EMEA•Romania•Kenya•Portugal•United Kingdom•Spain•South Africa•Nigeria
Remote
Senior
Full Time
remoteAIplatform engineeringsenior leveldistributed teamfully remote
Requirements
- •5+ years in data engineering, platform engineering, backend engineering, or a related discipline, with experience building and operating production systems
- •Strong Python and SQL skills
- •Hands-on experience building and deploying production applications or services using LLMs / generative AI
- •Experience with RAG, embeddings, vector search, tool/function calling, AI agents, or enterprise knowledge systems
- •Strong data engineering fundamentals, including pipelines, data modeling, data quality, and secure data access
- •Experience with Snowflake, Databricks, or comparable modern data platforms, plus tools such as dbt, Airflow, or similar
- •Experience building shared AI infrastructure, platforms, or reusable AI capabilities, rather than only integrating AI into individual applications
- •Experience taking AI systems from experimentation to reliable production
- •Solid understanding of security, authentication/authorization, privacy, and data governance
- •Strong communicator who can translate ambiguous AI opportunities into practical engineering solutions across teams
- •A reliable home internet connection (or be able to get one)
- •Fluent English language skills
What You'll Do
- •Design and build reusable platform capabilities for LLM applications, AI agents, RAG, tool calling, and AI workflows
- •Build data and knowledge pipelines supporting ingestion, embeddings, retrieval, vector search, metadata, and knowledge management
- •Develop secure integrations between AI applications and enterprise data and systems using APIs, MCP, tool calling, and similar patterns
- •Build reusable frameworks, libraries, services, and developer tooling so engineering teams can build AI applications without repeatedly solving the same foundational problems
- •Establish patterns and standards for AI deployment, observability, evaluation, and lifecycle management, including quality, accuracy, latency, security, reliability, and cost
- •Help take AI capabilities from prototype to production, building for reliability, scalability, and maintainability
- •Ensure that the AI platform's capabilities meet Oyster’s security, privacy, access control, and data governance requirements
- •Evaluate emerging AI models, frameworks, and infrastructure technologies and determine where they can create meaningful value for Oyster
Nice to Have
- •Experience with AWS Bedrock or other managed foundation-model platforms
- •Hands-on experience with MCP (Model Context Protocol) or similar approaches for connecting AI to enterprise tools and data
- •LLM evaluation, observability, monitoring, or AI quality experience
- •Experience with LangChain, LangGraph, or similar frameworks
- •Vector database or search technology experience
- •Experience implementing AI security, governance, or responsible AI practices
- •Experience building internal developer platforms, SDKs, APIs, or reusable infrastructure for engineering teams
Benefits
- •Work from anywhere within UTC−6 to UTC+3 timezone
- •40 days off per year including holidays and vacation or more if required by country
- •Mental health support via Plumm service
- •Monthly wellbeing allowance in ThanksBen wallet
- •Flexible parental leave with at least three months paid leave and job protection for up to 12 months or as required locally
- •Work from home stipend for laptop and home office equipment
About Oyster
Oyster is a distributed HR platform that offers companies to hire, pay, and care for teammates.
Charlotte, NC, US
500-1000
HR & Recruiting