Note: The job is a remote job and is open to candidates in USA. Perficient is seeking a Databricks AI Engineer to design, develop, and deploy scalable AI, machine learning, and generative AI solutions on the Databricks Lakehouse Platform. The role focuses on data engineering, MLOps, RAG applications, AI agents, and enterprise-grade AI solutions.
Responsibilities
- Design and implement AI/ML and Generative AI solutions using Databricks
- Develop scalable data pipelines with Apache Spark, Delta Lake, and Unity Catalog
- Build, train, deploy, and monitor ML models using MLflow and Databricks ML
- Develop RAG-based applications, AI agents, and LLM-powered solutions
- Implement MLOps best practices including CI/CD, model governance, and monitoring
- Collaborate with business, data, and engineering teams to translate requirements into technical solutions
- Optimize performance, scalability, security, and cost efficiency of AI platforms
Skills
- 5+ years of experience in AI/ML, Data Engineering, or Software Engineering
- 3+ years of hands-on experience with Databricks and Apache Spark
- Strong proficiency in Python, PySpark, and SQL
- Experience with MLflow, Delta Lake, Unity Catalog, and Databricks Workflows
- Experience building and deploying Generative AI, LLM, and RAG-based applications
- Knowledge of cloud platforms such as Azure, AWS, or GCP
- Understanding of MLOps, model deployment, and AI governance best practices
- Databricks
- Generative AI
- LLMs
- RAG
- MLflow
- Apache Spark
- PySpark
- Python
- SQL
- Delta Lake
- Unity Catalog
- MLOps
- Azure
- AWS
- GCP
- AI Agents
- LangChain
- LangGraph
- Databricks certifications (Data Engineer, Machine Learning Engineer, or Generative AI Engineer)
- Experience with LangChain, LangGraph, vector databases, and agentic AI frameworks
- Experience delivering enterprise-scale AI and analytics solutions
Company Overview
Company H1B Sponsorship