The Canada base salary range for this full-time position is $252,000-$308,000, plus equity and benefits. Our salary ranges are determined by role, level, and location. This role will be hybrid from our Vancouver, CAN office, with 2 days a week in the office required.

Responsibilities:

• Drive the design and implementation of new features. Break down complex problems into their bare essentials, translate this complexity into elegant design, and create high-quality, clean code.

• Make a meaningful impact on the lives of our community members.

• Design, develop, and deliver large-scale systems.

• Collaborate and mentor other engineers while providing thoughtful guidance using code, design, and architecture reviews.

• Contribute to defining technical direction, planning the roadmap, escalating issues, and synthesizing feedback to ensure team success.

• Estimate and manage team project timelines and risks.

• Care passionately about producing high-quality, efficient designs and code.

• Constantly learning about new technologies and industry standards in software engineering.

• Work cross-functionally with other teams, including: Analytics, design, product, marketing, and data science.

Requirements:

• 7+ years of development experience in backend software development

• Bachelor's, Master’s, or PhD in computer science, computer engineering, or a related technical discipline, or equivalent industry experience.

• Proficiency in at least one modern programming language, such as Java, Kotlin, Scala, or C#, and experience with at least one major framework such as Spring, Spring Boot, or ASP.NET Core.

• Hands-on experience working in cloud environments: AWS, GCP, or Azure

• Proficiency in event-driven systems such as Kafka, SQS, SNS, or Kinesis, and experience designing and operating scalable distributed systems.

• Knowledge of professional software engineering practices and best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations

• Hands-on experience working with various databases. DynamoDB, MySQL, ElasticSearch

• Experience using AI-assisted development tools (e.g., Copilot, Cursor, LLMs) to improve engineering productivity

• Experience with continuous integration and delivery tools, and experience in developing and executing functional and integration tests.

• Familiarity with a clean architecture approach and software craftsmanship

• Experience with Kubernetes and microservice architecture is a strong plus.

• Excellent written and verbal communication skills.

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Your responsibilities will include:

• Designing and building distributed systems that process, enrich, and respond to billions of behavioral events per day in real time
• Developing high-performance APIs and services that support advertising, identity, and intent features across the Marketing Platform
• Leveraging machine learning and large language models (LLMs) to analyze behavioral data, classify content, extract signals, and enable intelligent decision-making
• Building intelligent agents using frameworks like LangGraph or MCP to reason over data and power user-facing insights
• Designing and operating data pipelines using tools like Kafka, Kinesis, and ClickHouse to support both streaming and batch workloads
• Driving quality, performance, scalability, and observability across all systems you own
• Collaborating cross-functionally with product managers, data scientists, and engineers to deliver customer-facing features and internal tooling
• Contributing to technical leadership and mentorship of teammates

We're looking for someone with 8+ years of backend, data, or infrastructure engineering experience, or equivalent impact and leadership. You should have strong experience in at least one of the following areas:

• Distributed systems engineering
• Big data infrastructure
• Applied AI/ML

You should also be proficient in one or more core languages (Java, Go, Python), have a solid grasp of SQL and large-scale data modeling, and familiarity with databases and tools such as ClickHouse, DynamoDB, Bigtable, Memcached, Kafka, Kinesis, Firehose, Airflow, Snowflake.

Bonus points if you have experience in ad tech, real-time bidding (RTB), or programmatic systems, background in identity resolution, attribution, or behavioral analytics at scale, contributions to open source in ML, infrastructure, or data tooling, or strong product instincts and a passion for building tools that drive meaningful outcomes.

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Job Description:

Before 1965, it was extremely difficult and time-consuming to analyze complicated signals, like radio or images. You could solve it, but you had to throw a ton of compute at it. That all changed with the invention of the Fast Fourier transform, which could efficiently break that signal down into the frequencies that are a part of it.

The Risk Onboarding team is working on efficiently reviewing customers’ applications without compromising on quality. We are the front line of defense for preventing money laundering and financial crimes, building systems to verify that someone is who they say they are and that we are allowed to do business with them.

About Us:

At Mercury, we craft an exceptional banking experience for startups. Our team is focused on ensuring our products create a safe environment that meets the needs of our customers, administrators, and regulators.

Job Responsibilities:

As part of this role, you will:

• Partner with data science & engineering teams to design and deploy ML & Gen AI microservices, primarily focusing on automating reviews
• Work with a full-stack engineering team to embed these services into the overall review experience, including human in the loop, escalations, and feeding human decisions back into the service
• Implement testing, observability, alerting, and disaster recovery for all services
• Implement tracing, performance, and regression testing
• Feel a strong sense of product ownership and actively seek responsibility – we often self-organize on small/medium projects, and we want someone who’s excited to help shape and build Mercury’s future

Ideal Candidate:

The ideal candidate for the role has:

• 7+ years of experience in roles like machine learning engineering, data engineering, backend software engineering, and/or devops
• Expertise with:

• A full modern data stack: Snowflake, dbt, Fivetran, Airbyte, Dagster, Airflow
• SQL, dbt, Python
• OLAP / OLTP data modelling and architecture
• Key-value stores: Redis, dynamoDB, or equivalent
• Streaming / real-time data pipelines: Kinesis, Kafka, Redpanda
• API frameworks: FastAPI, Flask, etc.
• Production ML Service experience
• Working across full-stack development environment, with experience transferable to Haskell, React, and TypeScript

Total Rewards Package:

The total rewards package at Mercury includes base salary, equity (stock options/RSUs), and benefits. Our salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry. New hire offers are made based on a candidate’s experience, expertise, geographic location, and internal pay equity relative to peers.

Salary Range:

Our target new hire base salary ranges for this role are the following:

• US employees (any location): $200,700 - $250,900
• Canadian employees (any location): CAD 189,700 - 237,100

Diversity & Belonging:

Mercury values diversity & belonging and is proud to be an Equal Employment Opportunity employer. All individuals seeking employment at Mercury are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation, or any other legally protected characteristic.

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