Staff Software Engineer, AI

🕒 il y a 12 jours

🏄 California, Florida, +7 états de plus – Distant

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

💵 $210 000 - $260 000 / an

⏰ Temps Plein

🔴 Expert

🧑‍💻 Développeur Full-Stack

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Juniper Square

Site WebLinkedInTous les Emplois

201 - 500 employés

💸 Finance

🏠 Immobilier

☁️ SaaS

💰 €75 000 000 Series C en 2019-11

Finance • Real Estate • SaaS

Juniper Square est une entreprise qui propose une plateforme complète et des solutions adaptées aux partenariats d'investissement privés. Fondée en 2014, l'entreprise se concentre sur la facilitation d'une connexion et d'une communication fluides entre les associés commandités (GPs) et les associés commanditaires (LPs) tout au long du cycle de vie de l'investissement. La technologie de Juniper Square est spécialement conçue pour soutenir les entreprises de l'immobilier commercial, du capital-investissement et des sociétés de capital-risque de toutes tailles. La plateforme offre des services tels que l'administration de fonds, la collecte de fonds, la gestion des investisseurs, la conformité et le reporting aux investisseurs, le tout visant à améliorer la transparence, la gouvernance des données et l'expérience globale des investisseurs.

Description

• 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

🎯 Exigences

• 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

🏖️ Avantages

• 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