Role Overview
Oyster is seeking a Senior Data Engineer to join the product development team remotely within the UTC-6 to UTC+3 time zones. This position focuses on the AI Platform, requiring an expert to build data pipelines, services, and reusable platform capabilities that support generative AI and machine learning workflows.
Key Responsibilities
Design and construct data pipelines and platform capabilities that drive AI applications, knowledge systems, and workflows.
Develop and maintain data and knowledge pipelines handling ingestion, chunking, transformation, embeddings, retrieval, vector search, metadata, and knowledge management.
Create secure, reusable access methods for AI systems to interact with enterprise data using APIs, tool calling, and MCP patterns.
Build reusable services, frameworks, libraries, and developer tooling to simplify the creation and productionization of AI capabilities for engineering teams.
Apply robust data engineering principles covering data modeling, data quality, lineage, governance, security, and reliability.
Establish operational patterns for AI deployment, lifecycle management, observability, quality, latency, and cost.
Collaborate with stakeholders and engineers to transition AI use cases from prototypes to reliable, scalable production systems.
Ensure all platform capabilities adhere to Oyster's data governance, privacy, security, and access control policies.
Evaluate emerging technologies in data and AI to identify opportunities that deliver value to the organization.
Requirements
Minimum of 5 years of professional experience in data engineering, platform engineering, backend engineering, ML engineering, or a related domain.
Strong programming capabilities in Python and SQL.
Solid foundational understanding of data engineering, including data modeling, pipelines, orchestration, data quality, and secure data access.
Experience working with modern data platforms like Snowflake or Databricks, alongside tools such as Airflow and dbt.
Hands-on experience supporting or building production systems utilizing generative AI and LLMs.
Practical background in vector search, RAG, embeddings, AI agents, tool calling, or enterprise knowledge systems.
Experience designing reusable data or platform capabilities across multiple teams rather than single-use solutions.
Proven ability to scale and maintain systems moving from experimental stages to reliable production environments.
Clear understanding of enterprise security, authentication, authorization, data governance, and privacy.
Effective communication skills to bridge Engineering, Product, and IT departments.
Fluent English language skills and a reliable home internet connection.
Nice to Have
Experience utilizing AWS Bedrock or comparable managed foundation-model platforms.
Hands-on background with MCP or similar connectivity approaches for AI and enterprise tools.
Familiarity with LLM monitoring, observability, evaluation, or AI quality metrics.
Experience utilizing frameworks such as LangChain or LangGraph.
Background working with vector databases or search technologies.
Experience implementing responsible AI practices, security, or governance frameworks.
Experience designing internal developer platforms, APIs, SDKs, or reusable infrastructure.
Skills and Tools
Python
SQL
AWS
LLMs
LangChain
RAG
Airflow
Snowflake
dbt
Salary and Benefits
40 days of paid time off per year including holidays and vacation.
Access to Plumm for mental well-being support.
Monthly wellbeing allowance provided through a ThanksBen wallet.
Flexible parental leave offering at least three months of paid leave for new parents.
A work-from-home stipend for a laptop and necessary home office equipment.
Fully remote working environment with no physical borders or central headquarters.
About the Company
Oyster is a global employment platform dedicated to making it easier for companies to hire, pay, and care for team members anywhere in the world. Operating as a distributed team across more than 60 countries, Oyster is recognized as a B Corp-certified platform committed to fostering an inclusive, equal working environment.
How to Apply
Interested candidates should visit the official Oyster careers page to submit their application.
