ML/AI/Data Engineer

About the Company

Our client is an early-stage B2B SaaS company building intelligent automation software for finance teams. The platform focuses on real-time financial visibility, automated data ingestion, and advanced cost modeling using modern AI techniques.

The company operates in a large and fast-growing market, with strong early customer validation and active design partners. The team is small, product-driven, and focused on building high-quality software for customers who expect robust, enterprise-grade solutions. This role offers meaningful ownership over core systems and the opportunity to shape foundational technology from the ground up.

About the Role

The company is seeking an AI & Data Engineer to develop the intelligence layer of its platform. In this role, you will design and implement systems that transform messy, heterogeneous business data - such as emails, documents, and spreadsheets - into structured financial models.

You’ll work largely from first principles, deploying services to AWS and operating with a strong MVP mindset: prioritizing simple, effective solutions that can be shipped quickly and iterated on. You’ll collaborate closely with a SaaS engineering team to surface extracted insights through a client-facing dashboard.

Strong engineering fundamentals are expected, including version control, testing, CI/CD, and the ability to break complex problems into small, testable increments while communicating clearly with the team.

Responsibilities:

• Build and maintain ETL pipelines for collecting, cleaning, and structuring customer data;
• Implement document ingestion and vectorization workflows
• Apply NLP and LLM-based approaches to extract structured insights from unstructured data;
• Develop unsupervised models to infer financial structures, cost drivers, and relationships;
• Design custom algorithms to align extracted data with organizational hierarchies and financial models;
• Collaborate with frontend and product engineers to present insights in a clear, intuitive way;
• Maintain strong engineering practices around testing, version control, automation, and documentation;

• Optionally contribute to AWS deployments, infrastructure orchestration, and service integration.

   

Required Skills & Experience

• Hands-on experience with embeddings and vector databases;
• Strong background working with NLP models and large language models (local inference and/or APIs);
• Proven experience building data pipelines and data processing workflows;
• Research-oriented mindset with the ability to design custom solutions beyond off-the-shelf tools;
• Experience deploying and operating systems on AWS;
• Familiarity with automation or data acquisition tools (e.g., workflow automation, scraping, integrations);
• Ability to work independently, iterate quickly, and manage ambiguity;
• Clear communicator who can reason through technical trade-offs;

• Flexibility in working hours when needed.

   

Nice to Have

• Experience applying AI to finance, analytics, or enterprise data problems;
• Broader cloud or infrastructure experience;
• Familiarity with event-driven systems or microservice architectures;

• Background in unsupervised learning on large, messy, real-world datasets.

   

  We Offer: 

• Competitive market salary. 
• Fully remote work. 
• Convenient and somewhat flexible working hours. 
• 28 days of paid time off per calendar year. 
• The chance to work on meaningful, socially valuable products alongside a highly professional, US-based international team. Interesting technical challenges with opportunities to grow and learn.