The Application Modernization Platform team aids developers in making the shift from relational databases to MongoDB, building toolkits that leverage AI to power seamless transitions. 

As a Senior Technical Program Manager, you will own the successful delivery of complex, cross-functional efforts for Application Modernization. You will partner closely with stakeholders across the organization from Engineering, Product, Product Design, and Field-facing teams to develop and execute against our overall product vision and business objectives, uncover solutions to technical challenges, and provide data-driven insights that power strategic decision-making.

This remote position is open to candidates in Eastern and Central timezones.

The right candidate for this role will be:

• Experienced with 5+ years of Software development background, preferably with experience with Java web services and with relational data modelling and SQL
• Familiar with tools and methodologies for code analysis, refactoring, and automated testing
• Able to partner with technical stakeholders in methodically breaking down engineering challenges to deliver against abstract goals
• Able to participate in technical design discussions and summarize trade-offs, outcomes, and next steps
• Skilled at communicating across a diverse set of engineers and stakeholders
• Capable of deep user empathy and adept at balancing product goals and engineering constraints to deliver impactful experiences
• Hyper-organized and capable of coordinating across multiple independent work streams and organizations
• A role model for effective execution practices, driven by an attuned sense of priority and urgency
• Able to leverage their experience in program delivery to influence improvements to our tools, operations, architecture
• Trained in working with project tracking software (JIRA is preferred)
• Familiar with MongoDB or a comparable technology
• Exposed to generative AI and Machine Learning
• Interested in business automation work such as scripting in Python, Google Apps Script and Slack

Position Expectations:

• Leverage technical acumen and analytical skills to drive engineering programs forward and maximize business value delivery
• Recognize patterns in a sea of information and take action accordingly
• Develop a strategic approach to program management that balances hands-on oversight with process-driven operationalization. This involves discerning when to provide direct guidance and when to empower teams by establishing clear frameworks and guidelines for ongoing initiatives
• Build strategic partnerships with Product, Design, and Engineering stakeholders
• Expand knowledge into new domains as called upon
• Embody MongoDB's core values and leadership principles

Success Measures:

• In 3 months you will be ramped on the App Modernization product and engineering roadmap
• In 6 months you will own and drive critical initiatives across the App Modernization portfolio
• In 12 months you will be organizing multiple high impact efforts and integrating improvements to frameworks for managing critical programs at MongoDB

About MongoDB

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform, the most widely available, globally distributed database on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and over 60,000 customers, including 75% of the Fortune 100 and AI-native startups, relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. 

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB is an equal opportunities employer.

REQ ID: 4263333180

About the Cloud Payments team

Cloud Payments is part of the Cloud Billing organization. As MongoDB’s Cloud business grows, the billing and payments stack becomes increasingly mission‑critical. Our team:

• Ingests and aggregates detailed metering and usage data from internal services and major cloud providers (AWS, Azure, GCP)
• Calculates and generates daily customer bills for millions of customers worldwide
• Integrates with payment processors and internal financial systems to support Finance, Sales, Marketing, and Accounting
• Continuously improves customer-facing billing and payments experiences and the reliability and scalability of our backend systems

We’re a group of engineers who care deeply about code quality, correctness, and observability, and who are comfortable collaborating with both highly technical partners and non-technical stakeholders across the business.

The role

We’re looking for a Software Engineer 3 to help design, build, and operate the services that power Cloud Payments. You’ll work primarily in the JVM ecosystem (Java and related tooling), with a focus on large-scale, distributed systems that have to be correct, resilient, and auditable.

This is a Canada-based, fully remote role. You’ll collaborate closely with teammates and stakeholders across North America time zones, including engineers in the broader Cloud Billing organization.

What you’ll do

In this role, you will:

• Design, implement, and operate backend services that ingest, process, and reconcile large volumes of usage and billing data from internal and external systems
• Collaborate with product, Finance, Revenue, and other engineering teams to evolve our billing and payments capabilities and improve customer experience
• Own features end‑to‑end: requirements, design, implementation, testing, rollout, monitoring, and iterative improvement
• Help scale and harden our systems as Atlas and our broader Cloud business continue to grow rapidly
• Participate in architecture discussions, technical design reviews, and code reviews to keep our systems robust and maintainable
• Contribute to improving our tooling, observability, and development workflows so the whole team can move faster and safer
• Take part in an on‑call rotation that treats reliability as a team sport, not an individual burden

What we’re looking for

You may be a great fit if you:

• Have 3+ years of experience building and maintaining backend systems in a compiled language, ideally Java
• Understand core object‑oriented design principles and how to apply them to complex, evolving systems
• Have experience with distributed systems and services that need to be highly available, observable, and correct at scale
• Are comfortable working with databases (relational and/or non‑relational such as MongoDB) in production environments
• Communicate clearly and enjoy working with both technical and non‑technical stakeholders across multiple teams
• Are curious, collaborative, and motivated by solving real customer and business problems rather than just closing tickets

Nice to have (but not required):

• Experience with billing, payments, or other financial systems where correctness, auditability, and compliance really matter
• Experience with cloud platforms (AWS, GCP, Azure) and modern communication protocols like gRPC
• Familiarity with data-intensive applications, data pipelines, or data lakes
• Exposure to working with I/O frameworks like Reactor
• Experience with containerization and orchestration (e.g., Docker, Kubernetes)
• Prior exposure to MongoDB as a developer or operator

We don’t expect you to check every box. If you’re excited about the space and think you could do great work here, we’d love to hear from you.

Working model & location

• Location: Canada
• Working model: Fully remote, with colleagues primarily across North American time zones

How we’ll support you

MongoDB is committed to building a supportive, inclusive, and growth‑oriented environment for everyone on the team. Our approach to benefits and working models is designed to support your physical, emotional, financial, and family well‑being, and to give you flexibility in how you do your best work.

You’ll have opportunities to:

• Work on complex, meaningful projects that directly impact MongoDB’s Cloud business
• Learn from and collaborate with experienced engineers across Cloud Billing and other parts of MongoDB
• Grow your career through mentorship, feedback, and stretch projects aligned with your interests

About MongoDB

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform, the most widely available, globally distributed database on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and over 60,000 customers, including 75% of the Fortune 100 and AI-native startups, relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. 

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB is an equal opportunities employer.

REQ ID: 1273389937

The mission of Speechify is to make sure that reading is never a barrier to learning.

Over 50 million people use Speechify’s text-to-speech products to turn whatever they’re reading – PDFs, books, Google Docs, news articles, websites – into audio, so they can read faster, read more, and remember more. Speechify’s text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its 2025 Design Award winner for Inclusivity.  

Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting – Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies.

Overview

The responsibilities of our Platform team include building and maintaining all backend services, including, but not limited to, payments, analytics, subscriptions, new products, text to speech, and external APIs.

This is a key role and ideal for someone who thinks strategically, enjoys fast-paced environments, is passionate about making product decisions, and has experience building great user experiences that delight users.

We are a flat organization that allows anyone to become a leader by showing excellent technical skills and delivering results consistently and fast. Work ethic, solid communication skills, and obsession with winning are paramount. 

Our interview process involves several technical interviews and we aim to complete them within 1 week. 

What You’ll Do

• Design, develop, and maintain robust APIs including public TTS API, internal APIs like Payment, Subscription, Auth and Consumption Tracking, ensuring they meet business and scalability requirements
• Oversee the full backend API landscape, enhancing and optimizing for performance and maintainability
• Collaborate on B2B solutions, focusing on customization and integration needs for enterprise clients
• Work closely with cross-functional teams to align backend architecture with overall product strategy and user experience

An Ideal Candidate Should Have

• Proven experience in backend development: TS/Node (required)
• Direct experience with GCP and knowledge of AWS, Azure, or other cloud providers
• Efficiency in ideation and implementation, prioritizing tasks based on urgency and impact
• Preferred: Experience with Docker and containerized deployments
• Preferred: Proficiency in deploying high availability applications on Kubernetes

What We Offer

• A dynamic environment where your contributions shape the company and its products
• A team that values innovation, intuition, and drive
• Autonomy, fostering focus and creativity
• The opportunity to have a significant impact in a revolutionary industry
• Competitive compensation, a welcoming atmosphere, and a commitment to an exceptional asynchronous work culture
• The privilege of working on a product that changes lives, particularly for those with learning differences like dyslexia, ADD, and more
• An active role at the intersection of artificial intelligence and audio – a rapidly evolving tech domain

Think you’re a good fit for this job? 

Tell us more about yourself and why you're interested in the role when you apply.
And don’t forget to include links to your portfolio and LinkedIn.

Not looking but know someone who would make a great fit? 

Refer them! 

Speechify is committed to a diverse and inclusive workplace. 

Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

What we’re looking for

This is a highly visible, strategic, and impactful role, reporting the VP of Engineering for SurveyMonkey Core Engineering. As the Senior Director of AI, you will be a critical leader in defining the future of SurveyMonkey's products and services. You will not just manage the Machine Learning and Data Science teams, but help drive the fundamental shift in how our customers gather, analyze, and act on feedback. This requires both strong strategic thinking, and solid experience building models and deploying AI/ML systems end-to-end (from data to production). The successful candidate will make a material contribution to the company's success by providing thought leadership around how to leverage AI technology in the SurveyMonkey product in an intuitive and natural way.

What you’ll be working on

Strategic Leadership & Product Alignment

• Strategic Roadmapping: Define and execute the long-term data science strategy, ensuring alignment with SurveyMonkey’s overarching business objectives and product vision.
• Product-to-Data Science Translation: Act as the primary liaison between Product Management and the Data Science team, expertly mapping ambitious SurveyMonkey product requirements (e.g., automated thematic analysis, predictive modeling, intelligent survey generation) into clear, technically feasible data science projects.
• AI-First Transformation: Support the charge in migrating SurveyMonkey from a traditional SaaS product to an AI-first platform, embedding advanced data science and LLM capabilities deeply within the product experience.

Technical Expertise & Innovation

• LLM and NLP Integration: Drive the strategy for integrating and leveraging Large Language Models (LLMs) and advanced Natural Language Processing (NLP) techniques to enhance our text analytics, sentiment analysis, and generative features within the product.
• Familiarity with MLOps / LLMOps practices: Experience developing and deploying a Machine Learning Platform.  Experience with Agentic AI Architecture, deployment and execution. Familiarity with modern MLOps tools and platforms (e.g., AWS SageMaker, GCP Vertex AI, MLflow).
• Technical Direction: Set the technical standards for model development, deployment, monitoring, and maintenance. Ensure the team utilizes best-in-class data science models, tools, and platforms for scalable production systems.
• Ownership of model lifecycle: experimentation → deployment → monitoring → iteration
• Stay Current: Actively research, evaluate, and evangelize the latest developments in machine learning, deep learning, MLOps, and data science methodologies, ensuring the team's capabilities remain cutting-edge.

Team Management & Development

• Management and Motivation: Lead, mentor, and inspire a high-performing team of data scientists and machine learning engineers. Foster a culture of innovation, rigor, collaboration, and continuous learning.
• Recruitment and Growth: Recruit top-tier data science talent, manage performance, and define career progression paths to ensure the ongoing growth and retention of team members.

We’d love to hear from people with

• Experience: 10+ years of progressive experience in data science, including significant experience with AI/ML platforms, and at least 5 years in a Director level leadership role managing and scaling data science or machine learning teams in a commercial software environment.
• Experience building or leading AI/ML platforms: (feature stores, model serving, training pipelines) in a Cloud Environment like AWS
• Deep Technical Acumen: Extensive practical experience with and deep theoretical understanding of machine learning algorithms, statistical modeling, and experimental design (A/B testing).
• NLP and LLM Proficiency (Critical): Demonstrated experience in applying, fine-tuning, and integrating Large Language Models (LLMs) and advanced Natural Language Processing techniques into production systems, especially for tasks related to text classification, summarization, and generation.
• Product Thinking: Exceptional ability to translate ambiguous or high-level product needs into concrete, defensible data science problems and solutions.
• Communication: Excellent written and verbal communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders (e.g., Executives, Product Managers, Marketing).
• Education: Master’s degree or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field.

The base pay provided for this position ranges from CAD $224,000/ year - $336,000/ year depending on the geographic market and assuming a full-time schedule. Actual base pay is based on a number of factors including market location, job-related knowledge, education or training, skills, and experience.

Bonuses may also be offered as part of the total compensation package, in addition to a competitive benefits package including medical, dental, vision, life, and disability insurance; RRSP matching; flexible spending & health savings account; paid holidays; paid time off; employee assistance program; and other company benefits. 

This opening is for an existing vacancy.

SurveyMonkey believes in-person collaboration is valuable for building relationships, fostering community, and enhancing our speed and execution. While this role is remote, it may require in-person participation. You will be encouraged to attend company events throughout the year. These events will take place at a designated SurveyMonkey office or location.

#LI-remote

What we’re looking for

This is a highly visible, strategic, and impactful role, reporting the VP of Engineering for SurveyMonkey Core Engineering. As the Senior Director of AI, you will be a critical leader in defining the future of SurveyMonkey's products and services. You will not just manage the Machine Learning and Data Science teams, but help drive the fundamental shift in how our customers gather, analyze, and act on feedback. This requires both strong strategic thinking, and solid experience building models and deploying AI/ML systems end-to-end (from data to production). The successful candidate will make a material contribution to the company's success by providing thought leadership around how to leverage AI technology in the SurveyMonkey product in an intuitive and natural way.

What you’ll be working on

Strategic Leadership & Product Alignment

• Strategic Roadmapping: Define and execute the long-term data science strategy, ensuring alignment with SurveyMonkey’s overarching business objectives and product vision.
• Product-to-Data Science Translation: Act as the primary liaison between Product Management and the Data Science team, expertly mapping ambitious SurveyMonkey product requirements (e.g., automated thematic analysis, predictive modeling, intelligent survey generation) into clear, technically feasible data science projects.
• AI-First Transformation: Support the charge in migrating SurveyMonkey from a traditional SaaS product to an AI-first platform, embedding advanced data science and LLM capabilities deeply within the product experience.

Technical Expertise & Innovation

• LLM and NLP Integration: Drive the strategy for integrating and leveraging Large Language Models (LLMs) and advanced Natural Language Processing (NLP) techniques to enhance our text analytics, sentiment analysis, and generative features within the product.
• Familiarity with MLOps / LLMOps practices: Experience developing and deploying a Machine Learning Platform.  Experience with Agentic AI Architecture, deployment and execution. Familiarity with modern MLOps tools and platforms (e.g., AWS SageMaker, GCP Vertex AI, MLflow).
• Technical Direction: Set the technical standards for model development, deployment, monitoring, and maintenance. Ensure the team utilizes best-in-class data science models, tools, and platforms for scalable production systems.
• Ownership of model lifecycle: experimentation → deployment → monitoring → iteration
• Stay Current: Actively research, evaluate, and evangelize the latest developments in machine learning, deep learning, MLOps, and data science methodologies, ensuring the team's capabilities remain cutting-edge.

Team Management & Development

• Management and Motivation: Lead, mentor, and inspire a high-performing team of data scientists and machine learning engineers. Foster a culture of innovation, rigor, collaboration, and continuous learning.
• Recruitment and Growth: Recruit top-tier data science talent, manage performance, and define career progression paths to ensure the ongoing growth and retention of team members.

We’d love to hear from people with

• Experience: 10+ years of progressive experience in data science, including significant experience with AI/ML platforms, and at least 5 years in a Director level leadership role managing and scaling data science or machine learning teams in a commercial software environment.
• Experience building or leading AI/ML platforms: (feature stores, model serving, training pipelines) in a Cloud Environment like AWS
• Deep Technical Acumen: Extensive practical experience with and deep theoretical understanding of machine learning algorithms, statistical modeling, and experimental design (A/B testing).
• NLP and LLM Proficiency (Critical): Demonstrated experience in applying, fine-tuning, and integrating Large Language Models (LLMs) and advanced Natural Language Processing techniques into production systems, especially for tasks related to text classification, summarization, and generation.
• Product Thinking: Exceptional ability to translate ambiguous or high-level product needs into concrete, defensible data science problems and solutions.
• Communication: Excellent written and verbal communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders (e.g., Executives, Product Managers, Marketing).
• Education: Master’s degree or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field.

The base pay provided for this position ranges from CAD $224,000/ year - $336,000/ year depending on the geographic market and assuming a full-time schedule. Actual base pay is based on a number of factors including market location, job-related knowledge, education or training, skills, and experience.

Bonuses may also be offered as part of the total compensation package, in addition to a competitive benefits package including medical, dental, vision, life, and disability insurance; RRSP matching; flexible spending & health savings account; paid holidays; paid time off; employee assistance program; and other company benefits. 

This opening is for an existing vacancy.

SurveyMonkey believes in-person collaboration is valuable for building relationships, fostering community, and enhancing our speed and execution in problem-solving and decision-making. As such, you will be required to work from our Ottawa office up to 1 day per week.

#LI-Hybrid

Location: Ottawa, ON

As a Solutions Architect on the Canada team focused on Digital Native customers, you will shape the future of the big data landscape by working with the most sophisticated data engineering and data science teams in the world.

Reporting to the Field Engineering Manager, you will collaborate with customers, product teams, and the broader customer-facing team to develop architectures and solutions using our platform and APIs. You will guide customers through the competitive landscape, best practices, and implementation; and develop technical champions along the way.

The impact you will have:

• You will partner with the sales team and provide technical leadership to help customers understand how Databricks can help solve their business problems.
• Consult on Big Data architectures, implement proof of concepts for strategic projects, spanning data engineering, data science and machine learning, and SQL analysis workflows. As well as validating integrations with cloud services, home grown tools, and other 3rd party applications
• Collaborate with your fellow Solutions Architects, using your skills to support each other and our users
• Become an expert in, promote, and recruit contributors for Databricks inspired open-source projects (Spark, Delta Lake, and MLflow) across the developer community.

What we look for:

• 5+ years in a data engineering, data science, technical architecture, or similar pre-sales/consulting role
• Experience building distributed data systems
• Comfortable programming in, and debugging, Python and SQL
• Have built solutions with public cloud providers such as AWS, Azure, or GCP
• Expertise in one of the following:
  • Data Engineering technologies (Ex: Spark, Hadoop, Kafka)
  • Data Science and Machine Learning technologies (Ex: pandas, scikit-learn, pytorch, Tensorflow)
• Available to travel to customers in your region
• [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
• Nice to have: Databricks Certification

NOTE: If your experience isn’t a perfect match for the job description, but you feel like you’re a good fit for the role, apply.  We want to work with smart, passionate, people who are good at their job, and, a lot of times, those people have non-linear career paths.