20 hours ago
Remote, United StatesStaff+
Responsibilities
- Own the enterprise Generative AI and Agentic AI architecture vision, multi-year roadmap, governance, standards, reference architectures, and adoption guardrails.
- Define and govern scalable agentic AI platforms, including orchestration, reasoning, tool use, memory, human-in-the-loop controls, observability, fail-safes, and lifecycle management.
- Lead enterprise RAG, knowledge governance, retrieval, embeddings, vector store, context management, evaluation, and performance-tuning strategies.
- Establish integration patterns connecting AI capabilities with legacy platforms, mainframes, SQL Server, on-premises systems, and modern cloud services.
- Partner with data, analytics, and platform teams to define enterprise data architectures, ontologies, metadata, semantic layers, AI-ready data products, and quality standards.
- Ensure AI solutions address security, privacy, model risk, regulatory compliance, responsible AI, explainability, bias mitigation, red teaming, and auditability.
- Lead the AI architecture portfolio, investment prioritization, success metrics, value realization, production transition, and continuous improvement.
- Build AI architecture talent by coaching senior architects, setting capability standards, and creating communities of practice.
Requirements
- A master’s degree in AI, Machine Learning, Computer Science, Engineering, or a quantitative discipline is preferred.
- 10+ years of related progressive experience in enterprise architecture, platform architecture, or large-scale solution architecture, with 7+ years leading enterprise-scale GenAI, RAG, and Agentic AI delivery or architecture, or an equivalent combination of education and experience.
- Executive-level expertise with AWS AgentCore and Azure AI Agent Service is required.
- Deep mastery of agentic frameworks such as LangGraph and CrewAI is required.
- Proven experience establishing enterprise AI governance, driving cross-line-of-business adoption, and operationalizing AI within security, risk, and compliance constraints.
- Advanced mastery of Python, SQL, and PySpark, with deep expertise in vector stores, LLM platforms, and AI/ML lifecycle management.
- Proven leadership in AWS and Azure enterprise environments and strong functional exposure to advanced analytics platforms such as Palantir Foundry/AIP.
- Demonstrated transformation or enterprise innovation leadership, including operating models, reusable patterns, governance, cost efficiency, operational resilience, and risk reduction.
- Ability to influence executive stakeholders and bridge Data Science, AI Engineering, Enterprise Architecture, Technology, Security, Risk, Legal/Compliance, and business functions.
- Ability to work in a team environment and meet or exceed performance competencies.
Benefits
- Sedgwick offers work-life balance, a caring culture, and a diverse, equitable, and inclusive workplace.
- Reasonable accommodations may be considered when applicable and appropriate.
- Travel is required as needed.
- Sedgwick is an equal opportunity employer and drug-free workplace.
Categories
About Sedgwick
Sedgwick provides third‑party claims administration, risk and benefits services for employers, insurers, and public entities, spanning workers’ compensation, property and liability, disability and absence, and product recall. It sells outsourced claims management and related technology on a fee‑for‑service basis, supported by analytics and AI‑enabled tools, across operations in more than 80 countries. Founded in 1969 and headquartered in Memphis, Tennessee, Sedgwick is privately held under The Carlyle Group.