What are the responsibilities and job description for the Sr AI Engineer position at Venusgeo?
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.
Salary : $65 - $70