Overview
We are seeking a highly skilled AI/ML Engineer with deep expertise in Python, Azure Machine Learning, Generative AI, and financial data analysis. This role will focus on building intelligent systems that analyze, interpret, and explain financial documents using RAG architectures, LLMs, and Agentic AI frameworks.
The ideal candidate combines strong technical capability with solid accounting/finance domain understanding and can thrive in fast-paced, highly collaborative environments.
Responsibilities
- Design, build, and optimize RAG-based pipelines, LLM-driven workflows, and agentic AI systems for financial document analysis.
- Train, fine-tune, and evaluate large language models for use cases involving P&L analysis, expense classification, compensation modeling, and general ledger automation.
- Utilize Azure Document Intelligence, Azure ML, Data Factory, Azure Blob Storage, and Cloud Foundry to deploy scalable document understanding solutions.
- Implement robust ML pipelines including data ingestion, preprocessing, feature engineering, model training, inference, monitoring, and retraining cycles.
- Develop financial variance analysis models using AI to automatically detect, explain, and summarize discrepancies.
- Collaborate with accounting and finance teams to translate domain requirements into technical ML solutions (despite limited access/availability).
- Lead and participate in technical meetings; present findings, design choices, and architecture decisions clearly and confidently.
- Troubleshoot production issues rapidly and ensure high availability of AI services in a fast-paced environment.
Required Skills
Core AI/ML & GenAI
- Expert-level Python (data manipulation, modeling, automation, prompt engineering).
- Strong hands-on experience with Generative AI, LLM architectures, and RAG (Retrieval-Augmented Generation).
- Experience with Agentic AI frameworks (LangChain, LlamaIndex, AutoGen, or similar).
- Solid foundational ML understanding: supervised/unsupervised learning, embeddings, vector stores, model evaluation, and optimization.
- Experience training or fine-tuning models for domain-specific use cases.
Finance / Accounting Domain Knowledge
- Working understanding of:
Profit & Loss statements (P&L)
Accrual accounting
Product line budgeting
Compensation and expense classification
General Ledger (GL)
Variance analysis
- Ability to build AI workflows that interpret and explain financial structures and anomalies.
Azure & Data Infrastructure
- Experience with:
Azure Machine Learning
Azure Document Intelligence
Azure Data Factory
Azure Blob Storage
Cloud Foundry deployed on Azure
- Understanding of PDF parsing, document processing, and Cognitive Services.
Communication & Teamwork
- Excellent communication skills; able to present technical concepts to non-technical stakeholders.
- Comfortable running video meetings, leading discussions, and collaborating with busy finance teams.
- Highly hands-on, proactive, and able to work quickly without close supervision.
Preferred / Nice to Have
- Accounting or finance background, especially oil & gas accounting experience.
- Experience with:
Vector databases (Pinecone, Weaviate, FAISS, Chroma)
MLflow for model tracking
Kubernetes and container orchestration
Airflow or similar workflow tools
CI/CD pipelines for ML (MLOps)
Databricks and Spark-based large-scale processing
OpenAI, Azure OpenAI, Gemini, Claude, or custom model integrations
- Bachelor's degree in Computer Science, AI/ML, Data Science, or equivalent experience.
