Lead Data Scientist – Generative AI & Intelligent Systems

Lead Data Scientist – Generative AI & Intelligent Systems Location: Oaks, PA – Hybrid (Onsite Tuesday, Wednesday & Thursday) Candidates: Local to Oaks, PA only Duration: Long-term Contract : 24+ Months Visa: USC, GC, H4-EAD, L2-EAD Interview: Video

Important: Please provide 2 managerial-level professional references with the submission. References must be from manager-level contacts. Job Summary SEI Investments is seeking an experienced and visionary Lead Data Scientist – Generative AI & Intelligent Systems to lead enterprise AI innovation across the organization.

This role will define and execute AI strategies spanning Machine Learning, Generative AI, Agentic AI, Intelligent Automation, and AI-powered digital experiences.

The ideal candidate will lead the design, development, and deployment of scalable AI solutions, including enterprise copilots, RAG-based knowledge systems, AI agents, intelligent workflow automation, conversational AI, and advanced predictive analytics.

The candidate will work closely with business leaders, product teams, architects, cybersecurity, engineering, and other stakeholders to transform emerging AI technologies into practical enterprise solutions while establishing AI governance, best practices, security standards, and scalable frameworks. Key Responsibilities Define and drive the enterprise AI strategy across Machine Learning, Generative AI, Agentic AI, and Intelligent Automation.

Lead the design and delivery of enterprise-scale Generative AI applications, RAG platforms, AI copilots, chatbots, virtual assistants, and AI agents.

Architect AI solutions integrating LLMs, enterprise knowledge repositories, APIs, and business workflows.

Design and oversee RAG pipelines, vector databases, semantic search, and knowledge management solutions.

Evaluate emerging AI technologies, foundation models, frameworks, orchestration platforms, and agentic architectures.

Lead AI product development from ideation and prototyping through production deployment and continuous improvement.

Establish best practices for LLMOps, prompt engineering, model evaluation, AI governance, observability, AI safety, and responsible AI. Develop AI solutions using both structured and unstructured data sources. Ensure AI solutions meet security, privacy, regulatory, governance, and compliance requirements.

Partner with business stakeholders to identify and prioritize high-value AI opportunities.

Mentor and guide data scientists, AI engineers, architects, and technical leaders.

Communicate AI strategies, architectures, technical solutions, and business value to executive leadership and non-technical stakeholders. Required Qualifications Bachelor's degree or equivalent relevant experience. Master's, MBA, PhD, or CFA is a plus.

10+ years of experience in Artificial Intelligence, Data Science, Machine Learning, Software Engineering, or related fields.

Proven experience delivering enterprise-scale AI and Machine Learning solutions from concept through production.

Strong expertise in Generative AI, LLMs, RAG, prompt engineering, and AI orchestration.

Hands-on experience with technologies such as Azure AI, OpenAI, Anthropic, LangChain, Semantic Kernel, AutoGen, CrewAI, MCP, and vector databases.

Strong understanding of Agentic AI, including planning, orchestration, memory, tool usage, workflow automation, and multi-agent systems.

Strong cloud experience with Azure, AWS, or GCP and production AI deployment architectures.

Advanced Python development skills with experience building scalable AI applications and APIs.

Experience working with structured and unstructured data, knowledge repositories, search platforms, and document intelligence solutions.

Experience with AI governance, model evaluation, observability, security controls, and responsible AI.

Proven ability to balance innovation with governance, risk management, security, and operational excellence. Preferred Qualifications Thought leadership in Artificial Intelligence, Generative AI, Agentic AI, or emerging AI technologies.

Experience defining enterprise AI roadmaps, operating models, governance frameworks, and adoption strategies. Financial services, wealth management, or other regulated-industry experience. Strong executive communication and presentation skills. Experience leading cross-functional teams involving AI engineers, data scientists, architects, product managers, cybersecurity teams, and business leaders.

Experience evaluating AI platforms, vendors, and strategic technology partnerships.

Strong product mindset with the ability to translate complex business challenges into scalable AI solutions. Excellent analytical, problem-solving, and strategic decision-making skills.