Top AI & Machine Learning Jobs in Charlotte, NC

Own product strategy and roadmap for CX and AI tooling that enables support specialists. Prioritize high-impact CX problems, build AI-integrated features (intelligent routing, AI-assisted responses, knowledge retrieval, workflow automation), define success metrics, partner with CX, Design, Data Science, and Compliance, and drive end-to-end delivery and measurement to improve resolution time, CSAT, and efficiency.

Lead end-to-end pricing experimentation and strategy for consumer and business products. Design and analyze A/B tests, build pricing models and production-grade data pipelines, partner cross-functionally, and present actionable recommendations to senior leadership.

Lead end-to-end ML systems for identity verification, including document authenticity, face match, liveness and deepfake detection. Build GNN-based identity graphs, behavioral/device-intelligence models, vendor benchmarking/evaluation, and production enforcement. Mentor engineers and align ML architecture with Product, Compliance, Risk, and Security stakeholders.

Design and deliver LLM-powered, agentic AI systems to automate customer support and compliance. Build scalable, secure backend infrastructure in Python and Go, integrate third-party models/APIs, implement grounding and guardrails, and measure performance. Lead end-to-end projects, mentor engineers, conduct code reviews, and participate in on-call and incident response to improve resolution times and reduce operational costs.

Lead engineering of an AI-native finance automation platform: design LLM-based agents and multi-agent orchestration, integrate with NetSuite/Workday/Anaplan, ensure SOX-compliant traceability and human-in-the-loop controls, and partner with FP&A/Treasury to translate spreadsheet workflows into production systems.

Build and operate Coinbase's LLM and agent platform: design the LLM gateway, agent runtime, knowledge bases, AI spend governance, observability/eval tooling, and ship production agents while partnering cross-functionally to ensure secure, cost-effective, and responsible generative AI at scale.

Design and build a production-grade Legal AI platform of agentic workflows to automate high-volume legal tasks (agreement redlining, SEC filing support, governance), consolidate bots into a governed agent platform, own the institutional client agreement automation system, advise legal leadership, define make-vs-buy strategy, and serve as a pilot for deploying engineering in non-technical teams.

Lead cross-functional programs to transform customer support with AI-powered automation, agent tooling, analytics, and vendor evaluations. Define roadmap, size opportunities, set success metrics/OKRs, manage dependencies, and drive rollout/change management while partnering with Product, Engineering, Analytics, and Operations to deliver measurable CX improvements.

Own and evolve revenue calibration models tying CX interactions to revenue, design causal inference and experimentation frameworks, build LLM-powered classification/NLP pipelines, productionize models with Analytics Engineers, define segmentation and behavioral signals, and ensure statistical rigor for executive reporting and regulatory defensibility.

Senior SRE on the IT Operations team owning reliability, monitoring, and incident response for AI infrastructure. Build automation, CI/CD and Kubernetes tooling, improve observability and documentation, and develop internal full-stack tools using Go or Python. Partner with Infrastructure, Security, and Compliance to scale secure, resilient AI deployment pipelines.