About the role
Oyster provides a global employment platform that lets companies hire, pay, and care for talent anywhere. This role owns building the AI platform layer, data pipelines, and reusable capabilities that power AI use cases across Oyster. You will work with engineering, product, and IT to move AI use cases from prototype to production.
What you'll do
- Design and build data pipelines and platform capabilities that support AI applications and workflows.
- Build and maintain data and knowledge pipelines for ingestion, transformation, embeddings, retrieval, and vector search.
- Develop secure, reusable access methods for enterprise data using APIs and tool calling.
- Create reusable services, libraries, and developer tooling to productionize AI capabilities.
- Apply data engineering practices for data modeling, quality, lineage, access, reliability, and governance for AI data.
- Partner with engineers and stakeholders to scale AI use cases from prototype to production while ensuring security and observability.
What they're looking for
- 5+ years in data engineering, platform engineering, backend engineering, ML engineering, or related roles with production systems experience.
- Strong Python and SQL skills with solid data engineering fundamentals.
- Experience with Snowflake, Databricks, or comparable platforms and tools such as dbt and Airflow.
- Hands-on experience building or supporting production systems using LLMs or generative AI and practical work with embeddings, RAG, vector search, or AI agents.
- Ability to build data or platform capabilities that are reusable across teams and take systems from experimentation to production with insights on scalability and governance.
- Strong collaboration and communication across engineering, product, and IT teams.
For applicants in Nigeria
- The role is fully remote and can be worked from home, with the requirement that you are based within UTC-6 to UTC+3.
- The listing states worldwide eligibility, so Nigerian applicants are eligible; confirm any local or visa requirements during interviews.
- The listing does not state pay currency or salary range; confirm currency and compensation during interview.
- The listing does not specify whether the role is contractor or employee; confirm employment type during interview.
- No visa or work-authorization notes are provided beyond worldwide eligibility; confirm needs during process.
Summarized by RemoteWork from the original listing. Always confirm details on the employer’s page.