TL;DR

Fast-growing measurement company looking for a Python Backend Software Engineer to build and maintain the services that power our attention metric, AU. You'll be joining a company making a positive impact on the digital media market using evidence-based metrics to increase the transparency of media quality.

Position overview

This position reports to the Director of Engineering and joins a team of backend, data, and DevOps engineers building the services behind Adelaide's measurement products, including the high-throughput APIs that ingest tracking data at scale and the partner-facing services that expose our segments and scoring to demand-side platforms. You'll design, build, and maintain async Python services on FastAPI, working closely with Data Engineering and Data Science to move data reliably from client-side collection through to storage and downstream analytics, and you'll get regular hands-on exposure to the data pipelines and cloud infrastructure that feed those services.

Day-to-day activities include writing and testing async Python code, designing and maintaining FastAPI services, working with AWS services such as Kinesis Firehose, S3, RDS/Postgres, Redshift, and MWAA Airflow, tuning batching and performance-sensitive request paths, and participating in code reviews.

We're seeking a candidate with 3-5 years of professional software engineering experience, with most of it in Python.

This is a fully remote role within the United States, with opportunities to connect with colleagues at our New York office. You'll need to be in NYC a few times per year.

Compensation

• Base Salary Range: $140,000 - $160,000

This role includes a competitive compensation package consisting of base salary, performance-based bonus, and equity. Final compensation will be determined based on experience, level, and location.

What you'll learn
An important part of our culture is continuous learning and the open sharing of ideas. We offer:

• Access to a broad network of investors and advisors who can help you and your team succeed
• Mentorship from executives with decades of experience in adtech and media
• Regular internal knowledge-sharing sessions
• An education budget to support ongoing professional growth and development

Specifically, In this role, you'll learn:

• How to design and scale backend services that process hundreds of millions of data points a day
• Best practices for building on AWS and working alongside data engineering and data science teams
• Fundamentals of maintaining the data pipelines and infrastructure that power your services
• How attention metrics and media quality measurement work under the hood
• How to collaborate effectively across teams to meet stakeholder needs

Core responsibilities

• Design, build, and maintain backend services and APIs in Python that power Adelaide's measurement products.
• Collaborate with Data Engineering and Data Science to integrate models and data pipelines into production services, including contributing to Airflow-orchestrated ETL/ELT workflows.
• Write clean, well-tested, maintainable code and participate actively in code review.
• Help diagnose and resolve production issues, contributing to monitoring, alerting, and reliability improvements.
• Work with the broader engineering team to improve system architecture, performance, and developer workflows.
• Partner with Product and Customer Success to translate requirements into shipped, well-scoped features.

What you'll bring

• Strong Python Fundamentals: Proven experience building and maintaining production backend services or APIs in Python (FastAPI or a comparable async framework), with solid testing (pytest) and code review practices.
• Async & Performance Awareness: Comfort with asyncio-based services, request batching, and reasoning about latency and throughput in high-volume, low-latency APIs.
• Data & Typing Discipline: Working knowledge of Pydantic (or similar) for request/response validation and settings management, and comfort with static typing (mypy) in a production codebase.
• Cloud & Data Comfort: Working experience with AWS (Kinesis/Firehose, S3, RDS, or similar) and relational databases (Postgres), plus comfort working with moderately large datasets and some exposure to data pipeline/orchestration tools such as Airflow.
• Collaborative Problem Solver: Comfortable working cross-functionally with Data Engineering, Data Science, and Product to turn requirements into shipped features.

What will set you apart

• Exposure to data pipeline or workflow tools such as Airflow, or data tooling like Pandas, Polars/PyArrow.
• Experience with OAuth2 / JWT-based authentication flows for service-to-service APIs.
• Familiarity with uv (or another modern Python package/dependency manager) and linting/formatting tooling such as Ruff.
• Experience with structured logging (structlog or similar) and observability practices for production services.
• Comfort with Docker and Docker Compose for local development and integration testing.
• IaC experience, ideally with Terraform (CloudFormation also a plus).
• Exposure to AWS Glue, EMR, or Lambda for batch/serverless data processing
• Familiarity with ECS for containerized data workflows (complements the existing Docker bullet)
• Basic knowledge of data visualization or BI tools (e.g., Looker, Tableau, QuickSight)
• Exposure to CI/CD tooling such as GitHub Actions or AWS CodeBuild for data pipeline deployment

Benefits

Health & Wellness

• Medical, dental, and vision insurance
• Paid time off
• Parental leave
• Employee development & wellness stipend
• Holiday break
• Volunteer time off

Financial & Compensation

• Competitive salary
• Performance-based quarterly bonus
• Stock options
• 401(k) retirement plan

Workplace & Equipment

• Remote-first environment
• New York office access
• Access to available WeWork spaces