Senior AI Platform Engineer

Role Description

Oyster’s Data Engineering team is building the foundational AI platform layer that will enable teams across Oyster to develop, deploy, and operate secure, production-grade AI applications.

As an AI Platform Engineer , you’ll build the shared infrastructure, services, integrations, and developer tooling that sit beneath these applications. You’ll work hands-on with LLMs, AI agents, RAG, tool calling, and AI workflows, leveraging Oyster’s existing AWS/Snowflake data platform to turn AI use cases from experimentation into reliable, production-ready systems.

You’ll partner closely with Engineering, Product, and IT to establish the platform primitives, technical patterns, and guardrails that allow Oyster to build and scale AI securely and effectively.

Key Responsibilities

• 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.

Qualifications

• 5+ years in data engineering, platform engineering, backend engineering, or a related discipline, with experience building and operating production systems.
• Strong Python and SQL.
• 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.

Requirements

• 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: Oyster has no borders or HQ. As long as work is timely, your team is supported, and you're authorized to work where you live, you can work from anywhere.
• Paid time off: Enjoy 40 days off per year (including holidays and vacation), or more if required by your country.
• Mental health support: Access Plumm, our mental well-being service.
• Wellbeing allowance: Each month, receive a wellbeing allowance in your ThanksBen wallet to spend on a wide range of options.
• Flexible parental leave: All new parents are eligible for at least three months’ paid leave, with job protection for up to 12 months or as required locally.
• WFH stipend: Receive a stipend for your laptop and home office equipment to get you set up quickly.