Offer summary

Qualifications:

6–10 years of experience in back-end or full-stack engineering., Proficiency in Java, Python, or Node.js, with experience in ML tooling., Hands-on experience with large language models, embeddings, and vector search., Deep familiarity with cloud services like AWS or GCP, and MLOps processes..

Key responsibilities:

Own the AI roadmap by translating business priorities into technical milestones.

Design and build data and ML infrastructure, including data lakes and model registries.

Develop, train, and deploy AI models on domain-specific data.

Ensure quality, cost-efficiency, and compliance through automated evaluation and monitoring.

Job description

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.

Why join us

• Opportunity to work with a dynamic and innovative company at the forefront of the industry.

• Collaborative and supportive team environment with opportunities for growth and development.

• Competitive compensation package with insane opportunity for growth.

Our values and non-values

• Establishing team values is critical. We believe it’s equally essential to identify team non-values. We’re stronger in driving our mission home with both values and non-values taken into account. Note: Our goal in sharing these up front and transparently is to be as straightforward with people as possible. Our goal is not to be combative in our language; it’s to be straightforward.

• Action Item: If you read these values and non-values and get more fired up about working at doola, lets talk: https://www.doola.com/careers/

If you are passionate about helping businesses succeed and thrive, and you possess the skills and experience outlined above, we want to hear from you. Join us at doola and be part of a team dedicated to simplifying the path to business success.

doola is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

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