Staff Engineer – Agentic AI

🕒 Agosto 27

🇺🇸 Estados Unidos – Remoto (EUA)

💵 $132.600 - $182.250 / ano

⏰ Tempo Integral

🔴 Especialista

🧑‍💻 Engenheiro Full-stack

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Republic Services

SiteLinkedInTodas as Vagas

10.000+ funcionários

Fundada em 1998

💼 Consultoria

📦 Logística

Consulting • Logistics • Environmental Solutions

A Republic Services é um provedor líder em soluções ambientais abrangentes, especializado em reciclagem, gestão de resíduos e serviços de sustentabilidade. A empresa se associa a clientes residenciais e comerciais para criar comunidades mais limpas, seguras e saudáveis, impulsionando a sustentabilidade ambiental através de práticas e tecnologias inovadoras. Seus serviços incluem tratamento de resíduos sólidos e perigosos, aluguel de caçambas e resposta a emergências, todos direcionados a ajudar os clientes a alcançar suas metas de sustentabilidade.

Descrição

• Own the end-to-end development of the enterprise Agentic AI platform • Design, develop, test, and deploy high-performance generative AI capabilities for autonomous multi-step task execution • Ensure the platform is scalable, highly available, and suitable for mission-critical applications • Provide technical direction across the organization on GenAI-related projects • Collaborate with Solution and Enterprise Architects on architectures integrating LLMs, agent frameworks, and AI services • Lead coding, prompt engineering, and context engineering best practices • Conduct code, prompt, and context-pipeline reviews, including evaluation and regression testing • Establish guidelines for reproducible experiments and version control of prompts, contexts, agents, and datasets • Build internal frameworks and orchestration pipelines integrating LLMs and agents with enterprise data sources and services • Design retrieval, memory, and tool-use patterns for reliable enterprise context at inference time • Drive improvements in software development and LLM lifecycle processes • Implement LLMOps/GenAI Ops practices including automated evaluation, observability, guardrails, and CI/CD • Evaluate new GenAI tools and methods to improve team efficiency and system reliability • Mentor and coach team members in advanced GenAI and software engineering techniques • Provide non-managerial input on team performance, hiring, and promotions • Perform other job-related duties as assigned

🎯 Requisitos

• 7–10 years of progressively complex experience building and scaling enterprise software systems, with recent hands-on application of GenAI or Agentic AI technologies in production environments • 10+ years of experience designing, developing, and deploying enterprise-scale technology solutions, ideally with two years focused on GenAI/LLM or software architecture initiatives • Deep understanding of generative AI techniques and transformer-based models, including Claude, GPT, and other foundation or open-source LLMs • Hands-on experience integrating and adapting LLMs into enterprise applications • Expertise in prompt engineering, context engineering, RAG, GraphRAG, and agentic patterns such as ReAct, planner/executor, and multi-agent orchestration • Proficiency with GenAI frameworks/libraries such as LangChain, LangGraph, Semantic Kernel, or similar • Experience with model-serving runtimes and agent orchestration frameworks • Strong grasp of NLP fundamentals, tokenization, embeddings, and knowledge representation • Experience with cloud architectures including AWS Bedrock, kore.ai, and GCP AI • Familiarity with containerization and serverless architectures • Understanding of LLMOps/AI DevOps practices, including CI/CD, evaluation, versioning, observability, tracing, cost and token monitoring, red-teaming, and guardrails • Strong background in data engineering and architecture for AI-ready data • Hands-on experience with vector databases such as pgvector and Elastic Search, hybrid search, reranking, knowledge graphs, and embedding strategies • Experience designing semantic layers, metadata, and access controls • Experience integrating GenAI solutions via APIs, microservices, and event-driven patterns • Proven technical leadership, mentorship, technical design reviews, and best-practice enforcement • Demonstrated problem-solving skills and experience delivering proof-of-concept projects • Knowledge of AI ethics, safety, security, governance, compliance, and risk mitigation • Familiarity with monitoring, tracing, and logging tools such as Splunk, LangFuse, and CloudWatch • Bachelor's Degree in Computer Science or Data Science preferred • Not sponsorship eligible

🏖️ Benefícios

• Comprehensive medical benefits coverage, dental plans and vision coverage • Health care and dependent care spending accounts • Short- and long-term disability • Life insurance and accidental death & dismemberment insurance • Employee and Family Assistance Program (EAP) • Employee discount programs • Retirement plan with a generous company match • Employee Stock Purchase Plan (ESPP) • Paid Time Off (PTO) • Target annual bonus of 20% of base salary, subject to individual and company performance