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# Lead Machine Learning & GenAI Engineer

- **Company:** Resourcesoft, Inc.
- **Location:** Raleigh, NC, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Databases, Continuous Integration, Extract Transform Load (ETL), Elasticsearch, Apache Hadoop, Machine Learning, NoSQL, Software Engineering, Apache Solr, SQL Databases, Enterprise Data Management, Large Language Models, Apache Spark, Electronic Medical Records, Generative AI, Backend, Containerization, Kubernetes, Graphql, Virtual Agents, Restful APIs, Terraform, Docker, Microservices
- **Published:** September 8, 2026
- **Apply:** https://www.dice.com/job-detail/6c5751c1-2e09-42d9-887a-326d85316da5

## About the Role

* 10 or more years of experience in software engineering, machine learning, and enterprise data pipelines.
 * Proficiency in Python development, LangChain framework, and autonomous AI agent architectures.
 * Experience with Retrieval-Augmented Generation (RAG) system design and Large Language Model (LLM) APIs.
 * Experience in vector databases and search indexing engines including Solr, Elasticsearch, and OpenSearch.
 * Experience with big data ETL processing using Apache Spark, Hadoop, EMR, SQL, and NoSQL databases.
 * Experience in containerized deployments using Docker, Kubernetes, Terraform, and CI/CD pipelines.
 * Excellent verbal and written communication skills.

## Description

* Architect and deploy production-grade applications powered by Large Language Models and AI agents.
 * Build end-to-end Retrieval-Augmented Generation (RAG) pipelines integrating semantic search and vector stores.
 * Design high-throughput ETL data workflows and preprocessing pipelines to manage terabytes of text data.
 * Integrate custom machine learning models with existing backend systems via RESTful and GraphQL APIs.
 * Deploy, orchestrate, and maintain containerized AI microservices using Docker and Kubernetes clusters.
 * Optimize vector search indexing and query retrieval performance across Solr and OpenSearch databases.
 * Collaborate with data science and engineering teams to translate business requirements into AI capabilities.