Top Tech Jobs & Startup Jobs in Charlotte, NC

Leads security architecture across cloud, on-premises, data, APIs, and AI/ML environments. Designs security patterns, standards, and zero-trust architectures; strengthens identity, encryption, threat detection, vulnerability management, SIEM, and incident response capabilities. Partners with development, operations, business, and enterprise architecture teams to align security with business objectives. Secures machine learning models and pipelines against adversarial attacks while supporting regulatory compliance and risk management.

Supports succession planning and legacy planning services for financial advisors. Manages project intake, workflows, milestones, escalations, advisor engagements, process improvements, and technology automation. Provides guidance on continuity and corporate planning options, conducts ad hoc financial analysis and data entry, collaborates with business partners, and presents ideas for improving service offerings.

Lead full‑stack design, development, and maintenance of scalable financial applications across front-end, back-end, and databases. Build RESTful APIs and microservices, participate in code reviews, troubleshoot production issues, mentor junior developers, and adopt AI/LLM tools and cloud/container platforms to improve delivery and security.

Own the vision, strategy, roadmap, backlog, and measurement framework for an enterprise AI Product Development Lifecycle platform. Translate software delivery processes into workflows, requirements, governance gates, and measurable outcomes. Partner with engineering, architecture, design, AI governance, risk, and delivery teams to lead pilots, analyze results, improve adoption, and scale responsible AI-enabled software development practices.

Leads product ownership for enterprise data consumption capabilities, defining strategy, roadmaps, priorities, success measures, and requirements. Partners with business, engineering, architecture, governance, and platform teams to deliver scalable data products. Analyzes data usage, lineage, dependencies, and impacts; supports APIs, feeds, reporting, and shared services; manages backlogs, Agile delivery, stakeholder communications, and data consumption standards.

Manages and trades centrally managed investment platforms, ensuring accounts align with selected strategies. Reviews model portfolios and large trades, researches complex issues, maintains reports, analyzes data, supports process improvements and projects, and serves as a key contact for internal and external partners.

Supports securities-backed lending and margin products for financial advisors. Serves as a product expert, resolves advisor and client inquiries, explains product systems and policies, escalates exceptions, supports loan transitions to LPL, and provides product improvement feedback. The role requires financial services experience, knowledge of securities-backed lending and margin, strong communication, problem-solving, organization, and client-service skills.

Design, develop, test, and support scalable full-stack applications and cloud-native microservices using .NET, Angular, AWS, SQL, and NoSQL technologies. Build APIs, data integrations, ETL pipelines, and CI/CD solutions while improving system performance, reliability, and scalability. Collaborate with product, architecture, and engineering teams, participate in design and code reviews, troubleshoot applications, document technical solutions, and apply modern DevOps and AI-assisted development practices.

Leads the modernization of enterprise data platforms supporting reporting, statements, and letters. Architects cloud-native data platforms, ETL/ELT pipelines, streaming solutions, and real-time processing using AWS, Snowflake, Python, dbt, Airflow, and Kafka. Establishes engineering standards, technical roadmaps, observability, data quality, CI/CD, and DevOps practices. Provides hands-on technical leadership, mentors engineers, manages delivery across internal and vendor teams, resolves production issues, and drives cloud transformation and platform reliability.

Leads enterprise AI governance strategy and second-line oversight across the AI lifecycle. Establishes governance frameworks, risk standards, decision rights, approval processes, monitoring expectations, and escalation protocols. Independently reviews AI and machine learning solutions, challenges technical and business stakeholders, advises executives, oversees regulatory and audit reviews, drives remediation, and builds a high-performing AI governance team.