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Oyster

Senior Director, Data Platform and AI

RemoteUTC-7…UTC+3
Published
Role
Engineering Management
Experience
Senior
Employment
Full-time
Salary not disclosed
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Open to UTC-7…UTC+3. Set where you work from to check your eligibility.

No BS summary

Senior Director-level data and AI leadership role owning the platform's data strategy and AI transformation. Requires deep technical track record in distributed systems, MLOps, and LLM orchestration, as well as proven success driving organizational adoption of AI. Fully remote, but candidates must be based within UTC-7 to UTC+3 and are required to live in that time zone range.

Core skills

LLM orchestrationData PlatformMLOps

Required skills

distributed data systemsMLOps pipelines

Optional skills

semantic search solutionsretrieval-augmented generation (RAG) engine layersmulti-tenant customer data structures

Required languages

English fluent (spoken and written)

What you'll do

  • Drive the company-wide AI agenda: scaling local AI initiatives into centralized production systems that create measurable business value.
  • Own broad, high-impact AI initiatives that have cross functional impact: Moving our AI usage from past narrow or siloed automation examples to execute a company operational transformation.
  • Partner with Product, Engineering, and operational leaders to embed AI capabilities into our customer-facing platform, internal business workflows, and core processes.
  • Serve as the ultimate technical authority for our data and AI infrastructure, making critical architectural decisions across MLOps pipelines, LLM orchestration frameworks, and distributed data systems.
  • Oversee the development of a scalable corporate data platform that serves as the foundational bedrock for all AI and machine learning capabilities.
  • Transform our internal knowledge base by building the systemic data architecture needed to turn unstructured information into intelligent, easily searchable, and actionable assets.
  • Re-build and evolve our company-wide data structures and connectivity pipelines to be optimized to deploy, run, and maintain AI models efficiently while lowering cost-to-serve.
  • Set the company-wide tooling standards, maintain technical quality guardrails, and establish engineering best practices for embedded AI specialists working within roles.
  • Actively support the implementation of key local solutions built by decentralized specialists, ensuring they have the necessary tools and centralized platform support to success.
  • Maintain high levels of ethical compliance by ensuring all global AI initiatives strictly adhere to data privacy, platform security, and open data protection standards.
  • Educate and empower teams across the organization to scale their own AI use productively, providing them with the structural frameworks needed to safely build and innovate.
  • Partner deeply with the People and Operations functions to champion Amazon AI capability, replacing operational uncertain with structural training loops that convert manual specialists into power-users of automated solutions.
  • Drive the organizational change management and training literacy efforts required to move daily habits from traditional manual processes to AI-rounded operations.

What they require

  • A genuine passion for artificial intelligence that goes far beyond product feature delivery. Demonstrated interest in and concrete evidence of driving organizational change, specifically regarding how AI reshapes day-to-day employee workflows and habits.
  • Proven experience operating within a delivery / highly complex operational business, where data strategy directly impacts intricate, real-world workflows and diverse stakeholders.
  • A history weighted heavily toward data engineering, distributed systems development, platform services infrastructure, and system architecture over front-end application design.
  • Proven deep technical experience in distributed data systems, MLOps pipelines, and LLM orchestration. Able to evaluate and recommend complex models and emerging technologies as ultimate technical authority.
  • Documented success building, testing, and scaling complex asynchronous data structures, machine learning routing layers, or high-volume API integrations in modern software platforms.
  • Ability to view the organization holistically, using understanding of interconnected technical platforms, business processes, and human teams to design solutions that optimize entire workstreams.
  • Proven ability to drive early adoption for major technology or workflow transformations, break down complex AI frameworks for non-technical audiences, and shift habits.
  • Comprehensive familiarity with model validation systems, technical anomaly logging, data pipeline health metrics, and automated governance frameworks (e.g., custom logging models or open-source validation pipelines).
  • Bonus: Background architecting search solutions, retrieval-augmented generation (RAG) engine layers, or multi-tenant customer data structures from zero-to-one phases.
  • A reliable home internet connection.
  • English language skills required.

Benefits

  • Work anywhere: all Oyster roles are fully remote and remote.
  • Paid time off: 40 days off per year (including holidays and vacation), or more if required by country.
  • Mental health support: Plumm wellness service.
  • Wellbeing allowance – monthly allowance using ThanksBen wallet.
  • Flexible parental leave: at least three months paid leave, with job protection up to 12 months or as the period.
  • WFH stipend: stipend for laptop and home office equipment.

Oyster is a global employment platform that lets companies hire, pay, and care for people anywhere. It operates across Employer of Record, Global Employment, Multi-country Payroll, and HR Compliance, is distributed across 60+ countries since 2020, and is B Corp-certified.

HRTechMid-size
Salary not disclosed