1 day ago
Remote, United StatesStaff+
Responsibilities
- Own the enterprise Generative AI and Agentic AI architecture vision, roadmap, governance forums, standards, and adoption guardrails.
- Define and govern scalable agentic AI platforms using AWS AgentCore, Azure AI Agent Service, and frameworks such as LangGraph and CrewAI.
- Establish enterprise patterns for multi-agent orchestration, reasoning, tool use, memory, human-in-the-loop controls, observability, fail-safes, and lifecycle management.
- Own enterprise RAG and knowledge architecture strategies covering retrieval, embeddings, vector stores, context management, evaluation, provenance, permissions, lineage, and data quality.
- Define integration patterns across legacy platforms, mainframes, SQL Server, on-premises systems, AWS, Azure, identity, networking, monitoring, disaster recovery, and service management.
- Partner with data, analytics, and platform teams on ontologies, metadata, semantic layers, AI-ready data products, and governance using Palantir, Databricks, and Snowflake.
- Serve as the executive technical authority for AI security, privacy, model risk, compliance, responsible AI, red teaming, bias mitigation, explainability, and auditability.
- Lead the AI architecture portfolio, investment prioritization, value realization metrics, production transition, operational ownership, and continuous improvement.
- Build enterprise AI architecture capability through coaching, standards, communities of practice, vendor strategy, and ecosystem partnerships.
- Represent the organization in executive engagements and cross-enterprise transformation initiatives; travel as required.
Requirements
- 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 in complex corporate environments, or an equivalent combination of education and experience is required.
- Executive-level expertise with AWS AgentCore and Azure AI Agent Service and deep mastery of agentic frameworks such as LangGraph and CrewAI.
- 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; deep expertise in vector stores such as Pinecone, OpenSearch, and Azure AI Search; and experience with 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 success in a Transformation Office or enterprise innovation function, including operating models, reusable patterns, and governance for responsible adoption.
- Ability to align executive stakeholders, bridge data science, AI engineering, and enterprise architecture, and translate architecture decisions into business value, cost efficiency, resilience, and risk reduction.
- Ability to work in a team environment and meet or exceed performance competencies.
Benefits
- Work-life balance and a caring workplace culture.
- Equal opportunity employment and a drug-free workplace.
- Reasonable accommodations may be considered when applicable and appropriate.
- Travel is required as needed.
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.