Top Tech Jobs & Startup Jobs in Charlotte, NC

Lead delivery of AI and analytics solutions for a financial services client: manage end-to-end projects, run discovery workshops, translate requirements into product roadmaps, assess Agentic AI vs rules-based approaches, align Databricks Lakehouse and Unity Catalog architectures, and coordinate stakeholders and hybrid delivery teams.

Design, train, and deploy ML solutions with emphasis on generative AI and NLP (LLMs, RAG). Work with cross-functional teams to analyze text/transcription data, build scalable models, evaluate new algorithms, document results, and present findings to stakeholders to drive business value.

Lead modernization and design of applications, architecting cloud-native systems, optimizing APIs, and ensuring security and scalability for enterprise applications.

Lead modernization of enterprise reporting and migrate legacy BI to cloud platforms. Architect and embed agentic AI workflows to automate reporting and insights. Build and optimize data pipelines on AWS, develop Power BI dashboards, ensure data governance and security, and mentor cross-functional teams on modern BI and AI adoption.

The Databricks Architect will design and implement large-scale data solutions, optimizing performance and reliability, while leading initiatives in data engineering.

The Machine Learning Engineer will develop software solutions, optimize data pipelines, and deploy machine learning models using cloud platforms and best practices.

The Technology Partner will lead technology solutions and data transformation initiatives for Fortune 100 clients, providing thought leadership and managing executive relationships.

This role leads Revenue Growth Management initiatives, linking data analytics with executive strategy to drive business growth through actionable insights and project management.

Lead design and delivery of Snowflake-centric cloud data platforms. Engage with clients to gather requirements, architect scalable secure solutions, provide technical leadership, develop roadmaps, advise executives, and guide implementation best practices across the analytics stack.

Build high-performance API services and production-grade Generative AI systems. Design and implement end-to-end RAG pipelines, vector stores, embeddings, and latency-optimized generators. Develop agentic AI using LangChain/CrewAI/Semantic Kernel, integrate LLM APIs and AWS Bedrock, manage CI/CD and ML pipelines, and apply evaluation frameworks to detect hallucinations and optimize performance.