AI Engineer

Please note that we will never request payment or bank account information at any stage of the recruitment process. As we continue to grow our teams, we urge you to be cautious of fraudulent job postings or recruitment activities that misuse our company name and information. Please protect your personal information during any recruitment process. While Monks may contact potential candidates via LinkedIn, all applications must be submitted through our official website (monks.com/careers).

.Monks Technology Services, part of Media.Monks and S4 Capital, is a global consulting firm mastering AI-powered transformations for the Fortune 100. We combine long-term strategic thinking, deep enterprise experience, and a human-centered approach to help clients transform business processes and dominate their industries.
About the Role
As an AI / Parsing Engineer, you’ll own the foundational pipelines that transform messy documents, scanned records, and call transcripts into structured, reliable data for agentic AI systems. Working within a .Monks delivery team alongside clients, product partners, and domain experts, you’ll build extraction, classification, validation, and evaluation systems that downstream products can trust.
We’re all-in on agentic engineering. Tools such as Claude Code and Codex are part of our everyday workflow, and we’re looking for engineers who are fluent in working alongside AI coding agents and excited to advance these practices.
Responsibilities

• Build extraction pipelines that transform documents, transcripts, and records into structured, schema-validated data
• Combine LLMs with traditional parsing techniques, including OCR and layout analysis, to deliver reliable and cost-aware extraction
• Design validation rules, confidence-scoring systems, and workflows that route low-confidence cases to human review
• Build evaluation datasets and testing frameworks that measure extraction accuracy and identify regressions before release
• Process diverse and degraded inputs, ranging from clean PDFs to poor-quality scans and inconsistent formats
• Collaborate with clients, product teams, orchestration engineers, and domain experts to ensure clean data flows through the broader system
• Communicate pipeline capabilities, limitations, quality thresholds, and risks clearly to technical and nontechnical stakeholders
• Use AI coding agents, including Claude Code and Codex, as part of day-to-day engineering workflows
• Other duties as assigned

About YouYou’re comfortable working with inconsistent formats, poor scans, and partially structured inputs. You approach extraction with precision, thinking carefully about edge cases, confidence thresholds, and validation. You understand the nondeterministic nature of LLM systems and know how to measure and improve their reliability.