Senior AI Product Engineer

Oyster

. Own complex Oyster AI improvements end to end, from problem definition and solution design through evaluation, rollout, and production learning .

Posted 11/5/2026full-timeRemoteSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing LLM-powered product capabilities, with a strong focus on retrieval strategies, evaluation datasets, and system design. Proven ability to lead complex production work while ensuring effective communication and collaboration across teams.

Highest-signal resume keywords

LLM-Powered Product CapabilitiesRetrieval/RAG and IndexingCoding, Debugging, and TestingRuby/Rails and ReactTechnical Guidance and Mentoring

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

System DesignAPI IntegrationError HandlingData Access ControlProduction DeploymentEvaluation InfrastructureAutomated JudgesModel RoutingCost ControlsDebugging

Soft Skills

Clear CommunicationEffective CollaborationMentoringJudgmentProblem-Solving

Tools & Technologies

Ruby on RailsReactSlack IntegrationIn-App AssistantRetrieval Pipelines

Industry Keywords

AI CapabilitiesOyster AIProduction ScaleEmployment PlatformData Access Boundaries

Tech Stack

Tools & technologies

ReactRubyRuby on Rails

About the role

Key responsibilities & impact

Own complex Oyster AI improvements end to end, from problem definition and solution design through evaluation, rollout, and production learning
Design reliable agents and tools with clear contracts, robust error handling, bounded execution, and appropriate human control
Improve knowledge access through retrieval, embedding, indexing, and freshness strategies while respecting data-access boundaries
Build trustworthy evaluation loops using representative datasets, experiments, regression checks, and automated judges calibrated against human judgment
Diagnose and fix production failures across prompts, retrieval, tools, models, and infrastructure, then verify fixes with evidence
Make deliberate model and system-design trade-offs and document decisions and rollout criteria
Support product teams through technical guidance, code review, pairing, and mentoring
Build AI capabilities for Oyster, a global employment platform that helps companies hire, pay, and care for talent worldwide

Requirements

What you’ll need

Senior-level engineering judgment and a track record of independently leading complex production work from design through operation and improvement
Hands-on experience shipping LLM-powered product capabilities to production, with personal responsibility for implementation and delivery decisions
Depth in retrieval/RAG and indexing, evaluation datasets and experiments, LLM-as-judge, or agents and tool calling
Ability to distinguish model, retrieval, tooling, and application failures and validate improvements with evidence
Strong fundamentals in coding, debugging, testing, API integration, and system design
Willingness to work in Ruby/Rails and React
Sound judgment regarding sensitive data, access control, model limitations, and operational risk
Clear communication of trade-offs, effective asynchronous collaboration, and practical mentoring
Regular work-hour overlap with colleagues in the Americas and Europe, approximately UTC-4 to UTC+1
Authorization to work where you live
Nice to have: production Ruby on Rails experience
Nice to have: full-stack conversational or assistant experience
Nice to have: Slack or in-app assistant integration experience
Nice to have: experience operating retrieval pipelines, agent tools, evaluation infrastructure, model routing, and cost controls at production scale
Nice to have: experience helping multiple teams adopt reusable AI patterns

Benefits

Comp & perks

Work from anywhere, subject to timely work, team support, and authorization to work where you live
40 days off per year, including holidays and vacation, or more if required by country
Plumm mental well-being service
Monthly wellbeing allowance through ThanksBen wallet
At least three months’ paid parental leave for all new parents
Job protection for up to 12 months or as required locally
WFH stipend for laptop and home office equipment
Fully remote, async-friendly work culture
Opportunity to work on real AI products for real users
Ownership of complex AI engineering problems
Mentoring and multiplier impact across product teams
Stack-agnostic hiring with room to grow into Rails and React