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

MUST HAVE:

• 5+ years of experience in data engineering within fast-paced, cloud-native environments
• Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto)
• Experience building and managing scalable ETL pipelines and data lake infrastructure
• Familiarity with distributed systems, Spark, and data quality best practices
• Strong cross-functional collaboration skills to support BI, analytics, and engineering teams

EXPERIENCE: 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations.

YOUR ROLE

Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth.

OUTCOMES

• Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business
• Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units
• Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth
• Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows
• Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity
• Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support
• Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture

COMPETENCIES

• Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools
• Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions
• Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently
• Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows
• Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations
• Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering

MUST HAVE:

• 5+ years of experience in data engineering within fast-paced, cloud-native environments
• Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto)
• Experience building and managing scalable ETL pipelines and data lake infrastructure
• Familiarity with distributed systems, Spark, and data quality best practices
• Strong cross-functional collaboration skills to support BI, analytics, and engineering teams

EXPERIENCE: 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations.

YOUR ROLE

Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth.

OUTCOMES

• Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business
• Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units
• Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth
• Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows
• Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity
• Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support
• Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture

COMPETENCIES

• Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools
• Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions
• Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently
• Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows
• Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations
• Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering

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

The Machine Learning Platform team (MLP) is seeking a Senior Software Engineer II to design and implement the secure, highly scalable, and high-performance pipelines that govern the end-to-end lifecycle of ML models.

You will work at the intersection of Data Science and DevOps, building the "connective tissue" that empowers our product portfolio to leverage technologies like Generative AI, Natural Language Processing (NLP), and real-time classification. We are looking for a subject matter expert who will drive innovation and deliver results that meet the dynamic needs of a high-growth AI environment. You will report to the Senior Engineering Manager on the MLP Solutions team.

What you’ll be working on

• Build and maintain robust ML systems using Python (Pandas/NumPy, PyTorch/transformers) to support efficient ML operations.
• Design ML cloud infrastructure using AWS services, ensuring the platform is built for reuse, scalability, and high-volume throughput.
• Collaborate with application engineers to integrate, test, and monitor ML model services across SurveyMonkey’s microservices architecture.
• Act as a consultant to internal feature teams, educating and influencing decisions regarding ML tooling and infrastructure.
• Incorporate telemetry into the platform for complex failure mode analysis, ensuring real-time reliability for millions of daily survey responses.
• Serve as a technical leader and mentor, championing high standards in coding, documentation, and architectural best practices to foster the professional growth of junior engineers on the MLP team.

We’d love to hear from people with

• 8+ years of professional ML development experience with a proven track record of designing and implementing ML infrastructure in AWS.
• Mastery of ML concepts (supervised/unsupervised learning) and deep understanding of Large Language Models (LLMs) and NLP.
• Expert-level Python skills and experience with high-scale data processing (PySpark, etc.).
• Comfortable with Unix/Linux systems and experienced in deploying end-to-end solutions for real-time applications (spam detection, personalization, ranking).
• Bachelor’s Degree in Computer Science, Data Science, Software Engineering, Mathematics, Statistics, or a related quantitative field.

The base pay provided for this position ranges from CAD $126,400.00/ year - $158,000.00/ 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

Mission

Speechify is the easiest way to listen to the world’s information. Articles on the web, documents in the cloud, books on your phone. We absorb it all and let you listen to it at your desk, on the go, at your own speed, and with tools that make learning easier, deeper, and faster.

What streaming services have done for audio entertainment, we’re doing for audio information. And whatever we’re doing seems to be working. We’re #1 in our category, and experiencing exponential growth.

Overview

We're looking for a Senior Software Engineer to join our Core Experiences Team. This team builds and maintains the foundational services and SDKs that power Speechify’s product experience across platforms. It's a critical role for someone who enjoys working at the intersection of product and infrastructure, thinks strategically, and is passionate about designing clear, reliable APIs and simple systems that directly enhance the user experience.

What You’ll Do

• Collaborate with Speechify’s Product Teams to scope projects, find ways to reduce scope to get faster feedback from customers, navigate the integration/UX tradeoffs relevant to different product teams, and deliver solutions via our cross-platform SDK
• Optimize existing functionality to ship things like faster loading and more intelligent parsing by designing more efficient abstractions and improving our algorithms
• Ship cloud functions, lightweight backend services, and jobs using Kotlin

An Ideal Candidate Should Have

• Systems thinking. You know that optimizing a system requires end-to-end design, and you believe simplicity is valuable.
• Speed. You work quickly to generate ideas and options and know how to decide which things can ship now and what things need time
• Focus. We’re a high-growth startup with a busy, remote team. You know how and when to engage or be heads down
• Collaboration. You know how to inspire, play, and negotiate with opinionated designers, marketers, and PMs
• Preferred Tech Stack:
  • Kotlin Multiplatform (Java experience is OK but role is Kotlin Multiplatform) 
  • Prior experience with GCP is a plus

What We Offer

• A fast-growing environment where you can help shape the company and product.
• An entrepreneurial-minded team that supports risk, intuition, and hustle.
• A hands-off management approach so you can focus and do your best work.
• An opportunity to make a big impact in a transformative industry.
• Competitive salaries, a friendly and laid-back atmosphere, and a commitment to building a great asynchronous culture.
• Opportunity to work on a life-changing product that millions of people use.
• Build products that directly impact and support people with learning differences like dyslexia, ADD, low vision, concussions, autism, and more.
• Work in one of the fastest growing sectors of tech, the intersection of artificial intelligence and audio.

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.

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

We're looking to hire for our Data side of our AI team at Speechify. This role is responsible for all aspects of data collection to support our model training operations. We are able to build high-quality datasets at petabyte-scale and low cost through a tight integration of infrastructure, engineering, and research work. We are looking for a skilled Software Engineer to join us.

What You’ll Do

• Be scrappy to find new sources of audio data and bring it into our ingestion pipeline
• Operate and extend the cloud infrastructure for our ingestion pipeline, currently running on GCP and managed with Terraform.
• Collaborate closely with our Scientists to shift the cost/throughput/quality frontier, delivering richer data at bigger scale and lower cost to power our next-generation models.
• Collaborate with others on the AI Team and Speechify Leadership to craft the AI Team’s dataset roadmap to power Speechify’s next-generation consumer and enterprise products.

An Ideal Candidate Should Have

• BS/MS/PhD in Computer Science or a related field.
• 5+ years of industry experience in software development.
• Proficiency with bash/Python scripting in Linux environments
• Proficiency in Docker and Infrastructure-as-Code concepts and professional experience with at least one major Cloud Provider (we use GCP)
• Experience with web crawlers, large-scale data processing workflows is a plus
• Ability to handle multiple tasks and adapt to changing priorities.
• Strong communication skills, both written and verbal.

What we offer

• A fast-growing environment where you can help shape the company and product.
• An entrepreneurial-minded team that supports risk, intuition, and hustle.
• A hands-off management approach so you can focus and do your best work.
• An opportunity to make a big impact in a transformative industry.
• Competitive salaries, a friendly and laid-back atmosphere, and a commitment to building a great asynchronous culture.
• Opportunity to work on a life-changing product that millions of people use.
• Build products that directly impact and support people with learning differences like dyslexia, ADD, low vision, concussions, autism, and more.
• Work in one of the fastest-growing sectors of tech, the intersection of artificial intelligence and audio.

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.

About the Role

As a Context Engineer at CapIntel, you'll sit at the intersection of AI infrastructure and engineering. You will be responsible for how large language models are integrated into our core platform and how our engineering team adopts agentic workflows. This is a hands-on, production-focused role, not a research one. You'll build the systems that make our AI features reliable, accurate, and scalable for the wealth management enterprises that depend on us.

You'll be embedded in development teams working closely with engineers, product managers, and domain experts across the organization to design and deliver LLM-powered capabilities that directly enhance the advisor and client experience. As one of the first practitioners in this discipline at CapIntel, you'll also help define what context engineering looks like here: setting patterns and practices the broader team can build on.

This role is ideal for someone who thinks in systems, cares about production reliability over demo-day performance, and is energized by working in a discipline that is evolving quickly.

What You'll Do

• Design and implement LLM-powered features into our core application via model APIs (e.g. Anthropic, OpenAI, Cohere), with a focus on reliability and production-readiness
• Architect and maintain retrieval-augmented generation (RAG) pipelines, connecting language models to internal knowledge bases, databases, and live data sources
• Manage context window strategy, determining what information enters the model, when, in what format, and at what level of compression to optimise for accuracy, cost, and latency
• Design and implement agentic workflows enabling the platform to handle multi-step, autonomous tasks
• Build guardrail and output validation layers that constrain model behaviour and ensure AI features act within well-defined, compliant boundaries
• Develop reusable agent primitives, prompt templates, and workflow components that other engineers can build on independently
• Build evaluation frameworks to measure context effectiveness, output quality, and agent reliability in production
• Monitor deployed AI systems for failure patterns and implement mitigation strategies, feeding learnings back into continuous improvement cycles
• Collaborate with Product, Product Engineering, Implementation, and Data teams to translate business requirements, and proof of concepts into production AI system specifications
• Act as an internal practitioner and resource helping upskill the broader engineering team on context engineering principles and agentic best practices

What We're Looking For

• 5+ years of professional software engineering experience, with at least 1–2 years working with LLMs in a production context
• Strong experience with Python or Node and building API-integrated backend services
• Hands-on experience with an orchestration or execution framework
• Working knowledge of RAG architecture, vector databases (e.g. Pinecone, pgVector, AWS OpenSearch), and semantic search
• Familiarity with context management techniques: summarisation, chunking, session splitting, and memory strategies
• Experience building or consuming REST APIs and integrating with third-party services
• Comfortable collaborating with cross-functional teams in a fast-paced, high-growth environment
• Strong problem-solving instincts and a willingness to learn and adapt as the field evolves

Nice to Have

• Experience with the Model Context Protocol (MCP) or similar tool-integration standards
• Familiarity with LLMOps practices: tracing, observability (e.g. LangSmith, Datadog), and model versioning
• Exposure to multi-agent architectures and orchestration patterns
• Knowledge of AI output validation, context safety, and governance considerations particularly relevant in regulated industries like financial services
• Familiarity with AWS or cloud-based infrastructure and containerised deployments (Docker, Kubernetes)
• Ability to communicate technical concepts clearly to both technical and non-technical partners