# AI Engineer

> Weekday AI · Chicago, United States · Full-time · Posted 2026-09-26

**Salary:** INR 10,000,000–20,000,000

**Workplace:** on_site

**Department:** Weekday's Client via platform

## Description

𝗧𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗳𝗼𝗿 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝗲𝗸𝗱𝗮𝘆'𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀

𝗦𝗮𝗹𝗮𝗿𝘆 𝗿𝗮𝗻𝗴𝗲: 𝗥𝘀 𝟭𝟬𝟬𝟬𝟬𝟬𝟬𝟬 - 𝗥𝘀 𝟮𝟬𝟬𝟬𝟬𝟬𝟬𝟬 (𝗶𝗲 𝗜𝗡𝗥 𝟭𝟬𝟬-𝟮𝟬𝟬 𝗟𝗣𝗔)

Experience: 3+ yrs

Location: Chicago, Illinois, United States

Job Type: Full-time

We are looking for an experienced **AI Engineer** to design and build the intelligence layer across a document-to-return workflow. The role focuses on developing production-grade AI systems that transform complex financial and tax documents into reliable, structured data and support tax professionals in identifying missing information, inconsistencies, and potential errors.

This is a hands-on engineering role focused on **document intelligence, LLMs, extraction, agentic systems, evaluation, and human-in-the-loop workflows**. The ideal candidate combines strong technical skills with a high bar for accuracy, traceability, observability, and production reliability.

## Requirements

Key Responsibilities

-   Build production systems for **document classification, OCR, parsing, and structured data extraction**.
-   Process PDFs, scanned documents, tax forms, financial statements, receipts, and other unstructured financial information.
-   Design extraction workflows that preserve source context, handle ambiguity, and route low-confidence results for human review.
-   Develop **LLM-powered document understanding** and intelligent extraction capabilities.
-   Build AI agents that analyze completed returns against source documents and relevant tax context.
-   Identify missing information, inconsistencies, potential errors, and other issues and present findings clearly for professional review.
-   Design human-in-the-loop workflows that provide appropriate confidence signals, source citations, review controls, and correction mechanisms.
-   Build scalable **evaluation frameworks** for structured and unstructured document-processing systems.
-   Define evaluation datasets, ground-truth labels, scoring methodologies, benchmarks, and statistical analysis approaches.
-   Establish observability and feedback systems to measure extraction quality, model performance, and user outcomes.
-   Monitor production AI workflows and continuously improve accuracy, reliability, and coverage.
-   Identify high-effort manual steps within document and return-preparation workflows where AI can provide measurable value.
-   Collaborate with engineering and domain experts to translate real-world workflow requirements into reliable AI systems.
-   Establish reproducible testing and evaluation processes for models, agents, and extraction pipelines.
-   Contribute to expanding AI capabilities across document processing, return review, and professional workflows.

What Makes You a Great Fit

-   **3+ years of experience** building production AI, machine learning, or intelligent automation systems.
-   Strong hands-on experience with **document OCR, document understanding, parsing, and structured data extraction**.
-   Experience working with PDFs, forms, scanned documents, financial documents, or other complex unstructured data.
-   Strong understanding of **LLM-based document processing** and modern AI techniques for extraction and reasoning.
-   Experience designing and implementing **evaluation frameworks** for AI or machine-learning systems.
-   Strong knowledge of evaluation datasets, ground-truth labeling, scoring methodologies, benchmarking, and statistical analysis.
-   Experience building or working with **agentic AI systems** and human-in-the-loop workflows.
-   Strong understanding of observability, reproducibility, model monitoring, and production AI reliability.
-   Proficiency in **Python** and experience building scalable production systems.
-   Strong analytical and problem-solving skills with exceptional attention to accuracy and detail.
-   Ability to design AI workflows where outputs are **traceable, auditable, explainable, and actionable**.
-   Strong product and engineering judgment with a practical, outcome-oriented approach to AI development.
-   Comfortable working closely with domain experts and incorporating real-world feedback into AI systems.
-   Strong bias toward shipping, experimentation, measurement, and continuous improvement.
-   Comfortable operating in a **small, high-ownership environment** where engineering and product responsibilities are closely connected.

## Apply

[Apply at Weekday AI](https://apply.workable.com/weekday-1/j/C1E47DC9A5/apply)

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