About doola
doola is a dynamic company committed to simplifying the complexities of business formation, payment setup, compliance, taxes, and more. We empower entrepreneurs and businesses of all sizes to navigate the intricate landscape of financial and regulatory requirements with ease, allowing them to focus on what truly matters - building and growing their ventures.
About the Role
We’re hiring an engineer who blends large-language-model know-how, data-platform chops, and product sense. You will architect the AI stack from ingestion pipelines through model deployment, stand up a credit-aware inference platform, and integrate language models into both customer-facing features and internal tools.
Key responsibilities
Own the AI roadmap – translate business priorities into model, data, and infrastructure milestones.Build data & ML infrastructure – design data lake, feature store, vector search (pgvector), model registry, and CI/CD for ML.Develop and deploy models – train or fine-tune models on doola’s domain data; serve them behind low-latency, cost-controlled APIs.Ensure quality, cost, and compliance – set up automated evaluation, token-spend monitoring, and GDPR-safe data flows.
Skills and qualifications
6–10 years in back-end or full-stack engineering with at least one Gen-AI product or workflow in production.Strong in Java and fluent in Python or Node for ML tooling.Practical experience with LLMs, embeddings, vector search, and retrieval-augmented generation.Deep familiarity with AWS or GCP services, container orchestration, CI/CD, and monitoring.Comfortable setting up data models and MLOps processes (model registry, drift alerts, blue-green model deploys).Proven leadership in code reviews, technical mentoring, and cross-functional communication.
Bonus qualifications
Fine-tuning or QLoRA workflows on open-source models.Background in fintech, bookkeeping, or reg-tech domains.Open-source contributions in AI/ML.Prior leadership of distributed engineering teams.
