Engineering - Data Engineer

About Us:
Read AI is a leading productivity AI company focused on helping individuals and businesses optimize their workflows across meetings, messages, and email. With seamless cross-platform integration with Microsoft Teams, Google Meet, Zoom, Slack, Hubspot, and Salesforce, Read AI revolutionizes how teams connect and collaborate by providing an AI copilot wherever they work.

We’re excited to share that we recently closed a $50 million Series B funding round, led by Smash Capital, with continued support from existing investors Madrona and Goodwater Capital. This new funding brings our total to $81 million, just six months after our Series A. We're just getting started, so if you're passionate about shipping early, often, and impacting millions, we'd love for you to join our growing team!

The Role:
As a Data Engineer at Read AI, your contributions will directly impact the functionality, scalability and reliability of our product. Our team is responsible for owning the data flows and ML infrastructure across the company, which includes realtime audio/video processing, interactions with third party llm providers, data processing orchestration, database management, data APIs, inferencing services, and transcription services.

Responsibilities:

• Collaborate with cross-functional teams to design and develop scalable and reliable backend services and APIs that power our platform.
• Take ownership of critical components of our system, from conception to deployment and maintenance.
• Practice quality assurance best practices including unit and integration testing.
• Optimize data processing pipelines and storage solutions.
• Integrate third-party services and data sources seamlessly into our platform.
• Monitor, troubleshoot, and resolve issues related to infrastructure and operations to ensure maximum uptime and reliability.
• Continuously evaluate and implement best practices, tools, and technologies to enhance the scalability, reliability, and maintainability of our systems.

Requirements:

• Bachelor's degree or higher in Computer Science/Engineering, or 3+ years of relevant industry experience.
• Proven experience in backend development, with proficiency in one or more programming languages such as Python, Java, or Go.
• Strong understanding of distributed systems, microservices architecture, and cloud computing platforms (e.g., AWS, GCP).
• Familiarity with relational and non-relational databases, along with expertise in data modeling and database management.
• Excellent problem-solving skills with a pragmatic and results-driven approach.
• Ability to thrive in a fast-paced startup environment with a high degree of autonomy and accountability.
• Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams.

Nice to Have:

• Experience with containerization and orchestration tools such as Docker and Kubernetes.
• Experience with big data processing tools such as Flink and Spark.
• Experience with Python, Pydantic, FastAPI, and SQLAlchemy.
• Familiarity with CI/CD pipelines and DevOps practices.
• Prior experience in a startup or fast-growing environment.