Senior Full Stack Engineer; GenAI) Labs

You will support the AI Lead and Senior Data Analyst by building and shipping the core product and platform capabilities for the Cherith GRTI Search Platform. That includes the core search experience and APIs (retrieval pipelines, reranking, guardrails, and UI), plus the surrounding workflows that make it production-ready for multiple partners (onboarding, content management, access controls, analytics, and integrations).

Our AI mission is to place faithful AI in the hands of trusted pastors and ministries, so that their impact will be broader and deeper. To continue achieving this, we are developing and researching unique projects where trust, accuracy, and governance are first-class requirements:

• A platform to support the GRTI network of ministries and organizations. This platform is a central, searchable library of biblical resources, alongside integrations that bring search into GRTI partner applications and address their core pain points. We will also provide analytics so partners can understand usage, content coverage, and quality over time.
• A mature profiling algorithm and recommendation system to understand user behaviour and ensure the technical system is aiding spiritual growth rather than detracting from it, with a centred-set approach to profiling and careful safeguards.
• Fine-tuning a Christian LLM to further enhance our AI efforts and improve accuracy within our existing and future systems, with strong data stewardship and clear evaluation standards.

You are a product-minded engineer who enjoys owning features end-to-end, from data contracts to front-end polish, while collaborating closely with the AI Lead on quality and safety, and with the Senior Data Analyst on metrics, dashboards, and partner reporting. You will also support implementation work for centred-set profiling and recommendations, and contribute engineering support for the Christian LLM lifecycle (data workflows, evaluation hooks, deployment practices), without needing to be the primary model researcher.

• Ship partner-friendly platform features (search modalities, onboarding, content upload, dashboards, usage metrics, and admin tools) behind flags with safe rollout and rollback.
• Support a multi-tenant production-ready MVP with solid partner isolation, privacy-aware access controls, and clear auditability.
• Improve answer precision and faithfulness with hybrid retrieval and reranker iterations measured by automated evaluations and monthly evaluation cycles.
• Reduce p95 latency and cost per query via caching, efficient context construction, and cost and usage guardrails.
• Maintain healthy DORA metrics with small, frequent, reversible deployments, backed by strong observability and incident-ready runbooks.

• Build and operate RAG services in Python (APIs, retrieval, reranking, prompt orchestration) with guardrails and safe rendering to mitigate prompt injection, insecure output handling, and data leakage.
• Deliver multi-tenant platform foundations (tenant configuration, partner isolation, privacy-aware access controls), plus partner integration options (APIs, SDK patterns, embed-friendly components) with rate limits and clear documentation.
• Own ingestion and content management workflows end-to-end (partner onboarding, upload, parsing, chunking, indexing, re-indexing, corpus health, and failure handling).
• Partner with the AI Lead to implement evaluation hooks, regression tests, release gates, and quality, safety, latency monitoring across CI and deployments.
• Partner with the Senior Data Analyst to instrument analytics and deliver partner-facing dashboards for usage, quality trends, content coverage, and onboarding health.
• Build…