Staff Software Engineer

🕒 Maio 28

🗽 New York – Remoto

🗽 New York – Remote

💵 $160.000 - $180.000 / ano

⏰ Tempo Integral

🔴 Especialista

🧑‍💻 Engenheiro Full-stack

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Zeta Global

SiteLinkedInTodas as Vagas

1001 - 5000 funcionários

Fundada em 2007

☁️ SaaS

🤖 Inteligência Artificial

🤝 B2B

💰 Post-IPO Debt em 2024-09

SaaS • Artificial Intelligence • B2B

A Zeta Global é uma nuvem de marketing impulsionada por IA que aproveita a IA proprietária e trilhões de sinais de consumidores para adquirir, crescer e reter clientes de maneira mais eficiente. A Zeta Marketing Platform (ZMP) oferece um conjunto abrangente de ferramentas, incluindo gerenciamento de dados, plataformas de dados de clientes (CDP), provedores de serviço de e-mail (ESP) e processamento de sinal digital (DSP), para criar experiências personalizadas para clientes e melhorar os resultados de marketing. A Zeta enfatiza o marketing omnichannel, inteligência de cliente e estratégias de marketing orientadas por dados, fazendo parceria com marcas, agências e editoras em todo o mundo para acelerar o crescimento e o engajamento da marca. Sua plataforma é projetada para enfrentar desafios complexos de marketing com soluções para aquisição, crescimento e retenção de clientes por meio de IA preditiva e dados de consumidores acionáveis.

Descrição

• Identify systemic engineering challenges across our platforms and drive their resolution — shaping the technical backlog and near-term architecture. • Propose and validate technical approaches for problems involving scale, performance, security, or cross-team dependencies. • Lead architectural decisions for complex, ambiguous, or high-risk initiatives. • Incorporate modern industry patterns — including AI/ML tooling — into our technical strategy where it genuinely moves the needle. • Write code, review PRs, debug production issues, and optimize system performance — this is not a whiteboard-only role. • Dive deep into our AWS infrastructure, Kubernetes workloads, and JVM-based services to find and fix what's actually wrong. • Participate in our on-call rotation as a second-level escalation point for complex engineering incidents. • Step in during large incidents to help teams triage, coordinate, and resolve — and follow through with post-incident reviews that drive lasting fixes. • Champion operational excellence across our engineering teams: observability, reliability, deployment practices, and the operational habits that keep systems healthy at scale. • Partner with engineering teams as a technical point of contact on complex projects — ensuring good architectural decisions get documented and don't have to be re-litigated. • Work directly with Engineering Managers to align technical work with team and product priorities. • Mentor engineers across our teams, raising the technical floor through reviews, pairing, and direct feedback. • Stay close to the customer. Understand how Sailthru's platform affects the people using it, bring that context into technical decisions, and push back when engineering choices create friction for customers. • Partner closely with the product team — contribute to shaping what gets built, not just how. The best technical decisions happen when engineering and product are thinking together from the start.

🎯 Requisitos

• Deep, battle-tested expertise in AWS and cloud-native architecture — you know how to build reliable, scalable systems at real traffic volumes. • Strong JVM fundamentals, primarily Java and Kotlin, with the range to work across languages as the problem demands. • Hands-on Kubernetes experience — deploying, operating, and troubleshooting workloads in production. • Experience designing and operating distributed systems — fault tolerance, consistency tradeoffs, service coordination, and failure modes at scale. • Comfort working with large databases at scale — query optimization, schema design, operational concerns, and the tradeoffs between data storage approaches. • Practical experience with AI/ML engineering — whether integrating LLM capabilities, building pipelines, or evaluating where AI actually helps vs. adds complexity. • A track record of delivering large, complex initiatives in ambiguous environments — scoping, driving alignment, and shipping. • Strong debugging instincts and a bias toward root-cause analysis over symptomatic fixes. • The judgment to know when to push for the right solution and when pragmatism wins. • Fluency with AI-driven development tools — Claude Code, GitHub Copilot, Codex, or similar — is a firm requirement. We use these tools daily and expect staff engineers to be effective with them and to model best practices around prompt discipline, output validation, and security. • Comfort operating without a playbook — you've solved novel problems before and know how to navigate uncertainty. • Comfort working in and around legacy codebases — you can read unfamiliar code, understand systems that predate you, and make meaningful improvements without needing a rewrite. • The ability to quickly map an existing architecture — identify bottlenecks, constraints, and opportunities — and turn that understanding into concrete, actionable proposals that increase team velocity. • You think big. You're not constrained by how things are done today — you can envision meaningfully better outcomes and work backwards from them to find a path. • Bias for action. You'd rather move with imperfect information and course-correct than wait for certainty that never comes. You know the difference between a reversible decision and one that warrants more care.

🏖️ Benefícios

• Unlimited PTO • Excellent medical, dental, and vision coverage • Employee Equity and Stock Purchase Plan • Employee Discounts, Virtual Wellness Classes, and Pet Insurance And more!!