Staff Software Engineer, AI

🕒 Maio 26

🏄 California, Florida, +7 estados a mais – Remoto

🏄 California – Remote 🐊 Florida – Remote 🌽 Illinois – Remote 🗽 New York – Remote 🌲 North Carolina – Remote 🏈 Ohio – Remote 🚗 Michigan – Remote 🔔 Pennsylvania – Remote 🤠 Texas – Remote

💵 $210.000 - $260.000 / ano

⏰ Tempo Integral

🔴 Especialista

🧑‍💻 Engenheiro Full-stack

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Juniper Square

SiteLinkedInTodas as Vagas

201 - 500 funcionários

💸 Finanças

🏠 Imobiliário

☁️ SaaS

💰 $75.000.000 Series C em 2019-11

Finance • Real Estate • SaaS

A Juniper Square é uma empresa que oferece uma plataforma abrangente e soluções personalizadas para parcerias de investimento privado. Fundada em 2014, a empresa se concentra em possibilitar uma conexão e comunicação contínua entre General Partners (GPs) e Limited Partners (LPs) ao longo de todo o ciclo de vida do investimento. A tecnologia da Juniper Square é feita sob medida para apoiar empresas de imóveis comerciais, private equity e capital de risco de todos os tamanhos. A plataforma oferece serviços como administração de fundos, captação de recursos, gestão de investidores, compliance e relatórios para investidores, todos destinados a aprimorar a transparência, a governança de dados e a experiência geral do investidor.

Descrição

• Own Technical Direction and Architecture • Set the technical direction for AI systems - including shared AI SDKs, guardrails, evaluation frameworks, feedback systems, and agentic workflow infrastructure • Own architecture and technical strategy for complex backend and AI platform systems, from design through production • Lead technical design for ambiguous, cross-functional initiatives - evaluating tradeoffs, aligning stakeholders, and driving implementation • Evaluate and select technologies with a bias toward what ships well and scales sustainably • Build and Operate AI Systems • Write production code as a hands-on individual contributor - this is not a role that delegates implementation to others • Design and operate LLM-powered systems: RAG pipelines, agentic workflows, evaluation infrastructure, guardrails, and model observability • Own end-to-end reliability of AI systems from design through structured output delivery • Define quality benchmarks, evaluation frameworks, and feedback loops to continuously improve AI output accuracy and system reliability • Champion AI-Native Development • Champion and embed AI-native development practices and tools (e.g., Cursor, Augment) to achieve significant productivity gains across the team • Foster a culture of rapid iteration, high velocity, and quality - including guiding the effective use of AI code generation • Bring strong, informed opinions about how to get the most from AI-assisted development while maintaining reliability and correctness • Lead and Grow the Team • Mentor engineers, raise the quality of technical decision-making, and help the team execute with consistency • Establish coding standards, review practices, and architectural documentation that scale as the team grows • Help define what "good" looks like for a team building at speed without sacrificing quality • Partner with recruiting to build and grow the team • Collaborate Cross-Functionally • Work closely with engineering managers, product, design, and QA to translate requirements into executable technical plans • Participate actively in design reviews and roadmap discussions with grounded, implementation-level perspective • Handle most cross-team conflicts and technical decisions autonomously

🎯 Requisitos

• 7+ years of backend and/or ML engineering experience with a trajectory of increasing technical leadership, architectural responsibility, and mentorship • A portfolio of shipped production systems - we will ask you to walk through specific technical decisions you personally made and code you personally wrote; this is not a role for someone whose primary contribution has been directing others • Deep expertise in Python, with strong proficiency in building production-grade backend services; experience with other server-side languages (Node/TS, Java) a plus • Production experience building and operating AI/LLM-powered systems — such as AI SDKs, RAG pipelines, evaluation frameworks, agentic workflows, or model observability — in real systems, not just experimentation • Experience leading technical design for complex systems, including making architecture decisions, evaluating tradeoffs, and guiding implementation across multiple engineers or teams • Experience with relational/NoSQL databases, including schema design, performance tuning, and data modeling • Experience building and operating cloud-native systems using AWS, Docker, Kubernetes, and infrastructure as code • Strong understanding of CI/CD, observability, reliability, and operational excellence in production environments • Ability to work through ambiguity, break down complex problems, and drive alignment across engineering, product, and design • Demonstrated ability to raise engineering quality through technical standards, design reviews, mentoring, and reusable platform patterns • Hands-on experience with AI-native development tools (e.g., Cursor, Augment); demonstrated ability to embed AI-driven practices to accelerate team velocity and code quality • Ability to critically evaluate AI-generated code and outputs, including identifying failure modes, regressions, and edge cases

🏖️ Benefícios

• Health, dental, and vision care for you and your family • Life insurance • Mental wellness coverage • Fertility and growing family support • Flex Time Off in addition to company-paid holidays • Paid family leave, medical leave, and bereavement leave policies • Retirement saving plans • Allowance to customize your work and technology setup at home • Annual professional development stipend