Staff Software Engineer

🕒 vor 11 Tagen

🗽 New York – Remote

🗽 New York – Remote

💵 $160.000 - $180.000 / Jahr

⏰ Vollzeit

🔴 Experte

🧑‍💻 Full-Stack-Entwickler

🦅 H1B-Visum-Sponsor

Dieses Unternehmen hat in der Vergangenheit H1B-Visa gesponsert.

Jetzt Bewerben

Ähnliche Remote-Jobs finden

E-Mails für Remote-Jobs erhalten

📊 Überprüfen Sie Ihre Lebenslauf-Bewertung für diese Stelle

Verbessern Sie Ihre Chancen auf ein Vorstellungsgespräch, indem Sie Ihre Lebenslauf-Bewertung vor der Bewerbung überprüfen.

Lebenslauf hochladen

Zeta Global

WebsiteLinkedInAlle Stellen

1001 - 5000 Mitarbeiter

Gegründet 2007

☁️ SaaS

🤖 Künstliche Intelligenz

🤝 B2B

💰 Post-IPO Debt im 2024-09

SaaS • Artificial Intelligence • B2B

Zeta Global ist eine KI-gestützte Marketing-Cloud, die proprietäre KI und Billionen von Verbrauchersignalen nutzt, um Kunden effizienter zu gewinnen, zu binden und zu halten. Die Zeta Marketing Platform (ZMP) bietet eine umfassende Suite von Tools, darunter Datenmanagement, Customer Data Platforms (CDP), E-Mail-Service-Provider (ESP) und Digital Signal Processing (DSP), um individualisierte Kundenerlebnisse zu schaffen und die Marketingergebnisse zu verbessern. Zeta legt Wert auf Omnichannel-Marketing, Kundenintelligenz und datengesteuerte Marketingstrategien, arbeitet mit Marken, Agenturen und Verlagen weltweit zusammen, um das Markenwachstum und die Kundenbindung zu beschleunigen. Ihre Plattform ist darauf ausgelegt, komplexe Marketingherausforderungen mit Lösungen für Kundenakquise, Wachstum und Bindung durch prädiktive KI und umsetzbare Verbraucherdaten zu bewältigen.

Beschreibung

• 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.

🎯 Anforderungen

• 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.

🏖️ Vorteile

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