprise environments with strong technical fluency - can read code, evaluate architectures, make product tradeoffs on technical constraints, and drive scalable deployment patterns
• Exceptional communicator - clear PRDs, technical specs, and decision logs; has led AI products through full lifecycle and driven alignment with Directors, VPs, and C-level
• Comfortable operating in ambiguous, fast-moving environments where the AI landscape evolves weekly
• PM-level fluency across the AWS AI ecosystem - Bedrock, AgentCore, SageMaker, Strands, Kendra, OpenSearch, Lambda, Step Functions - to make informed product and architecture decisions

Preferred Qualifications

• Software engineering or coding background (Python, JavaScript, TypeScript)
• Agency or consulting delivery experience
• Experience in Financial Services, Healthcare, or Life Sciences industries
• Familiarity with open-source LLM ecosystem (Llama, Mistral) for flexibility and cost optimization
• Prior experience leading time-boxed discovery initiatives or technical spikes with rapid validation cycles

Why Join R&P?

You'll work at the intersection of cutting-edge AI and real enterprise impact - helping clients deploy Generative and Agentic AI solutions that change how their businesses operate. R&P gives you the variety of consulting (new problems, new industries, new tech) with the depth of a product role - you'll build, ship, and measure, not just advise. The team is collaborative, technically sharp, and genuinely invested in doing great work for clients.

About The Team 

Cerebras builds wafer-scale AI processors—single chips delivering tens of PB/s of memory bandwidth and a dataflow architecture that accelerates at a granularity no multi-device system can match. The Advanced Technology Group (ATG) is Cerebras’ pathfinding organization. We work ahead of product to explore new architectures, demonstrate breakthrough performance on scientific and AI workloads, and shape the technical roadmap for future Cerebras hardware and software. Our work regularly appears at top-tier venues (Supercomputing, SIAM, IEEE, and NeurIPS) and directly influences the design of next-generation wafer-scale systems. 

About The Role 

We are seeking Compiler Engineers to join a small team of specialists working on our emerging Tungsten language compiler. Tungsten is Cerebras’ dataflow programming language, purpose-built for wafer-scale hardware. You will work on the Tungsten compiler from language design through code generation, building the toolchain that translates high-level intent into efficient execution across hundreds of thousands of cores with a memory and interconnect model unlike anything in conventional computing. 

This is not incremental work on an existing backend. The architecture is new, the programming model is new, and the compiler is where those two things meet. You will collaborate closely with Cerebras’ ASIC, kernel, and AI teams, and your design decisions will directly shape both the language and the hardware it targets. Beyond the compiler itself, the broader toolchain—runtime, debugger, simulator—is still being built, and we are equally interested in engineers who want to own those pieces of the developer experience on novel hardware. 

What You Will Do 

• Design and implement compiler passes across the Tungsten toolchain: mid-end optimization, backend code generation, instruction scheduling, register allocation, assembler, and linker. 
• Co-design language constructs that improve expressiveness and performance for dataflow execution on wafer-scale hardware. 
• Develop and iterate on code generation strategies for complex scientific and AI workloads, analyzing performance bottlenecks and closing the gap between peak and achieved throughput. 
• Extend the compiler to support future hardware architectures as they move from design to silicon. 
• Work directly with ASIC architects and application researchers to inform hardware-software co-design decisions. 

What We Are Looking For

• PhD in Computer Science or Computer Engineering preferred; exceptional candidates without a graduate degree who demonstrate equivalent depth through published research, significant open-source contributions, or a strong industry track record are encouraged to apply. 
• Substantial experience in compiler development: IR design, optimization passes, code generation, or backend implementation for novel or non-standard architectures. 
• Strong grasp of computer architecture: instruction sets, memory models, dataflow execution, and how hardware constraints shape compilation strategy. 
• Systems-level programming ability in C; comfort reasoning about performance at the instruction and memory-access level. 
• Ability to think about compilation as a design problem, not just an implementation task: you should have opinions about how language semantics, compiler IR, and hardware capabilities interact. 
• Excellent communication and interpersonal skills: able to work effectively in a small, fast-moving team where compiler, architecture, and application concerns are deeply intertwined. 

Valuable Assets 

• Experience with compilers for spatial, dataflow, or CGRA architectures where the compilation model diverges significantly from conventional CPU/GPU targets. 
• Exposure to ML compiler frameworks (MLIR, XLA, TVM) and understanding of how AI workloads map to hardware. 
• Experience with multi-dimensional data representations, tiling strategies, and vectorized operations. 
• Track record of published research or patents in compilers, programming languages, or architecture. 
• Experience building runtime systems, debuggers, or architecture simulators, particularly for non-standard hardware. 
• Understanding of parallel/distributed systems and cluster computing. 

Why This Opportunity Is Exciting And Unique 

• Build a compiler for hardware that doesn’t exist anywhere else. The architecture is the constraint and the opportunity. 
• Publish and open-source your research. We present at Supercomputing, SIAM, IEEE, NeurIPS, and beyond. 
• Work on the fastest AI system in the world, with direct access to the hardware your compiler targets. 
• Join at a pivotal moment: Cerebras is pre-IPO with strong commercial traction and rapid growth. 
• Be part of a small, technical team with high autonomy, minimal bureaucracy, and a culture that values depth over hierarchy. 

We are hiring for multiple positions across experience levels. If this work resonates, we encourage you to apply. 

About The Team 

Cerebras builds wafer-scale AI processors—single chips delivering tens of PB/s of memory bandwidth and a dataflow architecture that accelerates at a granularity no multi-device system can match. The Advanced Technology Group (ATG) is Cerebras’ pathfinding organization. We work ahead of product to explore new architectures, demonstrate breakthrough performance on scientific and AI workloads, and shape the technical roadmap for future Cerebras hardware and software. Our work regularly appears at top-tier venues (Supercomputing, SIAM, IEEE, and NeurIPS) and directly influences the design of next-generation wafer-scale systems. 

About The Role 

We are seeking R&D Engineers to join Cerebras' Advanced Technology Group. You will design and implement workloads that establish new performance benchmarks on wafer-scale hardware, leveraging architectural features that no traditional platform offers. The 
scope ranges from large-scale scientific simulations to emerging AI/ML models, and the work sits at the intersection of algorithm design, compiler co-optimization, and hardware architecture. You will collaborate closely with Cerebras’ ASIC, compiler, kernel, and AI teams as well as external partners at universities and national laboratories. 

What You Will Do 

• Design and implement challenging scientific computing and AI workloads on Cerebras’ Wafer-Scale Engine, targeting performance results that advance the state of the art. 
• Lead algorithm–hardware co-design efforts with internal R&D teams and external research partners, turning architectural capabilities into measurable application-level advantages. 
• Build analytical performance models that quantify bottlenecks, guide optimization, and inform future chip and compiler design decisions. 
• Contribute to Cerebras’ multi-year technology roadmap by identifying high-impact workloads, proposing architectural experiments, and validating them on silicon. 
• Publish findings and present at top-tier conferences and journals; represent Cerebras in the broader HPC and AI research communities. 

What We Are Looking For 

• PhD in Computer Science, Engineering, Applied Mathematics, Physics, or a related quantitative field preferred. Exceptional candidates without a graduate degree who demonstrate equivalent depth through published research, significant open-source contributions, or a strong industry track record are encouraged to apply. 
• Deep experience in at least one of the following: computer architecture and accelerator design; parallel, distributed, or high-performance computing; numerical methods and scientific simulation; AI/ML theory and model design at a mathematical level. 
• Strong ability to analytically model and optimize the performance of complex systems and algorithms. 
• Track record of published research or patents in relevant venues. 
• Proficiency in C and Python; comfort working close to hardware. 
• Excellent communication and interpersonal skills: able to present complex technical material to both specialist and cross-functional audiences, and to collaborate effectively in a fast-paced, small-team environment. 

Areas Of Particular Interest 

We are hiring across several focus areas. Exceptional depth in one or more of the following is a strong signal: 

• Computational science: researchers who can bring insights from numerical methods and simulation into AI, or couple simulation and learning into joint computational workflows. Depth in hydrodynamics, solid mechanics, electromagnetics, molecular dynamics, or related PDE-based fields. 
• AI/ML foundations: deep understanding of model architecture, optimization methods, and their statistical underpinnings—the ability to design from first principles, not just apply established recipes. 
• Computer architecture: microarchitecture design, computing paradigms at the circuit and datapath level, memory hierarchy design. 
• Performance engineering: roofline modeling, bandwidth analysis, kernel optimization, communication-computation overlap, and compiler-level tuning for novel hardware. 

Why This Opportunity Is Exciting And Unique 

• Build on a fundamentally different architecture, unconstrained by GPU assumptions. 
• Publish and open-source your research. We present at Supercomputing, SIAM, IEEE, NeurIPS, and beyond. 
• Work on the fastest AI system in the world, with direct access to the hardware your compiler targets. 
• Join at a pivotal moment: Cerebras is pre-IPO with strong commercial traction and rapid growth. 
• Be part of a small, technical team with high autonomy, minimal bureaucracy, and a culture that values depth over hierarchy. 

We are hiring for multiple positions across experience levels. If this work resonates, we encourage you to apply. 

About The Team 

Cerebras builds wafer-scale AI processors—single chips delivering tens of PB/s of memory bandwidth and a dataflow architecture that accelerates at a granularity no multi-device system can match. The Advanced Technology Group (ATG) is Cerebras’ pathfinding organization. We work ahead of product to explore new architectures, demonstrate breakthrough performance on scientific and AI workloads, and shape the technical roadmap for future Cerebras hardware and software. Our work regularly appears at top-tier venues (Supercomputing, SIAM, IEEE, and NeurIPS) and directly influences the design of next-generation wafer-scale systems. 

About The Role 

Most AI research today is shaped by the constraints of existing hardware. This role starts from the other direction: what would you build if the architecture let you rethink the fundamentals? You will design and develop AI models and training methodologies on wafer-scale hardware, working at the level of optimization theory, model architecture, and statistical foundations rather than assembling existing components. 

The ATG sits at the intersection of AI, computational science, and computer architecture, and your work will draw on all three. You will collaborate closely with Cerebras’ ASIC, compiler, kernel, and AI teams as well as external partners at universities and national laboratories. 

What You Will Do 

• Design AI models and training methods from first principles, leveraging architectural properties of wafer-scale hardware that are unavailable on conventional platforms. 
• Investigate how techniques from computational science—numerical methods, PDE solvers, simulation—can inform and advance AI model design, and explore hybrid workflows that couple simulation and learning. 
• Develop a deep understanding of the hardware substrate and use it to guide algorithmic choices: model structure, optimization strategy, memory access patterns, numerical precision. 
• Publish findings and present at top-tier venues (NeurIPS, ICML, ICLR, etc.); represent Cerebras in the broader AI/ML research community. 
• Inform the design of future Cerebras hardware and software by identifying the computational patterns that matter most for next-generation AI workloads. 

What We Are Looking For 

• PhD in Machine Learning, Computer Science, Applied Mathematics, Statistics, Physics, or a related quantitative field preferred; exceptional candidates without a graduate degree who demonstrate equivalent depth through published research, significant open-source contributions, or a strong industry track record are encouraged to apply. 
• Mathematical maturity: comfort with the theory behind gradient methods, loss landscapes, generalization, and the relationship between model structure and data statistics. 
• Track record of published research at top-tier AI or computational science venues. 
• Proficiency in Python and PyTorch; comfort with C or other low-level languages is a strong signal. 
• Excellent communication and interpersonal skills: able to present complex technical material to both ML and systems audiences, and to collaborate effectively in a fast-paced, small-team environment. 

Why This Opportunity Is Exciting And Unique 

• You will have direct access to hardware that changes what’s algorithmically possible. Tens of PB/s of memory bandwidth and fine-grained dataflow execution open design spaces that don’t exist on GPU clusters. 
• You will work alongside researchers in computational science, computer architecture, and performance engineering. The synthesis across these fields is central to ATG’s approach. 
• Your research will influence silicon - ATG’s findings directly shape the design of future Cerebras chips and systems. 

We are hiring for multiple positions across experience levels. If this work resonates, we encourage you to apply. 

P-1381

At Databricks, we are passionate about enabling Data & AI teams to solve the world's toughest problems - from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers, we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for data interaction to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

About the Team:

The Backline Engineering Team serves as the critical bridge between Frontline Support and Engineering. We handle complex technical issues and escalations across the Data and AI ecosystem. With a strong focus on customer success, we are committed to delivering exceptional customer satisfaction by providing deep technical expertise, proactive issue resolution, and continuous platform improvements. We emphasise automation and tooling to enhance troubleshooting efficiency, reduce manual efforts, and improve the overall supportability of the platform and the health of our products. By developing smart solutions and streamlining workflows, we drive operational excellence and ensure a delightful experience for both customers and internal teams.

What your impact will be:

• Deep Dive Troubleshooting: Conduct deep-dive forensics into Spark core internals and the broader Databricks Data and AI ecosystem to resolve high-priority architectural failures and complex system anomalies.
• Root Cause Analysis: Perform advanced code-level analysis and resource profiling to identify and mitigate systemic root causes, ensuring the stability and reliability of high-scale production workloads.
• Architectural Optimization: Optimise architectural performance across the Data and AI stack by refining execution parameters and enforcing best practice strategies to maximise resource efficiency and throughput.
• Product Improvements: Analyse global issue trends and patterns to partner directly with Product Engineering, influencing the product roadmap and driving initiatives that enhance long-term supportability.
  Scalability & Tooling: Develop reproduction frameworks, automated workflows, and AI-driven diagnostic tools that translate complex backline findings into standardised resolution paths to empower and scale the broader organisation.

What we look for:

We are looking for customer-obsessed candidates with 10+ years of relevant experience, including deep expertise in one of the following three specialized tracks, along with proven experience in managing both customers and technical stakeholders. Since each track calls for a different set of technical capabilities, we’re looking for excellence in one area rather than proficiency in all: 

• Data Engineering Track: Expertise in large-scale big data solutions and ETL pipelines using Spark, Delta Lake, or Hive. Strong experience troubleshooting failures, diagnosing performance issues, and identifying root causes. Demonstrated problem-solving ability and understanding of data engineering best practices to ensure reliable, efficient workflows. Solid hands-on programming skills in Python, SQL, or Scala.
• Product Supportability Track: Deep understanding of distributed system internals. Ability to perform code-level root-cause analysis and profiling (using metrics and heap/thread dumps) in Java, Scala, or Python. Proven record of contributing to bug fixes and mentoring other engineers.
• AI Track: Experience with large-scale machine learning and generative AI systems, including LLM-based applications and agent-driven workflows. Strong grasp of model training, evaluation, and deployment in distributed environments. Experience managing the ML lifecycle, including governance and operationalisation. Skilled in diagnosing and optimising distributed ML workloads for performance and scalability.

Location: US or Canada
Type: US Applicants - Full-Time; Canadian Applicants - Independent Contractor

About Human Agency

We’re scaling rapidly and have a growing pipeline of opportunities that demand exceptional talent across disciplines. Our mission is to bring on individuals, from creative producers to technical experts to entrepreneurial leaders, who can help us realize this next chapter of growth.

We are a company of doers. Leaders roll up their sleeves, teams work flat, and everyone contributes to what ships. Titles don’t insulate us from feedback or basics. We invite critique, learn quickly, and keep raising the bar. The best ideas win here, no matter where they come from, because clients trust us to deliver the strongest outcomes every time.

Our clients’ missions, products, and bottom lines are sacred. We immerse ourselves in their world, becoming stewards of their goals and partners in solving big problems. Every product, strategy, or asset we create must be both beautiful and functional; practical, usable, and designed for real-world impact.

Humans are our most valuable resource, and we only grow by hiring people who push us forward. Across strategy, engineering, design, data, and operations, we seek out teammates who raise the bar and make us better. Always hire up, never down.

We partner with organizations of all sizes to explore, design, and implement AI strategies that are secure, scalable, and human-centered. We believe AI should amplify human potential, not replace it and we build with that conviction in every engagement. From advisory and tooling to implementation and education, we meet clients where they are at and help them integrate AI in ways that align with their mission and values. Our goal is to empower teams to work smarter, move faster, and unlock new possibilities through thoughtful, responsible innovation.

And through it all, we lead with purpose, love, and adventure. We do meaningful work with people we care about, and we make the ride an adventure worth taking. Because at Human Agency, who we are and how we work are one and the same.

The Opportunity

At Human Agency, we are shaping the future by combining cutting-edge AI solutions with intuitive software development. We specialize in building scalable and secure SaaS applications that empower enterprise clients to solve complex problems efficiently. As part of our team, you'll work on high-impact projects at the intersection of AI, machine learning, and secure software engineering.

We’re seeking a Senior Full-Stack Engineer to join our growing team. In this role, you'll lead development initiatives, contribute to our SaaS products, and tackle exciting challenges in backend architecture, frontend design, and AI/ML integrations with a particular focus on generative AI technologies.

Responsibilities

SaaS Application Development

• Detection:
• Develop backend algorithms to process articles, chunk content, and integrate with LLMs for predictive text generation.
• Build APIs and services to manage and scale the application’s content workflow.
• Protection:
• Create secure PDF upload workflows with encryption to ensure compatibility with Adobe Acrobat.
• Integrate authentication mechanisms like Okta for enterprise customer admin management.
• Enable data recovery, auditing capabilities, and enterprise-grade administrative tools.

AI/ML and Algorithm Development

• Collaborate with AI/ML teams to operationalize models such as OCR (Optical Character Recognition) and generative AI-based solutions (e.g., GPT models).
• Implement RAG (Retrieval-Augmented Generation) use cases using vector databases and data embedding techniques to enhance application functionality.
• Design workflows for large-scale data processing that enable efficient AI integrations and create dynamic AI-first features, such as custom GPTs tailored to enterprise needs.

DevOps & Operationalization

• Establish CI/CD pipelines and formal release structures for software delivery.
• Conduct security evaluations to identify vulnerabilities and optimize performance across AI-driven SaaS applications.
• Manage infrastructure and workflows for custom AI solutions, including tools like Snowflake and LangChain.

Future-Focused Development

• Build integrations and proof-of-concept applications leveraging company-specific datasets and AI technologies.
• Evaluate and implement tools for classification, indexing, and secure data management that incorporate the latest in generative AI advancements.
• Support the development of enterprise-grade AI solutions, including internal AI models and custom LLMs.

Requirements

Core Technical Skills

• Proficiency in Python and Ruby on Rails, with significant backend experience.
• Experience in designing secure systems, including encryption workflows and document protection mechanisms.
• Hands-on expertise in integrating generative AI tools, such as OpenAI APIs, LangChain, or Hugging Face frameworks, into SaaS applications.
• Strong knowledge of RAG techniques, vector databases (e.g. Pinecone, Weaviate), and embedding pipelines.
• Ability to operationalize AI/ML models and build workflows for enterprise clients.
• Frontend development experience in modern frameworks (e.g, React, Vue), with the ability to assess and recommend appropriate tech stacks.

Nice-to-Have Skills

• Computer vision and OCR expertise, especially for processing and indexing complex document workflows.
• Experience with authentication systems (e.g., Okta) and enterprise administrative tools.
• Experience in DevOps, CI/CD pipelines, and secure release management.
• Background in security evaluations, vulnerability assessments, and tool integrations.

Other Requirements

• Strong testing background with experience in automated and manual testing.
• Ability to manage data recovery, audits, and compliance workflows.
• Strong problem-solving and analytical skills, with attention to detail in complex environments.
• Excellent communication skills and the ability to work collaboratively across teams.

Why Join Us?

• Be part of a cutting-edge team solving complex problems in AI and SaaS development.
• Work on impactful projects with enterprise clients and cutting-edge technologies.
• Grow your career in a collaborative, innovative, and supportive environment.

If you're excited about working on secure, scalable systems while integrating advanced AI and ML capabilities, we’d love to hear from you.

Equal Opportunity Commitment

Human Agency is an Equal Opportunity Employer. We value diverse backgrounds and strive to build an inclusive culture where everyone feels welcomed and empowered.

This role sits at the intersection of AI engineering and application development. You’ll build customer-facing features from scratch, while also helping us integrate and scale the AI infrastructure that power them. You're deeply fluent in TypeScript and React, strong enough on the backend to own a feature end-to-end, and have meaningful experience building AI applications. You craft fast, polished, reliable software and you're drawn to problems that are genuinely unsolved.

We're looking for full stack engineers and those who lean more towards frontend.

Full stack. You understand applied AI well past the API layer: building systems that stay reliable when the model is unpredictable, writing evals that surface real signal, designing agentic workflows that hold up under production conditions. You've shipped RAG, tool calling, memory, or multi-agent patterns to real users and you know where each one breaks down.

Frontend. You notice things other engineers don't. The easing curve that's slightly off. The transition that happens too fast to register. The empty state that was clearly an afterthought. In a product where AI does most of the heavy lifting, the interface is where trust is built or broken — and you hold that line. You've built design systems from the ground up and have a point of view on motion, interaction, and what makes an AI-generated surface feel considered rather than random.

What we look for

• Production-grade React, NextJS, and TypeScript
• Strong backend experience: async systems, API design, schema decisions, scaling under real load
• For full stack: applied AI in production like RAG, tool calling, memory, multi-agent patterns, and the ability to write evals and reason about whether a system is actually improving
• For frontend: design systems, animation and motion, data-fetching patterns (TanStack Query, tRPC), and deep care for browser fundamentals and performance
• Familiarity with our infrastructure and AI tooling (Cloudflare Workers/Durable Objects, Postgres + PGVector, LangSmith, Inngest) is a plus

What success looks like

Features that are fast, reliable, and polished. Architectural and interaction decisions that make the next thing faster to build. You raise the bar for the people working alongside you.

Application process

Your works speaks louder than your resume. We want to see how you think, what you've made, and how you work with AI. Our application asks for three things:

1. A Loom video (2-3 minutes)

Tell us who you are, what you're working on or have recently built, and how AI is a core part of how you work. Don't script it. We want to see how you think out loud.

2. Something you've built or designed 

A link, a side project, a campaign. Anything that shows what you're capable of making. One strong example beats ten weak ones.

3. A few short questions

1. Why Durable 
2. Where are you located
3. What are your salary expectations

Fine print

We are a Vancouver-based company and candidates need to be based in Canada. Remote is fine - you can expect travel to Vancouver once per quarter (minimum) to work in-office with the team. 

Compensation is $180,000–$225,000 CAD base plus equity, for Vancouver-based candidates. Actual salary takes experience, location, and other factors into account.

Tech stack 

Languages: Typescript, SQL, Bash, HTML5, CSS3, Python

Frameworks/Libraries: React, NextJS, React Query, React Native, Expo, TailwindCSS, RadixUI, DrizzleORM, trpc, NodeJS, Bun, WebRTC, PyTorch

Tooling: Turborepo, ESLint, Prettier, NPM/PNPM, Git, AI codegen

Databases: Postgres (including PGVector and JSON datatype), Object stores

Infrastructure: Docker, Cloudflare (Workers, Durable Objects, Pages, DNS, CDN), Vercel, Inngest, Render, Trigger.dev, Datadog, Together.ai, LangSmith, Hugging Face, Replicate, Langfuse

AI engineering: Large Language Models, Multi-Modal Models, Image Generation, In-painting, Voice Models

AI concepts (learn over time): Basic Prompting, Chain of Thought prompting, N-shot prompting, Prompting reasoning models, Tool calling, Preprocessing unstructured data, ReAct, Agent basics, Advanced agentic patterns, Evals, Memory, Generative UI, Streaming, Real-time, Multi-agent systems, Guardrails, Citations, Vector databases, RAG, Text embeddings, Knowledge graphs, Query routing, Synthetic data, Fine-tuning, RLHF, Diffusion Models, MCP, Computer use, Using/Serving Multi-modal OSS models

About this position:

We’re looking for a Machine Learning Infrastructure Engineer to join our growing Data & Platform team and build the foundation that powers our AI and machine learning capabilities across Later’s product portfolio. As our first dedicated ML Infrastructure Engineer, you will own the systems that support model experimentation, training, deployment, and monitoring at scale.

This role is critical to accelerating our data science initiatives and enabling future AI innovation. You’ll design and operate reliable, secure, and scalable ML infrastructure that empowers data scientists and engineers to ship high-impact models with confidence. If you’re excited about building robust ML systems in a fast-moving environment—and want to define the standard for ML Ops at Later—this is your opportunity.

What you'll be doing:

Strategy

• Define and own the long-term ML infrastructure roadmap, ensuring it supports both current experimentation needs and future AI initiatives.
• Establish best practices for model lifecycle management, deployment standards, monitoring, and governance. 
• Identify infrastructure gaps and proactively design scalable solutions to enable high-velocity ML development.
• Contribute to cross-functional technical planning, ensuring ML systems align with product and platform strategy.

Technical/ Execution

• Design, build, and maintain production-grade model deployment and inference systems using CI/CD pipelines, containerized services (Docker), and API frameworks (e.g., Flask).
• Automate end-to-end ML lifecycle workflows including training pipelines, model validation, registry management, deployment, and rollback strategies.
• Implement robust monitoring systems for model performance, latency, drift detection, and infrastructure health using tools such as CloudWatch, Prometheus, and Grafana.
• Operate across AWS and GCP environments to manage training and inference workloads, including GPU-based infrastructure and BigQuery datasets.
• Develop and maintain infrastructure-as-code (Terraform, CloudFormation) to ensure scalable, repeatable, and secure cloud environments.
• Implement and optimize CI/CD workflows (e.g., GitHub Actions, GitLab CI, Bitbucket Pipelines) for ML and infrastructure automation.

Team / Collaboration

• Partner closely with Data Scientists, Analysts, Platform Engineers, and Product Engineers to support end-to-end ML workflows.
• Translate data science experimentation needs into production-ready infrastructure solutions.
• Serve as the technical bridge between ML experimentation and productized deployment.
• Share knowledge and best practices to elevate ML maturity across teams.

Research/Best Practices

• Stay current on emerging ML Ops practices, tools, and frameworks to continuously improve system reliability and efficiency.
• Evaluate and implement model-serving frameworks (e.g., TorchServe, Seldon, TensorRT) where appropriate.
• Contribute to governance, reproducibility, and auditability standards for ML systems.
• Experiment with new tooling and workflows to improve reproducibility, performance, and developer velocity.

What success looks like:

• ML models move from experimentation to production quickly and reliably, with minimal manual intervention.
• CI/CD pipelines enable safe, repeatable deployments with clear rollback strategies.
• Model performance, drift, and infrastructure health are proactively monitored and observable.
• Infrastructure supports scalable GPU training and real-time inference without bottlenecks.
• Data scientists report improved velocity, reproducibility, and confidence in deploying models.
• ML systems are secure, compliant, and aligned with evolving product and AI strategy.

What you bring:

• 4+ years of experience in ML Ops, ML infrastructure, backend engineering, or related roles supporting production ML systems.
• Experience working in cloud-native environments (AWS and/or GCP) with hands-on deployment of ML workloads.
• Proven track record designing and implementing CI/CD pipelines for ML systems.
• Strong experience with Amazon SageMaker, Docker, Flask-based APIs, and infrastructure automation tools.
• Hands-on experience with ML lifecycle tooling such as MLflow, SageMaker Studio, or Weights & Biases.
• Experience managing container orchestration platforms (Kubernetes, EKS, or GKE).
• Strong programming experience in Python (additional experience in Go, Java, or Scala is a plus).
• Experience working with infrastructure-as-code tools such as Terraform or CloudFormation.
• Familiarity with observability tools such as CloudWatch, Prometheus, Grafana, Datadog, or centralized logging platforms.
• Experience managing GPU-based workloads and scaling training/inference systems.
• Familiarity with data infrastructure tools such as BigQuery and cloud-native data pipelines.
• Bonus: Experience supporting LLMs or generative AI pipelines, distributed training systems, feature stores (e.g., Feast), real-time inference systems, or ML governance frameworks.
• A mindset focused on automation, reliability, performance, and continuous improvement in fast-scaling environments.

How you work: 

• Driven by Impact: You deliver results that matter—prioritizing high-value work, meeting deadlines, and adapting quickly while keeping outcomes clear.
• Strategic & Customer-Centric: You anticipate risks and opportunities, connect decisions to long-term growth, and build trust through proactive insights.
• Curious & Growth-Oriented: You seek knowledge, ask sharp questions, and apply learnings fast—challenging the status quo with a mindset of improvement.
• Collaborative & Resilient: You thrive in change by staying resourceful, solution-focused, and positive—removing roadblocks, sharing insights, and keeping morale high.
• Accountable & Honest: You own your work, hold yourself and others to a high bar, and use transparent feedback to drive growth.
• Emotionally Intelligent: You build trust through empathy and collaboration, foster inclusion, and inspire others with grit, optimism, and integrity.

Our approach to compensation:

We take a market-based & data-driven approach to compensation. We leverage data from trusted third-party compensation sources to help us understand the market value of a role based on function, level, geographic location, and scope. We evaluate compensation bi-annually, including performance and market-related factors.

Our salaries are benchmarked against market Total Cash Compensation for the geographic location of our job posting. Compensation for some roles is structured as On Target Earnings (OTE = base + commission/variable) while for others it is structured as Salary only.

To comply with local legislation and ensure transparency, we share salary ranges on all job postings. Skills, experience and other factors help determine the final salary we offer which may vary from the original range posted. 

Additionally, all permanent team members are eligible to participate in various benefits plans as part of their overall compensation package.

Salary Range: 

$ 145,000 -165,000 CAD

#LI-Hybrid 

About this position:

We’re looking for a Senior SEO Manager to lead Later’s organic growth engine and drive measurable impact across demand generation. In this role, you’ll be both a strategic leader and a hands-on practitioner—developing and executing SEO strategies that grow qualified traffic, improve conversion rates, and strengthen Later’s authority in the creator and social media space.
Reporting to the VP of Demand Generation, you’ll own Later’s SEO roadmap, partner cross-functionally with Web, Product Marketing, and Content teams, and set high standards for technical and content-driven SEO execution. This is a critical, high-visibility role across all lines of business (Later Influence, Later Social, and Mavely) with direct impact on revenue growth and regular exposure to senior leadership. 

What you'll be doing:

Strategy

• Own Later’s full SEO strategy across technical, on-page, content, off-site, and AI search to drive sustainable, high-quality organic growth across all three lines of business.
• Define SEO goals, KPIs, and reporting frameworks that connect performance to revenue growth.
• Provide actionable insights to Demand Gen, the broader marketing team, and senior leadership on trends, opportunities, and performance.

Technical/ Execution

• Lead keyword research, content gap analysis, SERP opportunity assessments, and AI search opportunities to inform actionable strategy.
• Create and deliver SEO-driven content plans, including briefs, page structures, and leveraging proprietary data for E-E-A-T methodology.
• Execute advanced on-page optimizations (metadata, internal linking, schema, site architecture).
• Manage technical SEO initiatives—site speed, Core Web Vitals, structured data, crawl/indexation, and CMS optimization (Contentful).
• Build scalable frameworks for monitoring rankings, visibility, and performance across key search queries.
• Drive off-page SEO efforts, including authority-building strategies and high-quality backlink acquisition.
• Regularly audit and revitalize content for freshness, keyword alignment, and competitive differentiation.
• Partner with Analytics and Data teams to ensure Amplitude, GA4, and GSC insights fuel revenue-focused decisions.

Team / Collaboration

• Serve as Later’s SEO lead, collaborating with Web, Content, and Creative teams to deliver integrated campaigns.
• Partner with Content on an SEO-driven content plan, embedding E-E-A-T methodology and 10x competitor strategy.
• Partner with Web for technical SEO, site health, and on-site optimizations.
• Partner with Product Marketing to embed SEO into GTM motions and campaign planning.
• Mentor junior SEO contributors (current or future) and establish SEO best practices across teams.
• Contribute to weekly, monthly, and quarterly planning within Demand Gen and cross-functionally.

Leadership

• Act as the hands-on manager and subject matter expert for SEO at Later.
• Balance day-to-day execution with setting strategy, frameworks, and processes for scalable growth.
• Foster a culture of testing, learning, and continuous optimization.

Research/Best Practices

• Stay ahead of evolving SEO landscapes including AI search (GEO, SGE, Perplexity, ChatGPT Overviews) and voice/social search.
• Monitor competitors and industry leaders, identifying opportunities to differentiate Later.
• Share insights and evangelize SEO best practices across Marketing and Growth teams.

What success looks like:

• Within the first 90 days, you’ve delivered a full SEO audit, identified quick wins, launched initial priority initiatives, and built dashboards that clearly connect SEO performance to revenue.
• By 6 months, SEO is driving measurable growth in trials, mid-market/enterprise leads, and creator sign-ups, with best practices embedded across Content, Web, and Marketing.
• Later consistently ranks on the first page (and top 3) for high-priority keywords across all lines of business, with improvements in Core Web Vitals, site speed, and indexation.
• Later is recognized as an authority in the space, with high-quality backlinks, top-tier press mentions, and a scalable roadmap for continued growth in AI and emerging search channels.

What you bring:

• 5–7+ years of SEO experience with proven impact in SaaS, PLG, or B2B tech environments.
• Track record of driving measurable growth through SEO (traffic, conversions, pipeline).
• Advanced proficiency in on-page, off-page, and technical SEO.
• Hands-on experience with tools such as SEMrush, Ahrefs, Screaming Frog, Moz, GSC, GA4, Amplitude.
• Strong background with CMS platforms (preferably Contentful), including structuring and optimizing workflows.
• Experience managing authority-building efforts and backlink acquisition.
• Strong analytical skills; comfortable with keyword data, content performance, and attribution.
• Excellent communication and collaboration skills; able to influence across technical and creative teams.
• Familiarity with Generative Engine Optimization (GEO) and AI-powered search visibility.
• Experience in creator/social media marketing space.
• Knowledge of Google Tag Manager, A/B testing tools, or data visualization platforms (Looker, Supermetrics).
• Basic knowledge of HTML, CSS, and JavaScript.

How you work: 

• Driven by Impact: You deliver results that matter—prioritizing high-value work, meeting deadlines, and adapting quickly while keeping outcomes clear.
• Strategic & Customer-Centric: You anticipate risks and opportunities, connect decisions to long-term growth, and build trust through proactive insights.
• Curious & Growth-Oriented: You seek knowledge, ask sharp questions, and apply learnings fast—challenging the status quo with a mindset of improvement.
• Collaborative & Resilient: You thrive in change by staying resourceful, solution-focused, and positive—removing roadblocks, sharing insights, and keeping morale high.
• Accountable & Honest: You own your work, hold yourself and others to a high bar, and use transparent feedback to drive growth.
• Emotionally Intelligent: You build trust through empathy and collaboration, foster inclusion, and inspire others with grit, optimism, and integrity.

Our approach to compensation:

We take a market-based & data-driven approach to compensation. We leverage data from trusted third-party compensation sources to help us understand the market value of a role based on function, level, geographic location, and scope. We evaluate compensation bi-annually, including performance and market-related factors.

Our salaries are benchmarked against market Total Cash Compensation for the geographic location of our job posting. Compensation for some roles is structured as On Target Earnings (OTE = base + commission/variable) while for others it is structured as Salary only.

To comply with local legislation and ensure transparency, we share salary ranges on all job postings. Skills, experience and other factors help determine the final salary we offer which may vary from the original range posted. 

Additionally, all permanent team members are eligible to participate in various benefits plans as part of their overall compensation package.

Salary Range: 

$ 130,000 - $ 155,000 USD

#LI-Hybrid

About this position:

We’re looking for a Senior SEO Manager to lead Later’s organic growth engine and drive measurable impact across demand generation. In this role, you’ll be both a strategic leader and a hands-on practitioner—developing and executing SEO strategies that grow qualified traffic, improve conversion rates, and strengthen Later’s authority in the creator and social media space.
Reporting to the VP of Demand Generation, you’ll own Later’s SEO roadmap, partner cross-functionally with Web, Product Marketing, and Content teams, and set high standards for technical and content-driven SEO execution. This is a critical, high-visibility role across all lines of business (Later Influence, Later Social, and Mavely) with direct impact on revenue growth and regular exposure to senior leadership. 

What you'll be doing:

Strategy

• Own Later’s full SEO strategy across technical, on-page, content, off-site, and AI search to drive sustainable, high-quality organic growth across all three lines of business.
• Define SEO goals, KPIs, and reporting frameworks that connect performance to revenue growth.
• Provide actionable insights to Demand Gen, the broader marketing team, and senior leadership on trends, opportunities, and performance.

Technical/ Execution

• Lead keyword research, content gap analysis, SERP opportunity assessments, and AI search opportunities to inform actionable strategy.
• Create and deliver SEO-driven content plans, including briefs, page structures, and leveraging proprietary data for E-E-A-T methodology.
• Execute advanced on-page optimizations (metadata, internal linking, schema, site architecture).
• Manage technical SEO initiatives—site speed, Core Web Vitals, structured data, crawl/indexation, and CMS optimization (Contentful).
• Build scalable frameworks for monitoring rankings, visibility, and performance across key search queries.
• Drive off-page SEO efforts, including authority-building strategies and high-quality backlink acquisition.
• Regularly audit and revitalize content for freshness, keyword alignment, and competitive differentiation.
• Partner with Analytics and Data teams to ensure Amplitude, GA4, and GSC insights fuel revenue-focused decisions.

Team / Collaboration

• Serve as Later’s SEO lead, collaborating with Web, Content, and Creative teams to deliver integrated campaigns.
• Partner with Content on an SEO-driven content plan, embedding E-E-A-T methodology and 10x competitor strategy.
• Partner with Web for technical SEO, site health, and on-site optimizations.
• Partner with Product Marketing to embed SEO into GTM motions and campaign planning.
• Mentor junior SEO contributors (current or future) and establish SEO best practices across teams.
• Contribute to weekly, monthly, and quarterly planning within Demand Gen and cross-functionally.

Leadership

• Act as the hands-on manager and subject matter expert for SEO at Later.
• Balance day-to-day execution with setting strategy, frameworks, and processes for scalable growth.
• Foster a culture of testing, learning, and continuous optimization.

Research/Best Practices

• Stay ahead of evolving SEO landscapes including AI search (GEO, SGE, Perplexity, ChatGPT Overviews) and voice/social search.
• Monitor competitors and industry leaders, identifying opportunities to differentiate Later.
• Share insights and evangelize SEO best practices across Marketing and Growth teams.

What success looks like:

• Within the first 90 days, you’ve delivered a full SEO audit, identified quick wins, launched initial priority initiatives, and built dashboards that clearly connect SEO performance to revenue.
• By 6 months, SEO is driving measurable growth in trials, mid-market/enterprise leads, and creator sign-ups, with best practices embedded across Content, Web, and Marketing.
• Later consistently ranks on the first page (and top 3) for high-priority keywords across all lines of business, with improvements in Core Web Vitals, site speed, and indexation.
• Later is recognized as an authority in the space, with high-quality backlinks, top-tier press mentions, and a scalable roadmap for continued growth in AI and emerging search channels.

What you bring:

• 5–7+ years of SEO experience with proven impact in SaaS, PLG, or B2B tech environments.
• Track record of driving measurable growth through SEO (traffic, conversions, pipeline).
• Advanced proficiency in on-page, off-page, and technical SEO.
• Hands-on experience with tools such as SEMrush, Ahrefs, Screaming Frog, Moz, GSC, GA4, Amplitude.
• Strong background with CMS platforms (preferably Contentful), including structuring and optimizing workflows.
• Experience managing authority-building efforts and backlink acquisition.
• Strong analytical skills; comfortable with keyword data, content performance, and attribution.
• Excellent communication and collaboration skills; able to influence across technical and creative teams.
• Familiarity with Generative Engine Optimization (GEO) and AI-powered search visibility.
• Experience in creator/social media marketing space.
• Knowledge of Google Tag Manager, A/B testing tools, or data visualization platforms (Looker, Supermetrics).
• Basic knowledge of HTML, CSS, and JavaScript.

How you work: 

• Driven by Impact: You deliver results that matter—prioritizing high-value work, meeting deadlines, and adapting quickly while keeping outcomes clear.
• Strategic & Customer-Centric: You anticipate risks and opportunities, connect decisions to long-term growth, and build trust through proactive insights.
• Curious & Growth-Oriented: You seek knowledge, ask sharp questions, and apply learnings fast—challenging the status quo with a mindset of improvement.
• Collaborative & Resilient: You thrive in change by staying resourceful, solution-focused, and positive—removing roadblocks, sharing insights, and keeping morale high.
• Accountable & Honest: You own your work, hold yourself and others to a high bar, and use transparent feedback to drive growth.
• Emotionally Intelligent: You build trust through empathy and collaboration, foster inclusion, and inspire others with grit, optimism, and integrity.

Our approach to compensation:

We take a market-based & data-driven approach to compensation. We leverage data from trusted third-party compensation sources to help us understand the market value of a role based on function, level, geographic location, and scope. We evaluate compensation bi-annually, including performance and market-related factors.

Our salaries are benchmarked against market Total Cash Compensation for the geographic location of our job posting. Compensation for some roles is structured as On Target Earnings (OTE = base + commission/variable) while for others it is structured as Salary only.

To comply with local legislation and ensure transparency, we share salary ranges on all job postings. Skills, experience and other factors help determine the final salary we offer which may vary from the original range posted. 

Additionally, all permanent team members are eligible to participate in various benefits plans as part of their overall compensation package.

Salary Range: 

$ 130,000 - $ 155,000 USD

#LI-Hybrid