AI Engineer

🕒 Outubro 13

🇺🇸 Estados Unidos – Remoto (EUA)

⏰ Tempo Integral

🟡 Pleno

🟠 Sênior

🤖 Engenheiro de IA

👻 Score fantasma 10%

O que significa: a chance de ninguém estar realmente contratando para esta vaga.Como ler: 60% ou mais significa que achamos que é uma vaga fantasma. Pontuações mais baixas preocupam menos.Como pontuamos: tempo em aberto, republicações, vagas abertas vs tamanho do time, rapidez para fechar vagas, e se o salário está divulgado.Observação: é uma estimativa de dados públicos, não um julgamento da empresa. Vagas reais podem ter pontuação alta, então use como uma dica, não como um fato.

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Bridgeway Benefit Technologies

SiteLinkedInTodas as Vagas

201 - 500 funcionários

☁️ SaaS

👥 RH Tech

SaaS • HR Tech

A Bridgeway Benefit Technologies é uma empresa que se concentra em aprimorar soluções de administração de benefícios. Ela fornece serviços de software e tecnologia para melhorar e simplificar a gestão de benefícios dos funcionários para empresas e organizações. A empresa visa tornar a administração de benefícios mais eficiente e amigável por meio de seu conjunto de ferramentas tecnológicas.

Descrição

• Contribute to the technical direction for AI-enabled systems in partnership with senior engineers and the architecture team. • Participate in design reviews for AI-adjacent features and incorporate feedback from senior engineers and architects. • Build production-quality Python services, pipelines, and integrations applying LLMs and retrieval to internal and product problems. • Integrate LLM APIs into existing systems using established guidance on model selection, cost profile, and failure handling. • Ensure AI capabilities honor schema-per-tenant and PHI-boundary patterns within the multi-tenant model. • Partner with the data and analytics team on retrieval- and LLM-backed features for the lakehouse and analytics layer, including embedding, chunking, retrieval evaluation, semantic search, summarization, anomaly narration, and contextual guidance. • Contribute to prompt libraries, evaluation frameworks, reference implementations, and reusable components; help refine standards for model selection, evaluation, testing, observability, and cost management. • Evaluate emerging AI tools and provide input on build-versus-buy decisions. • Build AI implementations compliant with HIPAA, SOC 2, and NIST, including PHI handling, data residency, audit logging, BAA coverage, prompt-injection defenses, LLM DLP, model access governance, and secrets handling. • Maintain documentation of AI systems, data flows, and risk assessments for audit and compliance review. • Collaborate with engineering, product, customer success, security, data, and operations to identify automation opportunities, translate them into technical plans, and contribute to the customer-facing AI roadmap. • Participate in operational quality and on-call rotation, including incident response, post-incident learning, observability, and feedback loops to improve retrieval quality, prompt behavior, and agent reliability. • Track production AI cost, quality, and adoption metrics and report outcomes to the manager, architecture team, and team leads. • Apply enterprise AI-integration best practices and share knowledge with peers.

🎯 Requisitos

• 3–5 years of software engineering experience, with at least one year working on AI- or ML-backed systems, including contributions to at least one LLM-backed system in production. • Working knowledge of programmatic LLM orchestration, evaluation frameworks, and agent and tool-using systems, including exposure to securely connecting enterprise APIs to agentic systems. • Strong Python skills for production services, data pipelines, and integration work. • Experience building retrieval-augmented systems including familiarity with enterprise data architectures such as Databricks and Azure/AWS. • Strong written and verbal communication. • Familiarity with CI/CD, infrastructure-as-code, and MLOps practices for AI/ML systems. • Experience using generative AI tools such as Claude and Copilot to improve productivity and deliver high-quality outcomes. • Production experience in a regulated industry, with practical familiarity with HIPAA, SOC 2, or NIST, and with multi-tenant SaaS data isolation and identity/access patterns for B2B platforms (preferred). • Bachelor's or master's degree in Computer Science, Engineering, Data Science, or related field.

🏖️ Benefícios

• Remote position • Equal Opportunity Employer

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