AI Engineering Manager

2 Weeks ago • 6-10 Years • Research Development

Job Summary

Job Description

We are hiring an engineer with expertise in large language models, data platforms, and product sense to architect the AI stack, from ingestion pipelines to model deployment. You will establish a credit-aware inference platform and integrate language models into customer-facing features and internal tools. Responsibilities include owning the AI roadmap, building data and ML infrastructure (data lake, feature store, vector search, model registry, CI/CD for ML), developing and deploying models, and ensuring quality, cost, and compliance through automated evaluation and monitoring.
Must have:
  • 6-10 years backend/full-stack experience
  • 1+ Gen AI product/workflow in production
  • Strong Java skills
  • Fluent Python or Node for ML tooling
  • Practical LLM, embeddings, vector search experience
  • Familiarity with AWS/GCP, containers, CI/CD
  • Comfortable with data models and MLOps
  • Proven leadership in code reviews/mentoring
Good to have:
  • Fine-tuning or QLoRA workflows
  • Fintech, bookkeeping, or reg-tech background
  • Open-source AI/ML contributions
  • Prior leadership of distributed teams
Perks:
  • Opportunity to work with a dynamic and innovative company
  • Collaborative and supportive team environment
  • Opportunities for growth and development
  • Competitive compensation package with insane opportunity for growth

Job Details

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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