Partner with business stakeholders to identify high-value AI use cases and deliver agentic AI and LLM solutions. Architect multi-agent and tool-augmented LLM systems, ensure scalability, security, explainability, and governance. Collaborate with engineering to deploy production-grade solutions, implement evaluation/monitoring and guardrails, and act as an enterprise AI advisor while mentoring peers and contributing AI best practices.
Responsibilities:
Solve Business Problems with AI
- Partner with business stakeholders to identify, frame, and prioritize high‑value problems that can be addressed using Agentic AI, LLMs, and NLP.
- Translate business needs into clear AI use cases, success metrics, and delivery plans.
- Focus on business outcomes, not just model performance.
Design & Build Agentic AI Solutions
- Architect and develop agentic AI systems that can reason, plan, and take actions across tools, workflows, and data sources.
- Design multi‑agent and tool‑augmented LLM solutions to automate complex, multi‑step processes.
- Ensure solutions are reliable, explainable, and governed for enterprise use.
Scalable & Responsible AI
- Collaborate with engineering teams to deploy AI solutions with scalability, security, and performance in mind.
- Implement evaluation, monitoring, and guardrails for LLM and agentic systems, including bias, drift, and failure modes.
- Align solutions with enterprise risk management, compliance, and responsible AI standards.
Thought Leadership & Collaboration
- Act as a trusted AI advisor, helping teams understand where Agentic AI and LLMs add value—and where they do not.
- Contribute to AI best practices, reusable patterns, and strategic direction.
- Mentor peers and teammates on applied AI and business‑driven problem solving.
Qualifications:
- Agentic AI: Experience designing AI agents that reason, plan, and act across systems.
- Large Language Models (LLMs): Hands‑on experience building enterprise LLM applications (e.g., RAG, tool use, orchestration, evaluation).
- Natural Language Processing (NLP): Strong experience working with unstructured text and language‑driven workflows.
- MS or PhD in Computer Science, Machine Learning, Data Science, or a related quantitative field.
- 3+ years delivering AI/ML solutions in production environments.
- 5+ years of hands‑on Python experience; experience with distributed data processing is a plus.
- Strong ability to solve business problems using AI, not just build models.
- Excellent communication skills, with the ability to explain complex concepts to both technical and non‑technical audiences.
- Experience working in cross‑functional, enterprise environments.
Special Factors
Sponsorship
Vanguard is offering visa sponsorship for this position.About Vanguard
At Vanguard, we don't just have a mission—we're on a mission.
To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.
How We Work
Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.
Vanguard Charlotte, North Carolina, USA Office
Two North Falls Plaza, Charlotte, NC, United States, 28217
Similar Jobs
Energy • Renewable Energy
Leads end-to-end data science and machine learning initiatives, from problem discovery and proof of concept through production deployment and continuous improvement. Develops statistical, optimization, simulation, and machine learning solutions using strong software engineering, MLOps, and Responsible AI practices. Partners with stakeholders and multidisciplinary teams, provides technical direction, evaluates feasibility and risks, communicates analytical recommendations, and remains hands-on in solution development.
Top Skills:
SparkDatabricksMachine Learning LibrariesMlflowMlopsPysparkPythonResponsible AiSQL
Fintech
Build AI-powered digital twins that simulate customer behavior and decision-making. Lead data science and AI initiatives involving LLMs, RAG, agentic systems, experimentation, validation, and performance measurement. Apply behavioral science, UX research, and marketing analytics to develop human-centered models. Partner cross-functionally to translate business problems into scalable solutions, communicate recommendations, and mentor junior team members.
Top Skills:
Agentic AiAi Evaluation FrameworksDigital TwinsLarge Language Models (Llms)Machine LearningModel Fine-TuningPrompt EngineeringPythonRetrieval-Augmented Generation (Rag)SQL
Internet of Things • Mobile • Retail
Designs, builds, and analyzes complex structured and unstructured datasets; applies statistical methods, visualization, feature engineering, and machine learning to solve business problems. Develops revenue-generating models, identifies cost savings, optimizes processes, and delivers business insights using cloud, big data, data engineering, MLOps, and advanced machine learning tools.
Top Skills:
Apache AirflowAutomlAWSAzureDatabricksDockerETLGitGCPHadoopJupyter NotebooksKerasMatplotlibMlopsNosql DatabasesPandasPower BIPythonPyTorchRRelational DatabasesScalaScikit-LearnSeabornShinySparkSQLTableauTensorFlowTidyverse
What you need to know about the Charlotte Tech Scene
Ranked among the hottest tech cities in 2024 by CompTIA, Charlotte is quickly cementing its place as a major U.S. tech hub. Home to more than 90,000 tech workers, the city’s ecosystem is primed for continued growth, fueled by billions in annual funding from heavyweights like Microsoft and RevTech Labs, which has created thousands of fintech jobs and made the city a go-to for tech pros looking for their next big opportunity.
Key Facts About Charlotte Tech
- Number of Tech Workers: 90,859; 6.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Lowe’s, Bank of America, TIAA, Microsoft, Honeywell
- Key Industries: Fintech, artificial intelligence, cybersecurity, cloud computing, e-commerce
- Funding Landscape: $3.1 billion in venture capital funding in 2024 (CED)
- Notable Investors: Microsoft, Google, Falfurrias Management Partners, RevTech Labs Foundation
- Research Centers and Universities: University of North Carolina at Charlotte, Northeastern University, North Carolina Research Campus
