We’re seeking a Staff DevOps Engineer to join our Cloud Platform Team — the engineer who sets the technical direction for how Built’s infrastructure is designed, operated, and evolved. This is the most senior individual contributor role on the platform team, and it goes well beyond day-to-day operations. You’ll architect the systems that every engineering team at Built depends on, define the standards that others work within, and drive the platform roadmap with full autonomy. By raising the reliability and velocity of our infrastructure, you directly enable Built’s mission of radically disrupting construction finance.

Our Guiding Principles

• Be Bold. We pursue the biggest problems in our industry, challenge assumptions others take for granted, and take calculated risks to get there. We don’t hide behind consensus or committees. Playing it safe is just failing slowly.
• Help Customers Win. We learn our customers’ businesses deeply — how they think, how they deploy capital, what keeps them up at night. We treat their capital like our own. We ship leverage, not features. And we measure ourselves by customer results, not our intentions.
• Move with Urgency & Purpose. We bias toward delivery over perfection, remove friction from our own paths, and communicate in real time. Momentum compounds — and we build it every day.
• Own the Outcome. We own outcomes, not just tasks. We hold a high Say:Do ratio and take responsibility from idea through impact. When something breaks, we fix it — we don’t wait to be asked.
• Never Satisfied. We raise the bar continuously. We stay curious, hold exacting standards, debate hard, and hold our opinions loosely when the evidence shifts. Excellence is a habit, not an event.

What You’ll Do

• Architect and own Built’s core cloud infrastructure on AWS — defining the patterns, standards, and systems that all engineering teams build on, from EKS/ECS cluster design to VPC topology to IAM governance.
• Lead platform modernization — driving the migration and simplification of our software delivery lifecycle, rationalizing tooling, and building the infrastructure foundation for Built’s AI-related product initiatives.
• Own SLOs and SLIs for the platform — define them, instrument them in your observability stack, and lead the team in meeting reliability targets consistently across all environments.
• Define DevOps engineering standards across the team — IaC patterns, CI/CD architecture, container orchestration standards, and observability frameworks.
• Drive the platform roadmap in partnership with engineering leadership — balancing foundational investment with immediate delivery needs and communicating trade-offs clearly to technical and non-technical stakeholders.
• Lead incident response and postmortems — serve as the technical escalation point for complex infrastructure failures, drive systemic improvements, and reduce incident volume over time.
• Evaluate and adopt new technologies across the platform stack — making sound build-versus-buy decisions with a clear view of long-term trade-offs and ROI.
• Mentor a team of 5 platform engineers through design reviews, pairing, architecture guidance, and knowledge-sharing sessions across the broader engineering organization.
• Partner with Information Security to lead vulnerability assessment and security architecture — ensuring compliance, proactive risk management, and adherence to regulatory requirements.

Skills & Experience

Must-Have

• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
• 8+ years of hands-on experience in DevOps, platform engineering, or cloud infrastructure in a production environment.
• Expert-level AWS knowledge — deep fluency with EKS, ECS, EC2, RDS, S3, IAM, VPC, and cost management tooling.
• Deep Kubernetes expertise — cluster architecture, networking, RBAC, autoscaling, and debugging production workloads at scale.
• Strong infrastructure-as-code proficiency with Terraform — writing extensible, maintainable modules and enforcing IaC standards across the team.
• Proven experience designing and operating CI/CD pipelines with GitHub Actions, CircleCI, or similar tooling.
• Hands-on observability experience with Datadog, Grafana, or similar platforms — metrics, logs, traces, monitors, SLO tracking, and alerting.
• Familiarity with incident management tooling (Incident.io, PagerDuty, or similar) and a track record of leading postmortems and driving systemic reliability improvements.
• Fluency in at least one scripting or automation language — Python, Go, or Bash.
• Strong communication skills — able to present infrastructure risks and architectural trade-offs to both engineers and non-technical stakeholders.

Nice-to-Have

• Experience with other IaC tools (Pulumi, CloudFormation, CDK) is a plus.
• Experience with service catalog and developer experience tooling (OpsLevel, Backstage, or similar).
• Background in fintech, lending, or regulated industries where uptime, auditability, and data security are critical.
• FinOps experience — cloud cost governance, right-sizing, and spend transparency across engineering teams.
• Contribution to open-source infrastructure projects or published engineering RFCs.

What the First Year Looks Like

Days 1–30: Learn the Landscape

• Ramp up on Built’s AWS infrastructure (EKS, ECS, VPC, IAM), CI/CD pipelines, and observability stack.
• Shadow on-call rotations (roughly one week every six weeks) to understand current incident patterns and pain points firsthand.
• Build relationships with product engineering teams to understand their infrastructure dependencies and friction points.

Days 30–60: Start Shaping the Platform

• Identify the highest-leverage opportunities for platform modernization and SDLC simplification.
• Begin contributing to architecture decisions and TRDs for current initiatives.
• Propose improvements to IaC standards, deployment pipelines, or observability coverage where gaps exist.

Days 60–90: Own and Drive

• Lead a meaningful platform initiative from architecture through delivery — whether modernization, reliability, or developer experience.
• Establish yourself as the technical standard-setter the team turns to for complex infrastructure and AI-related platform questions.
• Contribute to the roadmap planning process with a clear point of view on what the platform needs next.

AI & Technology Expectations

At Built, AI is a first-class part of how we work — not a pilot program. For this role specifically, that means:

• Use AI coding assistants (your choice of platform) as a daily productivity multiplier for IaC authoring, pipeline configuration, and automation scripting.
• Apply AI to platform operations: runbook generation, incident summarization, root cause analysis drafts, and postmortem synthesis.
• Drive and contribute to Built’s broader initiative to automate the software delivery lifecycle — identifying where AI can reduce manual toil across build, test, deploy, and observe workflows.
• Evaluate emerging AI infrastructure tooling and bring well-reasoned recommendations to the team.
• Share effective AI use cases and patterns with the broader engineering organization.

Operational Details

• Team size: You’ll join a team of 5 platform engineers, with this role serving as the senior technical anchor.
• On-call: Rotations run approximately one week every six weeks. We work continuously to reduce incident volume and toil so that on-call is manageable and low-noise.
• Location: Remote (US). Flexible working hours.

Built’s salary range for this position is $175,000-$235,000 USD per year. The pay range is designed to accommodate upward mobility in the role, therefore it encompasses the full span of proficiency levels for this role and we believe that the midpoint of the range is competitive in the market. Salary is just one component of Built's total compensation package for employees. Your total rewards package at Built will include equity, top-notch medical, dental and vision coverage, an unlimited PTO policy, and other benefits.

Who we are

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn’t coming; it’s here, and we need builders, innovators and problem solvers to help us create it.

Who you are

Metropolis is seeking a Senior Analytics Engineer to join our Data Engineering and Analytics team. The ideal candidate will possess a passion for creating value using data and a strong foundation in all aspects of analytics engineering. In this pivotal role, you will be instrumental in making data accessible and actionable, facilitating informed decision-making throughout the company. You will partner and lead across multiple product team functions and domains and drive impact through your data vision and architecture.

What you'll do

• Design and implement large-scale data warehouses and data marts using Snowflake, Star, or Data Vault 2.0 schemas
• Build and maintain data transformation pipelines using SQL frameworks like dbt to abstract model code
• Write complex SQL including window functions and STRUCT/ARRAY manipulations while adhering to performance best practices
• Manage and optimize DAGs, including troubleshooting task failures and improving run times
• Implement metadata management, data lineage, and security principles such as least-privilege access
• Use a test-driven approach to design systems that trap poor quality data and trigger alerts within the data flow
• Partner with engineering, data science, and business stakeholders to own project scopes
• Mentor others on data best practices to drive impact through your data vision
• Provide architectural guidance to ensure data is accessible and actionable across the company
• Drive technical excellence within the data engineering and analytics domain

What we're looking for

• 5+ years of experience in data/analytics engineering with proficiency in Python and SQL within Snowflake
• 3+ years of experience with dbt
• Owned large-scale data projects that drove significant impact through effective cross-functional partnering
• Led the design, implementation, and monitoring of data warehouses that enable clear product-focused insights
• Expert at SQL, window functions, and query optimization for complex data manipulations
• Applied performance best practices, including partitions, sort keys, and incremental modeling
• Designed systems using test-driven approaches to ensure data quality and flow integrity
• Familiarity with ELT processes and tools to prepare and clean data for analysis
• Skill in using tools like dbt to build data transformation pipelines
• Experience mentoring stakeholders in Data Science, Analytics, PM, and Engineering on data best practices

While not required, these are a plus:

• A dbt certification

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection.

When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $130,000.00 USD to $175,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis's total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans and more. #LI-CM1 #LI-Onsite

Who we are

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn’t coming; it’s here, and we need builders, innovators and problem solvers to help us create it.

Who you are

Metropolis is seeking a Senior Analytics Engineer to join our Data Engineering and Analytics team. The ideal candidate will possess a passion for creating value using data and a strong foundation in all aspects of analytics engineering. In this pivotal role, you will be instrumental in making data accessible and actionable, facilitating informed decision-making throughout the company. You will partner and lead across multiple product team functions and domains and drive impact through your data vision and architecture.

What you'll do

• Design and implement large-scale data warehouses and data marts using Snowflake, Star, or Data Vault 2.0 schemas
• Build and maintain data transformation pipelines using SQL frameworks like dbt to abstract model code
• Write complex SQL including window functions and STRUCT/ARRAY manipulations while adhering to performance best practices
• Manage and optimize DAGs, including troubleshooting task failures and improving run times
• Implement metadata management, data lineage, and security principles such as least-privilege access
• Use a test-driven approach to design systems that trap poor quality data and trigger alerts within the data flow
• Partner with engineering, data science, and business stakeholders to own project scopes
• Mentor others on data best practices to drive impact through your data vision
• Provide architectural guidance to ensure data is accessible and actionable across the company
• Drive technical excellence within the data engineering and analytics domain

What we're looking for

• 5+ years of experience in data/analytics engineering with proficiency in Python and SQL within Snowflake
• 3+ years of experience with dbt
• Owned large-scale data projects that drove significant impact through effective cross-functional partnering
• Led the design, implementation, and monitoring of data warehouses that enable clear product-focused insights
• Expert at SQL, window functions, and query optimization for complex data manipulations
• Applied performance best practices, including partitions, sort keys, and incremental modeling
• Designed systems using test-driven approaches to ensure data quality and flow integrity
• Familiarity with ELT processes and tools to prepare and clean data for analysis
• Skill in using tools like dbt to build data transformation pipelines
• Experience mentoring stakeholders in Data Science, Analytics, PM, and Engineering on data best practices

While not required, these are a plus:

• A dbt certification

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection.

When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $130,000.00 USD to $175,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis's total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans and more. #LI-CM1 #LI-Onsite

Who we are

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn’t coming; it’s here, and we need builders, innovators and problem solvers to help us create it.

Who you are

Metropolis is seeking a Senior Analytics Engineer to join our Data Engineering and Analytics team. The ideal candidate will possess a passion for creating value using data and a strong foundation in all aspects of analytics engineering. In this pivotal role, you will be instrumental in making data accessible and actionable, facilitating informed decision-making throughout the company. You will partner and lead across multiple product team functions and domains and drive impact through your data vision and architecture.

What you'll do

• Design and implement large-scale data warehouses and data marts using Snowflake, Star, or Data Vault 2.0 schemas
• Build and maintain data transformation pipelines using SQL frameworks like dbt to abstract model code
• Write complex SQL including window functions and STRUCT/ARRAY manipulations while adhering to performance best practices
• Manage and optimize DAGs, including troubleshooting task failures and improving run times
• Implement metadata management, data lineage, and security principles such as least-privilege access
• Use a test-driven approach to design systems that trap poor quality data and trigger alerts within the data flow
• Partner with engineering, data science, and business stakeholders to own project scopes
• Mentor others on data best practices to drive impact through your data vision
• Provide architectural guidance to ensure data is accessible and actionable across the company
• Drive technical excellence within the data engineering and analytics domain

What we're looking for

• 5+ years of experience in data/analytics engineering with proficiency in Python and SQL within Snowflake
• 3+ years of experience with dbt
• Owned large-scale data projects that drove significant impact through effective cross-functional partnering
• Led the design, implementation, and monitoring of data warehouses that enable clear product-focused insights
• Expert at SQL, window functions, and query optimization for complex data manipulations
• Applied performance best practices, including partitions, sort keys, and incremental modeling
• Designed systems using test-driven approaches to ensure data quality and flow integrity
• Familiarity with ELT processes and tools to prepare and clean data for analysis
• Skill in using tools like dbt to build data transformation pipelines
• Experience mentoring stakeholders in Data Science, Analytics, PM, and Engineering on data best practices

While not required, these are a plus:

• A dbt certification

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection.

When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $130,000.00 USD to $175,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis's total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans and more. #LI-CM1 #LI-Onsite

Who we are

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn’t coming; it’s here, and we need builders, innovators and problem solvers to help us create it.

Who you are

Metropolis is seeking a Senior Analytics Engineer to join our Data Engineering and Analytics team. The ideal candidate will possess a passion for creating value using data and a strong foundation in all aspects of analytics engineering. In this pivotal role, you will be instrumental in making data accessible and actionable, facilitating informed decision-making throughout the company. You will partner and lead across multiple product team functions and domains and drive impact through your data vision and architecture.

What you'll do

• Design and implement large-scale data warehouses and data marts using Snowflake, Star, or Data Vault 2.0 schemas
• Build and maintain data transformation pipelines using SQL frameworks like dbt to abstract model code
• Write complex SQL including window functions and STRUCT/ARRAY manipulations while adhering to performance best practices
• Manage and optimize DAGs, including troubleshooting task failures and improving run times
• Implement metadata management, data lineage, and security principles such as least-privilege access
• Use a test-driven approach to design systems that trap poor quality data and trigger alerts within the data flow
• Partner with engineering, data science, and business stakeholders to own project scopes
• Mentor others on data best practices to drive impact through your data vision
• Provide architectural guidance to ensure data is accessible and actionable across the company
• Drive technical excellence within the data engineering and analytics domain

What we're looking for

• 5+ years of experience in data/analytics engineering with proficiency in Python and SQL within Snowflake
• 3+ years of experience with dbt
• Owned large-scale data projects that drove significant impact through effective cross-functional partnering
• Led the design, implementation, and monitoring of data warehouses that enable clear product-focused insights
• Expert at SQL, window functions, and query optimization for complex data manipulations
• Applied performance best practices, including partitions, sort keys, and incremental modeling
• Designed systems using test-driven approaches to ensure data quality and flow integrity
• Familiarity with ELT processes and tools to prepare and clean data for analysis
• Skill in using tools like dbt to build data transformation pipelines
• Experience mentoring stakeholders in Data Science, Analytics, PM, and Engineering on data best practices

While not required, these are a plus:

• A dbt certification

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection.

When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $130,000.00 USD to $175,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis's total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans and more. #LI-CM1 #LI-Onsite

Who we are

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn’t coming; it’s here, and we need builders, innovators and problem solvers to help us create it.

Who you are

Metropolis is seeking a Senior Analytics Engineer to join our Data Engineering and Analytics team. The ideal candidate will possess a passion for creating value using data and a strong foundation in all aspects of analytics engineering. In this pivotal role, you will be instrumental in making data accessible and actionable, facilitating informed decision-making throughout the company. You will partner and lead across multiple product team functions and domains and drive impact through your data vision and architecture.

What you'll do

• Design and implement large-scale data warehouses and data marts using Snowflake, Star, or Data Vault 2.0 schemas
• Build and maintain data transformation pipelines using SQL frameworks like dbt to abstract model code
• Write complex SQL including window functions and STRUCT/ARRAY manipulations while adhering to performance best practices
• Manage and optimize DAGs, including troubleshooting task failures and improving run times
• Implement metadata management, data lineage, and security principles such as least-privilege access
• Use a test-driven approach to design systems that trap poor quality data and trigger alerts within the data flow
• Partner with engineering, data science, and business stakeholders to own project scopes
• Mentor others on data best practices to drive impact through your data vision
• Provide architectural guidance to ensure data is accessible and actionable across the company
• Drive technical excellence within the data engineering and analytics domain

What we're looking for

• 5+ years of experience in data/analytics engineering with proficiency in Python and SQL within Snowflake
• 3+ years of experience with dbt
• Owned large-scale data projects that drove significant impact through effective cross-functional partnering
• Led the design, implementation, and monitoring of data warehouses that enable clear product-focused insights
• Expert at SQL, window functions, and query optimization for complex data manipulations
• Applied performance best practices, including partitions, sort keys, and incremental modeling
• Designed systems using test-driven approaches to ensure data quality and flow integrity
• Familiarity with ELT processes and tools to prepare and clean data for analysis
• Skill in using tools like dbt to build data transformation pipelines
• Experience mentoring stakeholders in Data Science, Analytics, PM, and Engineering on data best practices

While not required, these are a plus:

• A dbt certification

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection.

When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $130,000.00 USD to $175,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis's total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans and more. #LI-CM1 #LI-Onsite

WORKING AT THE MLC

The MLC is committed to excellence, service, transparency, and diversity. Our culture is collaborative, our people are adaptable. On our team, you are respected, valued for your unique strengths and experiences, and empowered to identify and resolve your own challenges.

The Mechanical Licensing Collective (The MLC) is a nonprofit organization designated by the U.S. Copyright Office to administer blanket mechanical licenses for digital music services in the United States. Our mission is to ensure that songwriters, composers, and music publishers are accurately paid for the use of their music in the digital ecosystem. While our foundation is rooted in music licensing and rights administration, the scale and complexity of the data we process-billions of usage records from digital service providers-has positioned The MLC at the intersection of music and technology. As we continue to build and refine the systems that power matching, royalty processing, and rights management, we are increasingly operating like a technology company, developing sophisticated platforms, data infrastructure, and automation to support the future of digital music licensing.

THE ROLE

As a Quality Assurance Engineer, you will design, implement, and own the testing strategy for the Matching Platform. You will build and maintain automated testing frameworks and perform exploratory validation across workflows, APIs, integrations, and user-facing components to ensure the system behaves as intended and that changes do not introduce regressions. You will contribute production-quality testing code, establish testing standards and best practices, and work closely with the Matching Team throughout story refinement and implementation to ensure new functionality is testable, clearly defined, and validated before completion. The Matching Platform is a critical tool that enables The MLC to drive accurate royalty payments to our Members.

QUALIFICATIONS

• Minimum five (5) years’ experience in Quality Assurance or Quality Engineering within a software engineering team.
• Strong experience designing and implementing automated tests; able to write and maintain production-quality testing code.
• Hands-on experience with manual and exploratory testing in complex systems; able to validate behavior against business rules.
• Experience testing APIs and workflow-heavy or data-driven systems; proficient in SQL; experience working within AWS environments.
• Experience testing machine learning or probabilistic systems, building testing frameworks from scratch, or working with orchestration tools such as Dagster or Airflow is a plus.
• Strong attention to detail, clear documentation skills, and effective collaboration within Agile, cross-functional teams.
• Working proficiency in Python, familiarity with other languages is a plus.

ESSENTIAL RESPONSIBILITIES

AS A QA ENGINEER AT THE MLC, YOU WILL:

• Own the testing strategy for the Matching Platform, ensuring consistent validation across workflows, APIs, integrations, and user-facing components.
• Design, build, and maintain automated test suites in Python, establishing and evolving the team’s testing framework.
• Perform manual and exploratory testing before work is considered complete, validating complex workflows, identifying defects, edge cases, unintended behaviors, and deviations from business rules.
• Collaborate closely with engineers and product stakeholders during story refinement and development to ensure features are testable and clearly defined.
• Define and maintain QA standards and testing practices within the Matching Team, contributing to regression coverage as the platform evolves.
• Investigate and document defects clearly, working with developers to resolve issues prior to ticket completion.

AS A MEMBER OF THE TECHNOLOGY TEAM, YOU WILL:

• Advocate for quality throughout the development lifecycle, partnering with engineers to incorporate testing considerations early.
• Contribute to the evolution of scalable, automated QA practices across the Technology organization.
• Promote consistent standards for reliability, validation, and defect management.
• Participate in Agile ceremonies, providing a quality-focused perspective in planning and retrospectives.
• Support continuous improvement of engineering practices as systems grow in complexity.