Odore

We are global advocacy platform powering creator communities for the world's leading beauty and personal care brands. Founded in 2019, we help brands like L'Oréal, Estée Lauder, Coty, and Unilever build authentic relationships with millions of creators, driving user-generated content at scale.

What We Do:

• Connect brands with 350M+ creators globally through our proprietary database
• Power advocacy programs across 40+ markets (US, UK, EU, LATAM, Middle East, Asia)
• Process millions of creator interactions, content submissions, and campaign data points monthly
• Handle sensitive personal data (PII), financial transactions, and brand-creator relationships

Our Scale:

• Trusted by Fortune 500 beauty & personal care brands
• Processing 100k+ creator content submissions monthly
• Operating in 40+ countries with localized compliance requirements

Why Join Us:

• High-growth SaaS scale-up at the intersection of social, beauty, and enterprise tech
• Build security & compliance infrastructure from the ground up - you'll own it
• Work directly with Fortune 500 clients (L'Oréal, Unilever, Estée Lauder)
• Remote-first culture with global team
• Meaningful equity stake in a fast-growing company

The Role: Head of Information Security & Compliance

As our first Head of InfoSec & Compliance, you'll be the guardian of trust - ensuring we meet the highest standards of data protection, security, and regulatory compliance as we scale globally. You'll build our compliance framework from the ground up, own enterprise client security reviews, and future-proof our platform for SOC 2, ISO 27001, and global data privacy regulations.

This is a foundational role. You'll have the autonomy to shape our security posture, define policies, and build the systems that enterprise clients demand.

What You'll Do

Compliance & Regulatory (40%)

• Own GDPR, CCPA, LGPD, and emerging data privacy regulations across 40+ markets
• Maintain SOC 2 Type II certification (or lead first certification if not yet achieved)
• Prepare for ISO 27001 certification roadmap
• Manage DPIAs (Data Protection Impact Assessments) for new features/markets
• Be the go-to expert for client compliance questionnaires, security reviews, and audits
• Ensure vendor compliance (AWS, payment processors, third-party APIs)

Client Security & Enterprise Sales Enablement (30%)

• Own enterprise client security reviews (infosec questionnaires, pen test reports, architecture reviews)
• Support sales team with security documentation, certifications, and client security calls
• Build & maintain security collateral (security white papers, data flow diagrams, compliance matrices)
• Act as security liaison for enterprise clients (L'Oréal, Unilever, Estée Lauder)
• Negotiate data processing agreements (DPAs) and BAAs

InfoSec Infrastructure & Risk Management (30%)

• Design and implement security policies, procedures, and controls
• Conduct regular risk assessments and threat modeling
• Manage vulnerability management program (pen tests, bug bounties, security scanning)
• Oversee incident response planning and execution
• Drive security awareness training for engineering and ops teams
• Monitor security tools (SIEM, CASB, endpoint protection) and respond to alerts

We are seeking a highly skilled Senior AI Engineer to design, integrate, and optimize AI-driven solutions across our platform. This role will focus on integrating existing AI tools and services, enhancing data processing and analysis workflows with AI, and laying the technical foundation for advanced AI capabilities.

You will work closely with backend, frontend, and product teams, and over time, grow into an AI Lead position, shaping the long-term AI strategy and architecture.

Key Responsibilities

AI Integration & Architecture

• Integrate and orchestrate third-party and in-house AI/ML tools (e.g., LLMs, embeddings, vector databases, AI APIs).
• Design scalable AI-powered services that integrate seamlessly with existing systems.
• Evaluate new AI technologies and tools, and recommend adoption based on business impact.

Data Processing & AI Optimization

• Optimize data pipelines for AI-driven processing, analysis, and automation.
• Apply AI techniques to improve data quality, insights generation, and operational efficiency.
• Collaborate with data and product teams to translate business needs into AI solutions.

Backend & Frontend Collaboration

• Build and maintain AI-enabled backend services using Python, AWS, and RESTful APIs.
• Expose AI capabilities via well-structured APIs for frontend consumption.
• Work with frontend engineers to integrate AI features into React applications.

Scalability, Reliability & Security

• Ensure AI solutions are production-ready, scalable, cost-efficient, and secure.
• Monitor performance, latency, and accuracy of AI systems in production.
• Implement best practices for model versioning, observability, and responsible AI use.

Leadership & Growth

• Act as a technical mentor for engineers working with AI-related features.
• Contribute to defining AI standards, best practices, and long-term roadmap.
• Gradually take ownership of AI architecture and strategy, growing into an AI Lead role.

Required Qualifications

• 5+ years of relevant experience in software engineering, machine learning, or AI-focused roles.
• Strong proficiency in Python, with experience building production backend systems.
• Hands-on experience with AI/ML integration, including LLMs, ML APIs, or AI platforms.
• Experience with AWS (e.g., EC2, Lambda, S3, SageMaker, or similar services).
• Solid understanding of RESTful API design and microservice architectures.
• Experience collaborating with frontend teams using React or similar frameworks.
• Strong knowledge of data processing, analysis pipelines, and performance optimization.
• Ability to design systems that balance experimentation with production reliability.

Nice to Have

• Experience with MLOps, model deployment, and monitoring.
• Familiarity with vector databases, retrieval-augmented generation (RAG), or agent-based systems.
• Experience optimizing AI cost, latency, and inference performance.
• Prior experience mentoring engineers or leading technical initiatives.
• Exposure to AI ethics, governance, and compliance considerations.

What We Offer

• Opportunity to build and scale AI capabilities in a real-world production environment.
• Clear growth path toward an AI Lead position with strategic ownership.
• High level of autonomy and technical influence.
• Collaborative environment working across backend, frontend, and product teams.
• Competitive compensation and benefits, commensurate with experience.

We are seeking a highly skilled Lead AI Engineer to design, integrate, and optimize AI-driven solutions across our platform. This role will focus on integrating existing AI tools and services, enhancing data processing and analysis workflows with AI, and laying the technical foundation for advanced AI capabilities.

You will work closely with backend, frontend, and product teams, and over time, grow into an AI Lead position, shaping the long-term AI strategy and architecture.

Key Responsibilities

AI Integration & Architecture

• Integrate and orchestrate third-party and in-house AI/ML tools (e.g., LLMs, embeddings, vector databases, AI APIs).
• Design scalable AI-powered services that integrate seamlessly with existing systems.
• Evaluate new AI technologies and tools, and recommend adoption based on business impact.

Data Processing & AI Optimization

• Optimize data pipelines for AI-driven processing, analysis, and automation.
• Apply AI techniques to improve data quality, insights generation, and operational efficiency.
• Collaborate with data and product teams to translate business needs into AI solutions.

Backend & Frontend Collaboration

• Build and maintain AI-enabled backend services using Python, AWS, and RESTful APIs.
• Expose AI capabilities via well-structured APIs for frontend consumption.
• Work with frontend engineers to integrate AI features into React applications.

Scalability, Reliability & Security

• Ensure AI solutions are production-ready, scalable, cost-efficient, and secure.
• Monitor performance, latency, and accuracy of AI systems in production.
• Implement best practices for model versioning, observability, and responsible AI use.

Leadership & Growth

• Act as a technical mentor for engineers working with AI-related features.
• Contribute to defining AI standards, best practices, and long-term roadmap.
• Gradually take ownership of AI architecture and strategy, growing into an AI Lead role.

Required Qualifications

• 5+ years of relevant experience in software engineering, machine learning, or AI-focused roles.
• Strong proficiency in Python, with experience building production backend systems.
• Hands-on experience with AI/ML integration, including LLMs, ML APIs, or AI platforms.
• Experience with AWS (e.g., EC2, Lambda, S3, SageMaker, or similar services).
• Solid understanding of RESTful API design and microservice architectures.
• Experience collaborating with frontend teams using React or similar frameworks.
• Strong knowledge of data processing, analysis pipelines, and performance optimization.
• Ability to design systems that balance experimentation with production reliability.

Nice to Have

• Experience with MLOps, model deployment, and monitoring.
• Familiarity with vector databases, retrieval-augmented generation (RAG), or agent-based systems.
• Experience optimizing AI cost, latency, and inference performance.
• Prior experience mentoring engineers or leading technical initiatives.
• Exposure to AI ethics, governance, and compliance considerations.

What We Offer

• Opportunity to build and scale AI capabilities in a real-world production environment.
• Clear growth path toward an AI Lead position with strategic ownership.
• High level of autonomy and technical influence.
• Collaborative environment working across backend, frontend, and product teams.
• Competitive compensation and benefits, commensurate with experience.

We’re hiring a Campaign Data Analyst to enhance the depth and consistency of insights across our client reporting and campaign optimisation.

You’ll analyse live campaign performance, community behaviour, and platform data to identify key patterns and opportunities that improve engagement, conversion, and ROI.

Key Responsibilities

• Analyse campaign and platform data to identify what drives performance by brand, market, category, and audience segment.
  
   
• Deep-dive into existing reports to uncover new insight layers — post rates, engagement drivers, creator types, and reward performance.
  
   
• Build concise insight summaries and dashboards that help teams optimise campaigns in real time.
  
   
• Collaborate with Customer Success Managers to turn findings into tactical changes and client recommendations.
  
   
• Connect raw campaign data with platform metrics (creator demographics, community health, engagement ratios).
  
   
• Support continuous improvement of reporting templates and measurement frameworks.
  
   
• Work with the Product team to refine data capture, tagging, and visualisation.
  
   

What You’ll Bring

• 2–4 years’ experience in data, marketing analytics, or performance analysis.
  
   
• Strong analytical skills and comfort with spreadsheets or BI tools (Excel, Google Sheets, Looker Studio, etc.).
  
   
• Ability to interpret marketing and campaign data into clear, commercial insight.
  
   
• Solid grasp of metrics like CTR, engagement rate, conversions, and ROI.
  
   
• Comfortable presenting findings to non-technical stakeholders.
  
   
• Detail-oriented, curious, and able to balance data precision with business relevance.
  
   
• (Bonus) Familiarity with SQL, Google Analytics, or campaign data pipelines.
  
   

Nice to Have

• Experience in beauty, FMCG, or digital campaign environments.
  
   
• Understanding of community or influencer campaign metrics

What We Offer

• Exposure to enterprise-level campaign data from global brands.
  
   
• A role that builds on an existing analytics foundation — with freedom to innovate.
  
   
• Collaborative, data-driven, and fast-moving environment.
  
   
• Competitive compensation and opportunity for growth.
  
   

Equal Opportunity & Inclusion

We are proud to be an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive, supportive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other legally protected status.

 Core Requirements
Experience: min 2–4 years in software testing (manual or mixed — manual + automation).
Understanding of development processes: SDLC, STLC, types and levels of testing, defect lifecycle, and estimation techniques.
Documentation: ability to create test cases, checklists, and bug reports (Jira, TestRail, Confluence, or equivalents).
Tools: Postman/Insomnia, Swagger, Jira, DevTools, Fiddler, or similar.
API testing: experience with REST / JRPC, understanding of HTTP requests, status codes, and request parameters.
Databases: basic knowledge of SQL (select, join, aggregate functions).
Experience working with hooks and sockets.
UI / Web / Backend testing: experience testing web applications, responsiveness, cross-browser and cross-platform compatibility. Soft Skills
 

• Attention to detail, analytical thinking, and proactivity.
• Ability to describe defects clearly and explain their impact.
• Willingness to learn and work with feedback.
• Strong communication and teamwork skills.
• Problem-solving mindset and readiness to take ownership.
• English — Intermediate+ level (for reading documentation, correspondence, and meetings).

 Would Be a Plus
 

• Experience with CI/CD (GitHub Actions,  GitLab CI).
• Automation (advantage): basic knowledge of JS / TypeScript; experience with Playwright is a plus.
• Understanding of API test automation fundamentals.
• Familiarity with Agile / Scrum / Kanban methodologies.
• Experience working with logging and monitoring tools (Kibana, Grafana, Sentry).
• Testing of microservices and microservice-oriented architectures.