Senior Applied AI Engineer - Remote US Timezones — Columbus
Traveler-Friendly Insight
This role is listed as fully remote with the team operating in US timezones. The job posting explicitly states "everyone remote in US timezones," which means you'll need to be available during roughly UTC-5 to UTC-8 business hours. This is a meaningful constraint for nomads based in Europe, Southeast Asia, or beyond — expect significant overlap requirements given the daily standup culture.
Timezone flexibility: Limited. Daily standups and weekly planning suggest synchronous commitments. Nomads in Medellín, Colombia (UTC-5) or Mexico City (UTC-6) would be ideally positioned. Eastern Europe (UTC+2/+3) would require very early mornings. Southeast Asia is essentially incompatible with daily syncs.
Visa considerations: Since no specific country restrictions are stated (beyond US timezone preference), nomads could potentially work from anywhere with reliable internet, provided they manage timezone overlap. Colombia's digital nomad visa and Mexico's temporary resident visa are practical options for LATAM-based nomads. Lisbon (UTC+1) may allow partial overlap if you're willing to shift your day early.
- Medellín: ~$1,500-2,500/mo comfortable living — excellent value given senior-level USD pay
- Lisbon: ~$2,500-3,500/mo — feasible but timezone push required
- Bangkok: Timezone (UTC+7) makes daily US syncs very difficult — not recommended
No travel perks (coworking allowance, equipment stipend) are explicitly mentioned. Monthly USD payments are nomad-friendly for international banking purposes.
Headquarters: New Jersey, USA
URL: https://vertican.com
About the Role
For 40 years, Vertican has built software that runs law firms. One year ago, we created a new modern AI platform for document automation (processing/extraction/redacting) which our customers have been adopting faster than any product we've ever had. Our suite of AI-enabled products saves customers thousands of hours each week by processing high volumes of documents with precision and speed. The AI team is growing and we'd like you to join.
We are hiring an engineer to own the document processing pipelines end to end: design, benchmarking, experimenting with new architectures and tools, defining the threshold required for deploying a new pipeline, and more.
We believe it's important to build our own tooling to help us run, improve, and measure our applications. The ideal candidate thinks outside the box — not just on how to build the product/pipeline, but also the tooling needed around it.
You will be the first dedicated ML hire on the product, taking over from the engineering manager who built the current solution, and will work directly with the founding engineering team. This is a senior, hands-on individual-contributor role, but we are a small team and you'll be involved in design, planning, roadmapping, and architectural decisions.
What You Will Do
Design the pipelines. Own the architecture of the extraction-to-posting pipelines: page classification, field extraction, candidate retrieval, claim matching, confidence gating, and the hand-off to human review. Decide where rules end and models begin, what each stage must guarantee to the next, and what the separation of concerns are. We have different pipelines for different document types and expect that at any given point new ones may emerge and others may be consolidated.
Evaluate new systems before we adopt them. Run structured trials of candidate components and recommend what to keep. Examples include probabilistic record linkage (Splink), Azure AI Content Understanding and Document Intelligence, Azure OpenAI and Foundry-hosted models, and LLM agents with tools. Similarly, test new models with the existing pipeline as they are released from the frontier labs.
Build the evaluation process. Own the process of evaluating false positives, false negatives, errors of omission, etc., that we ultimately use to determine if we should upgrade the pipeline.
Ship and operate. Take components from trial to production in our Python workers on the cloud, instrument them, watch cost and quota, and diagnose the cases reviewers send back.
Set direction. Work with leadership on planning for accuracy, cost improvement, and overall product improvements.
What We Are Looking For
Required
- 6+ years building ML or data-intensive systems, with at least 3 of them owning a production pipeline whose output people acted on.
- Solid backend engineering understanding and ideally cloud architecture understanding.
- Hands-on experience with document understanding: OCR or layout models, field extraction from scanned PDFs, or intelligent document processing products.
- Experience with entity resolution or record linkage at scale (Splink, Dedupe, Zingg, or your own blocking-and-scoring system) against databases of hundreds of thousands of rows.
- Designed an evaluation from scratch: built a labeled ground-truth set, chosen the metrics, and defended a threshold to a non-technical stakeholder.
- Production experience with LLM APIs, including structured output, tool calling, and cost or rate-limit management; you can say when an LLM is the wrong tool.
- Strong Python and SQL. Comfortable reading Postgres query plans and writing raw queries when the ORM gets in the way.
- Engineering/scientist mindset: scientific about testing the pipeline and how results are interpreted and presented.
Nice to Have
- Azure AI services (Content Understanding, Document Intelligence, Azure OpenAI, Foundry) or the AWS and GCP equivalents.
- Financial document processing: checks, remittance advices, lockbox files, payment matching, or accounts receivable automation.
- Exposure to collections, legal operations, or other regulated workflows handling PII.
- Probabilistic matching theory (Fellegi-Sunter) or active-learning labeling workflows.
- Experience building human-review tooling or feedback loops that feed back into training and evaluation data.
How We Work and What We Offer
Small team, direct access to large datasets, weekly planning, daily standup — everyone remote in US timezones.
- A small team of tight-knit, like-minded people passionate about high-quality software
- Competitive compensation, commensurate with a senior individual-contributor role
- Monthly payments in USD
Vertican is an equal opportunity employer. We hire on merit and do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status.
To apply: https://weworkremotely.com/remote-jobs/vertican-senior-applied-ai-engineer-document-intelligence
Frequently Asked Questions
Is this role truly remote or is there an office requirement?
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Will I be managing a team or is this purely an individual contributor role?
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What ML stack and cloud platforms does Vertican use?
