Applied AI Engineer

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🕒 Abril 28

🥔 Idaho, Louisiana, +2 estados a mais – Remoto

🥔 Idaho – Remote ⚜️ Louisiana – Remote 🌾 Nebraska – Remote 🎸 Tennessee – Remote

⏰ Tempo Integral

🟡 Pleno

🟠 Sênior

🤖 Engenheiro de IA

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Sedgwick

SiteLinkedInTodas as Vagas

10.000+ funcionários

🏢 Corporativo

📋 Conformidade

Insurance • Enterprise • Compliance

A Sedgwick é uma fornecedora global de soluções de tecnologia para riscos, benefícios e negócios integrados. Eles ajudam pessoas e organizações a gerenciar e mitigar riscos com soluções em administração de sinistros de acidentes, saúde, invalidez, compensação por desemprego e responsabilidade, entre outros. A Sedgwick oferece serviços como administração de sinistros, consultoria de construção, contabilidade forense e engenharia forense. Suas especialidades incluem restauração de propriedades, proteção de marcas e prevenção de perdas em vários setores, incluindo agricultura, construção e setores ambientais. A empresa enfatiza diversidade, equidade e inclusão (DEI) e práticas ambientais, sociais e de governança (ESG).

Descrição

• Architect and deploy LLM-powered and agentic AI solutions that transform claims intake, policy interpretation, fraud detection, and resolution workflows. • Design end-to-end retrieval-augmented generation (RAG) systems leveraging enterprise knowledge bases, policy documents, SOPs, and historical claims data. • Build autonomous and semi-autonomous agents capable of reasoning, planning, and executing multi-step claims processes. • Develop stateful workflow orchestration layers that manage context, memory, and task sequencing across interactions. • Implement planning and reflection loops that decompose complex claims scenarios into structured subtasks. • Enable dynamic tool use through function calling and secure API integrations with claims systems, CRM platforms, document repositories, and analytics tools. • Develop document intelligence pipelines using LLMs for summarization, entity extraction, classification, validation, and timeline reconstruction. • Design structured prompt frameworks that enforce deterministic outputs and domain-aware reasoning. • Build multi-agent systems that coordinate document review, coverage analysis, compliance checks, and decision support. • Implement human-in-the-loop checkpoints for escalation, review, and override of AI-driven decisions. • Develop guardrails, output validation layers, and hallucination mitigation strategies. • Enforce structured outputs using schemas, type validation, and deterministic post-processing logic. • Optimize token consumption, inference latency, and cloud infrastructure costs. • Deploy scalable AI microservices using containerization and cloud-native architectures. • Implement monitoring for model drift, retrieval quality degradation, reasoning failures, and workflow breakdowns. • Maintain detailed audit logs of model decisions, agent reasoning steps, and tool executions. • Develop evaluation frameworks to test reasoning accuracy, workflow completion rates, and system reliability. • Collaborate with data engineering to build embedding pipelines, feature stores, and vector indexing strategies. • Ensure compliance with Responsible AI standards, data privacy regulations, and enterprise governance policies. • Partner with claims operations leadership to embed AI capabilities directly into adjuster and supervisor workflows. • Measure business impact through cycle-time reduction, automation coverage, fraud detection lift, and operational efficiency gains.

🎯 Requisitos

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Engineering, or related field. • 5+ years of experience building production-grade AI or advanced software systems. • 2–4+ years of hands-on experience with LLM-powered applications and orchestration layers. • Strong expertise in retrieval-augmented generation architectures and vector search systems. • Experience designing and implementing multi-agent systems and workflow orchestration engines. • Deep understanding of planning loops, contextual memory, and tool-augmented LLM reasoning. • Strong proficiency in Python and API-driven system design. • Experience integrating enterprise platforms and building secure connectors. • Familiarity with Azure OpenAI or similar enterprise LLM environments. • Experience deploying containerized services and managing CI/CD pipelines. • Understanding of distributed systems, microservices, and event-driven architectures. • Experience implementing guardrails, access controls, and auditability mechanisms. • Strong knowledge of evaluation methodologies for LLM reliability and agent performance. • Experience in insurance, claims, healthcare, or other regulated industries preferred. • Ability to translate complex operational workflows into scalable, AI-driven autonomous systems.

🏖️ Benefícios

• Flexible work arrangements • Professional development opportunities