AI Engineer

Quick Facts

• Role: AI Engineer

• Focus: Building an AI-powered invoice audit platform with LLM/document intelligence and deterministic, explainable audit rules

Description

Build and deploy AI-powered capabilities for an invoice audit platform, combining LLM/document intelligence with deterministic, explainable, and compliant audit logic. Own end-to-end development of scalable, production-grade backend workflows for large-volume document classification, extraction, and assessment. Work with cloud infrastructure, vector search, and observability to ensure reliability and performance.

Responsibilities

• Design, develop, and deploy AI features using LLMs, document intelligence services, and machine learning pipelines

• Build and optimize asynchronous processing workflows for large-scale document classification and extraction

• Implement and maintain rules engines to ensure accurate, explainable, and compliant audit findings

• Develop backend services in Python with FastAPI and async frameworks for high-volume invoice processing

• Use vector databases and embedding models to enable semantic search and intelligent document retrieval

• Integrate cloud AI services for OCR, document understanding, and NLP

• Design data models for complex financial and contractual data using PostgreSQL and document databases

• Build observability and monitoring to ensure system reliability and performance

• Translate business requirements with financial SMEs and domain experts

• Participate in agile ceremonies, code reviews, and continuous improvement initiatives

Requirements

• 3–7 years of professional software engineering experience

• 2+ years hands-on AI/ML experience with LLMs and document processing

• Production-grade application development with Python and modern frameworks

• Strong data modeling and database design experience with relational and NoSQL systems

• Cloud experience on AWS and/or Azure

• Experience integrating LLMs using OpenAI APIs and/or LangChain (or similar)

• Experience with document intelligence, OCR, and information extraction

• Knowledge of embeddings, vector databases (e.g., pgvector), and semantic search

• Prompt engineering experience

• Expert Python 3.10+ development

• FastAPI experience with async/await and Uvicorn

• SQLAlchemy 2.0 (async), Alembic migrations, and database optimization experience

• Pydantic for validation and Pandas for data manipulation

• AWS services experience: EC2, RDS, S3, SQS, Batch

• Azure familiarity: Blob Storage, Cosmos DB, and AI services

• Infrastructure as Code experience (e.g., CloudFormation)

• Docker/containerization experience

• CI/CD experience (e.g., GitHub Actions)

• Testing experience with async patterns (e.g., Pytest)

• Observability/monitoring/logging best practices knowledge

Benefits

• Opportunity to build scalable, production-grade AI systems for enterprise financial operations

• Work with modern cloud infrastructure, advanced AI tooling, and a deterministic-first, AI-augmented architecture

• Collaborative, agile environment with code reviews and continuous improvement