Data Scientist II

About the role

SEI is seeking a Software Engineer, Data Scientist to join our Enterprise Artificial Intelligence team. This role is designed for a highly technical builder who lives at the forefront of AI innovation and is passionate about transforming emerging technologies into enterprise-scale solutions. The ideal candidate has expertise in Python, Generative AI, Retrieval-Augmented Generation (RAG), AI agents, LLM orchestration, and modern AI engineering practices. They possess the rare combination of technical depth, creativity, business acumen, and execution excellence required to rapidly design, build, and deliver AI solutions that drive measurable business impact. This individual will serve as both a thought leader and technical catalyst, continuously evaluating emerging AI technologies while helping SEI translate innovation into secure, scalable, and widely adopted solutions.

Responsibilities

• Design, architect, and develop enterprise-grade AI applications leveraging Large Language Models (LLMs), agentic frameworks, RAG architectures, and emerging AI technologies.
• Build production-ready AI solutions from concept to deployment, driving adoption across business and technology teams.
• Develop intelligent assistants, copilots, autonomous agents, workflow automations, and knowledge-based AI systems.
• Design and optimize RAG pipelines, vector databases, knowledge graphs, semantic search solutions, and document intelligence systems.
• Rapidly prototype innovative AI capabilities and convert promising concepts into scalable enterprise platforms.
• Evaluate emerging AI tools, models, frameworks, and open-source technologies to identify opportunities that accelerate SEI's AI strategy.
• Build robust APIs, integrations, orchestration layers, and backend services that enable AI capabilities across the enterprise.
• Implement AI governance, security, observability, testing, and monitoring practices throughout the solution lifecycle.
• Contribute to AI platform strategy, reusable accelerators, development frameworks, and enterprise AI architecture.
• Stay continuously current on advancements in Generative AI, agentic systems, reasoning models, multimodal AI, open-source ecosystems, and enterprise AI engineering.

Requirements

• Bachelor's degree in Computer Science, Engineering, Data Science, or equivalent practical experience.
• At least 3 years of Python development skills with a strong understanding of software engineering principles and enterprise architecture.
• Hands-on experience building and deploying LLM-powered applications in production environments.
• Deep knowledge of Retrieval-Augmented Generation (RAG):
  • Vector databases
  • Embedding models
  • Semantic search architectures
  • Agentic AI frameworks
  • Prompt engineering
  • Model evaluation techniques
• Experience with modern AI frameworks and tooling such as LangChain, LangGraph, Semantic Kernel, LlamaIndex, AutoGen, CrewAI, OpenAI, Azure AI Foundry, Anthropic, and open-source LLM platforms.
• Strong software engineering background with experience in API development, microservices, cloud-native architectures, CI/CD pipelines, DevOps practices, and experience with Azure and AWS cloud platforms.
• Strong understanding of AI governance, security, responsible AI, and enterprise deployment considerations.
• Proven ability to move rapidly from idea to production while balancing innovation, scalability, and risk.
• Demonstrated success delivering solutions that achieve meaningful business adoption and measurable outcomes.

Skills

• Obsessive curiosity about AI and emerging technologies.
• A builder mentality with a passion for creating solutions rather than researching concepts.
• Ability to quickly learn, evaluate, and operationalize new technologies.
• Creative, outside-the-box thinker who challenges conventional approaches.
• Proven ability to influence technical direction and drive innovation across teams.
• Strong communication skills with the ability to explain complex AI concepts to both technical and executive audiences.

Benefits

• Comprehensive care for physical and mental well-being.
• Strong retirement plan.
• Tuition reimbursement.
• Support for working parents.
• Flexible Paid Time Off (PTO).
• Healthcare (medical, dental, vision, prescription, wellness, EAP, FSA).
• Life and disability insurance (premiums paid for base coverage).
• 401(k) match.
• Education assistance.
• Commuter benefits.
• Up to 11 paid holidays per year.
• 21 days PTO per year (pro-rated for new hires, increasing over time).
• Paid parental leave.
• Back-up childcare arrangements.
• Paid volunteer days.
• Discounted stock purchase plan.
• Investment options.
• Access to thriving employee networks.