Top Tech Jobs & Startup Jobs in Charlotte, NC

Lead and manage data engineering teams to build and maintain high-quality data pipelines, implement automation and performance scripts, integrate LLMs/Agentic AI, collaborate with product and engineering, oversee data modeling, ensure data quality, and support SEC-related data solutions.

Lead global AI-first transformation for legislative content: define strategy, prioritize AI-enabled content generation and workflows, deploy editorial AI tools, set standards, measure quality and outcomes, and build cross-functional capability and adoption.

Lead end-to-end software implementation projects for financial crimes compliance solutions. Translate SOWs into implementation roadmaps, coordinate cross-functional teams, manage risks, oversee UAT and post-go-live hypercare, and ensure delivery on time, within budget, and aligned to customer requirements.

Partner with SVP Editorial Operations and senior leaders to lead financial planning, budgeting, forecasting, and long-range planning across a $100M+ global cost base. Provide decision support through reporting, scenario modelling, business cases, and analytics; drive productivity, AI-enabled optimization, and cost-efficiency initiatives; link financial and operational metrics to business outcomes and act as a trusted finance advisor and change agent.

Lead customer-facing technical integrations for SaaS fraud and identity solutions. Design, test, deploy, and optimize mobile SDKs, web fingerprinting, and REST API integrations. Advise developers and business stakeholders, present findings, troubleshoot implementations, and support adoption. Occasional travel required.

Design, build, and optimize generative AI, RAG, and agentic RAG systems for drafting, search, and reasoning. Improve LLM outputs via prompt design, retrieval optimization, embeddings, reranking, and evaluation. Develop production-grade ML components and retrieval pipelines using OpenSearch/Solr, write maintainable Python code, and collaborate with engineering, product, and domain teams to improve relevance, accuracy, and user trust.

Support teams in preparing and maintaining AI-ready data by assessing data readiness, improving data quality and metadata, documenting lineage and ownership, and advising on governance and retrieval suitability for AI systems. Collaborate with data engineering, AI, and governance teams to create checklists, guidance, and remediation recommendations without owning pipelines or technical implementations.