Sr AI Engineer

Job Title: AI Engineer (Mid-Level)

Location: Warren, NJ - 4 days onsite

Education

• Bachelor's degree in Computer Science, Data Science, Machine Learning, Software Engineering, or a related quantitative field. Master's degree is a plus.

Experience

• 3 5 years of professional experience in AI/ML engineering, with demonstrated delivery of production-grade AI systems.
• Hands-on experience building and deploying LLM-powered applications using frameworks such as LangChain, LlamaIndex, or Semantic Kernel.
• Proven experience implementing MLOps pipelines in cloud environments (Azure preferred).
• Experience developing AI agents or automation workflows using agentic frameworks.
• Prior experience in financial services, insurance, or regulated industries is strongly preferred.

Generative AI & LLMs

• OpenAI / Azure OpenAI (GPT-4o, GPT-4 Turbo), Claude, Mistral, or open-source LLMs (Llama 3, Falcon)
• RAG architectures, vector search, embeddings (OpenAI, Cohere, SentenceTransformers)
• LangChain, LlamaIndex, Semantic Kernel
• Prompt engineering, few-shot learning, instruction tuning, RLHF concepts

AI Agents & Automation

• Agentic frameworks: ReAct, Tool-Augmented Agents, LangGraph, AutoGen, CrewAI
• Workflow orchestration: Apache Airflow, Databricks Workflows, Azure Logic Apps
• API design and integration: REST, GraphQL, Webhooks

MLOps & Model Serving

• MLflow (experiment tracking, model registry, model serving)
• Azure Machine Learning, Databricks AutoML & Feature Store
• Docker, Kubernetes (AKS), Azure Container Apps
• CI/CD: Azure DevOps, GitHub Actions
• Model monitoring: Evidently AI, Azure ML monitoring, or equivalent

Programming & Data Engineering

• Python (expert level): PyTorch, Hugging Face Transformers, scikit-learn, Pandas, NumPy
• PySpark and Delta Lake for large-scale data processing
• SQL (T-SQL / Spark SQL) for feature engineering and data validation
• Git for version control and collaborative development

Cloud & Platform

• Microsoft Azure (Azure OpenAI, Azure AI Search, AKS, Azure Data Factory, Azure Key Vault)
• Databricks (Unity Catalog, Delta Live Tables, Workflows)
• Microsoft Fabric / OneLake (familiarity a strong plus)

Preferred Qualifications

• Experience with P&C insurance workflows such as FNOL processing, claims triage, underwriting decisioning, or actuarial modeling.
• Familiarity with insurance regulatory requirements including NAIC guidelines and data privacy standards (CCPA, GDPR).
• Experience implementing responsible AI principles fairness, explainability, and bias mitigation in regulated environments.
• Microsoft certifications: Azure AI Engineer Associate (AI-102) or Azure Data Scientist Associate (DP-100) preferred.
• Exposure to Data Mesh patterns and publishing AI model outputs as domain data products.
• Familiarity with Databricks Model Serving and Mosaic AI capabilities.