About the job
About Us We're a venture-backed startup building an innovative AI-driven platform called Proxi for policy professionals. Our product helps users navigate complex regulatory, legislative and emerging compliance environments through a voice-driven interface powered by our cutting-edge semantic search pipeline operating over our immense legislative and regulatory data corpus. Our team's experience spans roles across the White House, State Department, K&S Law, Microsoft and Datadog.
The Role You'll join our founding engineering team to enhance and scale the existing data infrastructure and processing pipelines that form the backbone of our platform. Working with our current systems, you'll help expand our real-time data velocity advantage and optimize our scalable architecture that handles vast amounts of legislative and regulatory information while supporting seamless voice interactions.
Location: New York City
Key Responsibilities
- Extend and optimize our real-time data ingestion pipelines to incorporate additional legislative and regulatory sources
- Enhance our document processing workflows to support new data formats and improve efficiency
- Optimize existing database schemas and search indices for improved performance
- Scale and refine our cloud infrastructure to maintain reliability as we grow
- Enhance our low-latency voice streaming and real-time conversation capabilities
- Improve and maintain our CI/CD pipelines for streamlined deployment
- Extend our NLP-enhanced data transformation systems to support new use cases and data types
- Collaborate with ML engineers to support evolving data needs for relevance and personalization systems
Requirements
- Strong Python proficiency for backend development and data processing
- Experience with cloud platforms (GCP preferred) including serverless computing and storage
- Must have Expertise in optimizing and scaling existing data pipelines and ETL processes
- Strong database skills with PostgreSQL, including query optimization and performance tuning
- Experience with real-time streaming architectures and low-latency response systems
- Experience with containerization (Docker) and CI/CD workflows
- Knowledge of search technologies and vector storage solutions
- Understanding of asynchronous programming patterns in Python
- Experience with API development using modern frameworks
- Strong problem-solving skills for troubleshooting complex distributed systems
Nice to Have
- Experience with API integration for comprehensive data collection
- Background in legislative or regulatory data processing
- Knowledge of workflow orchestration tools like Apache Airflow
- Experience with audio streaming and voice processing technologies
- Familiarity with MLOps practices and supporting ML systems in production
- Experience integrating and optimizing LLM usage in data workflows
- Knowledge of Infrastructure as Code (IaC) tools
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