Senior Data & Applied AI Engineer

Reporting to the Head of Engineering, your role is to design, build, and operate the data and applied AI foundations that power intelligent learning experiences and business workflows. You will ship production- grade pipelines, retrieval/search systems, and LLM-enabled features that are measurable, secure, and reliable.

We are committed to building software that is not only functional and reliable, but also beautiful and intuitive. Our engineers and designers work together to create products that are a joy to use, and that solve real-world problems in innovative ways. We believe in the Agile and XP methodologies, and we prioritize collaboration, communication, and continuous improvement in everything we do.

We are embarking on an exciting journey of rebuilding our product and engineering organization to drive innovation and growth. Our goal is to create a world-class platform that delivers the best possible learning experiences to our users.

Share the journey along with engineers, product managers, and leaders from the most successful organizations in the region.

• Design, oversee, build and operate data pipelines and applied AI systems that power our education platform across consumer and business customer segments.
• Build and scale retrieval and search foundations (hybrid search, metadata filtering, vector retrieval) that enable AI experiences.
• Deliver production LLM capabilities with measurable quality, cost controls, and safety guardrails.
• Improve system performance, reliability, observability, and maintainability through proactive monitoring and data quality checks.
• Collaborate closely with stakeholders (product managers, designers, frontend/mobile engineers) to translate business requirements into technical solutions.
• Contribute to sprint planning, technical documentation, and cross-team initiatives as a senior engineering voice.
• Contributing to sprint planning, technical documentation, and cross-team initiatives as a senior voice in the engineering org

• 4+ years of experience in data engineering, backend engineering, or platform engineering, with meaningful production ownership.

• Strong SQL and data modeling skills; experience designing schemas and data contracts.

• Experience building and operating pipelines (batch and/or streaming), including backfills and data quality validation.

• Experience with search/indexing systems and retrieval patterns (e.g., OpenSearch/Elasticsearch, vector DBs, hybrid search).

• Hands-on experience implementing LLM-powered features (RAG, tool/function calling, prompt/version management) — no deep ML required.

• Familiarity with CI/CD, containerization (Docker), and cloud services (ex. AWS, GCP).
  

• Strong problem-solving and debugging skills, with a proactive attitude towards owning and improving systems.
  

• Strong written and verbal communication skills, with the ability to explain complex ideas clearly to technical and non-technical stakeholders.

• Bachelor’s degree in computer science, Engineering, or a related field is preferred but not required