Senior Engineer, Data & AI - Temporary
V
Vox MediaMedia technology
Source API remote eligibility restrictions: United StatesTemporarySenior
Salary127,000 - 180,000 USD per year
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Job Details
- Required Skills
- PostgreSQLPythonSQLFastAPIdbtGenerative AI
Requirements
- Have experience as a Python backend engineer or data engineer, with a focus on high-quality production-grade code.
- Be comfortable building and deploying APIs and services in cloud-native environments; FastAPI experience is preferred.
- Be fluent in SQL.
- Have experience with analytics workflows in a cloud data warehouse or relational databases such as Postgres.
- Have an interest in applying generative AI and LLM tooling to real-world problems.
- Be thoughtful about architecture, trade-offs, and making systems easy for others to build on.
- Be comfortable working independently, collaborating across functions, and shifting between scoped projects and open-ended discovery work.
- Bonus: experience with semantic search, embedding-based retrieval, recommendation systems, or agentic system design.
- Bonus: experience with data modeling and orchestration tools such as dbt and Dagster, or willingness to learn.
- Bonus: exposure to LLM frameworks such as Pydantic AI or LangChain.
Responsibilities
- Build and maintain production-grade backend services using the team's typical Python, FastAPI, PostgreSQL, and Google Cloud Run stack.
- Develop and evolve AI-powered applications using provider APIs such as OpenAI or Gemini and open-source tools and frameworks.
- Contribute to Remix, enabling search, recommendations, personalized marketing, and other reader-facing and internal experiences.
- Help maintain and extend VoxStar, the user data store and internal memory layer for personalized experiences.
- Write structured code, tests, and documentation for services operating at scale and supporting multiple use cases.
- Contribute to API design for services.
- Create deployment workflows, tune database and query performance, and manage lightweight cloud infrastructure.
- Collaborate with product, audience, and editorial stakeholders to translate problems into technical solutions.
- Contribute to data engineering workflows to build datasets and tools using Python and SQL.
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