Staff Software Engineer, AI

🕒 vor 1 Monat

🇺🇸 Vereinigte Staaten – Remote

💵 $152.519 - $260.000 / Jahr

⏰ Vollzeit

🔴 Experte

🧑‍💻 Full-Stack-Entwickler

🦅 H1B-Visum-Sponsor

info

🗣️🇺🇸🇬🇧 Englisch erforderlich

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Logo of MeridianLink

MeridianLink

501 - 1000 Mitarbeiter

Gegründet 1998

💳 Fintech

🏦 Bankwesen

☁️ SaaS

💰 €485.000.000 Post-IPO Debt im 2021-11

Fintech • Banking • SaaS

MeridianLink ist ein Softwareunternehmen, das eine cloud-basierte, umfassende digitale Kreditvergabe- und Kontoeröffnungsplattform für Finanzinstitute bietet. Die konfigurierbare MeridianLink One-Plattform beinhaltet Kreditvergabe (Privat-, Unbesicherte-, Auto-, Hypothekarkredite), digitale Kontoeröffnung, Point-of-Sale-Finanzierung, Inkasso, Daten & Berichterstattung sowie Beratung/Analyse, um Banken und Kreditgenossenschaften bei der Automatisierung von Prozessen, der schnelleren Entscheidungsfindung und der Verbesserung der digitalen Kundenerfahrungen zu unterstützen. MeridianLink bedient hauptsächlich Banken, Kreditgenossenschaften und Hypothekengeber durch SaaS-Lösungen und ein Partner-Ökosystem.

Beschreibung

• Own the reference architecture for the AI platform, encompassing API abstractions, prompt and version management, RAG infrastructure, vector retrieval, evaluation harnesses, and model serving. • Lead build-vs-buy evaluations for AI components, including due diligence and integration planning. • Design foundational data pipelines and infrastructure to support reliable, scalable AI services. • Define and document API contracts, standards, and platform interfaces across engineering. • Contribute to backend development in Python and RESTful API design, including integrations with leading AI providers. • Participate in full-stack delivery when needed, using React/TypeScript/Vite to deliver AI features. • Build and maintain tooling, SDKs, and platform APIs to enable safe, scalable AI adoption by product teams. • Drive improvements to AI-assisted development workflows with tools like GitHub Copilot and Claude. • Implement integrations with LLMs: context management, prompt templating, response validation, and robust fallback strategies. • Build and maintain evaluation frameworks for reproducible model testing. • Establish observability and performance tracking for AI services. • Participate in designing vector-based retrieval and model serving infrastructure as custom model capabilities become a focus. • Advise and collaborate with Security through architecture and design phases, ensuring compliance and security standards are met. • Apply secure-by-default principles (encryption, least privilege, audit logging) and stay current with financial data governance and privacy standards. • Collaborate with Product to translate business needs into technical designs and specifications, while contributing a strong architectural perspective. • Support AI platform roadmap development with product leadership. • Engage in companywide architectural forums and workgroups to drive engineering standards. • Partner with Data Engineering, DevOps/SRE, and Security to ensure aligned technical foundations. • Mentor L3–L4 engineers through code reviews, design sessions, and architectural guidance. • Promote engineering excellence, robust documentation, and reusable internal resources.

🎯 Anforderungen

• 8+ years in professional software engineering, with demonstrated cross-team architectural influence • Proven end-to-end delivery of AI-powered features, from product concepts to production • Experience leading large, complex technical initiatives • Strong proficiency in Python and RESTful API development (FastAPI, Django) • Knowledge of full-stack development (React, TypeScript) • Hands-on integration with third-party LLM/AI APIs • Experience with AWS (preferred), including IAM, networking, managed services, and storage • Solid foundation in distributed systems, API design, cloud-native architecture • Comfortable with CI/CD pipelines, version control, Docker, and AI-assisted development tools • Demonstrated ability to author durable technical proposals (RFCs, ADRs) • Clear communicator with technical and non-technical stakeholders • GenAI experience (e.g., RAG pipelines, prompt management, LLM evaluation, agent frameworks) • Familiarity with vector databases/semantic search (Pinecone, pgvector, OpenSearch) • Exposure to model serving, MLOps/LLMOps practices, and model lifecycle/deployment tools • Experience building developer platforms, SDKs, and self-service engineering tooling • Experience with IaC tools (Terraform/Pulumi), Kubernetes, and observability tools (Prometheus, Grafana, Datadog) • Leadership in technical communities, mentoring, and architectural standards • Bachelor’s in Computer Science, Software Engineering, or equivalent experience

🏖️ Vorteile

• Insurance coverage (medical, dental, vision, life, and disability) • Flexible paid time off • Paid holidays • 401(k) plan with company match • Remote work

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