Senior Product Manager – AI Platform

🕒 Maio 29

🇺🇸 Estados Unidos – Remoto (EUA)

💵 $94.667 - $161.400 / ano

⏰ Tempo Integral

🟠 Sênior

🤖 Engenheiro de IA

🦅 Patrocina Visto H1B

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MeridianLink

SiteLinkedInTodas as Vagas

501 - 1000 funcionários

Fundada em 1998

💳 Fintech

🏦 Bancário

☁️ SaaS

💰 $485.000.000 Post-IPO Debt em 2021-11

Fintech • Banking • SaaS

A MeridianLink é uma fornecedora líder de soluções SaaS para instituições financeiras, especializada em sistemas de originação de empréstimos e tecnologias de transformação digital. Sua plataforma fim-a-fim melhora as experiências digitais através da integração com sistemas de gestão de empréstimos hipotecários (LOS), soluções para abertura de contas de depósito e mais. Os sistemas em nuvem da MeridianLink aprimoram a eficiência no processamento de empréstimos e cobranças, na tomada de decisões orientadas por dados e na gestão de contas. A empresa colabora com parceiros para expandir seu alcance de mercado e impulsionar o crescimento na indústria de fintech. Com mais de 25 anos de experiência, a MeridianLink é dedicada a apoiar bancos, cooperativas de crédito e outros provedores de serviços financeiros através de tecnologia e inteligência empresarial.

Descrição

• Own the end-to-end product strategy and roadmap for the AI platform layer. • Partner with executive leadership to align AI initiatives with company-wide product vision and revenue goals. • Build business cases justifying R&D investment based on expected benefits. • Partner with principal engineers and ML infrastructure leads to make informed build-vs-buy-vs-partner decisions on foundational AI capabilities • Establish and govern platform-level standards: API versioning policies, model lifecycle management, prompt versioning, and observability requirements • Stay updated with the latest trends and advancements in AI and ML, to identify opportunities for innovation and incorporate relevant insights into product strategy and development. • Treat internal R&D teams as your primary customers. Conduct structured discovery with feature teams to understand their AI integration pain points, latency requirements, and data access needs. • Define and own the developer experience for consuming the AI platform: API contracts, SDK design, documentation standards, sandbox environments, and onboarding flows. • Establish a platform roadmap governance process: intake, prioritization, and communication of platform changes to dependent teams. • Build feedback loops with consuming teams post-release to detect friction, integration failures, and unmet capability needs early. • Establish monitoring and observability standards: model drift detection, confidence thresholds, input distribution shifts, and alerting policies. • Translate regulatory requirements for AI use in lending (FCRA, ECOA, HMDA, OCC SR 11-7 model risk management) into concrete platform requirements: explainability APIs, audit logging, adverse action reason codes, and human-in-the-loop override mechanisms. • Partner with information security to define data residency, encryption-at-rest/in-transit requirements, and PII handling policies for AI data flows. • Maintain a clear capability matrix of which AI features are permissible for which customer tiers, regulatory environments, and data sensitivity levels. • Define and own platform-level SLOs: inference availability, P99 latency, pipeline throughput, and data freshness. • Build platform health dashboards and escalation playbooks for AI service degradation—distinct from application-layer monitoring. • Track platform adoption metrics: number of consuming teams, API call volumes, feature flag usage, and time-to-integrate for new consumers. • Hold regular platform reviews with engineering leadership to surface technical debt, capacity constraints, and architectural risks before they affect downstream feature teams. • Align platform metrics with those of the AI-based application products; collaborate with application Product Managers to ensure alignment.

🎯 Requisitos

• 5+ years’ experience in product management, with proven success designing enterprise AI/ML products in a SaaS B2B environment. • At least 3 years in a platform, infrastructure, or developer tools PM role • Experience conducting customer/user research, usability testing, and translating insights into product strategy. Proficiency with AI-driven prototyping methods. • Strong organizational and multi‑tasking abilities, capable of managing multiple projects, priorities, and communication channels in a fast‑paced environment • Mastery of agile methodologies, processes, artifacts. Understanding exposure to emerging DevAI practices. • Strong problem-solving skills • Effective storytelling and presentation abilities • Excellent collaboration skills within and across teams • Ability to give and receive constructive design feedback • Awareness of industry trends, emerging technologies, and best practices in AI product design. • Demonstrated track record of taking AI features from concept to production—including model integration, data contracts, and post-launch monitoring • Experience with AI/ML concepts, LLMs, MCPs, GenAI platforms, API integration • Familiarity with responsible AI principles, model interpretability, bias mitigation, and quality/accuracy metrics required for production grade AI systems. • Experience collaborating with Data Science and Engineering teams to define training data needs, evaluate model performance, and implement iterative feedback loops. • Proven track record shipping AI or ML capabilities into production: you have written PRDs that specify inference APIs, data schemas, latency budgets, model versioning strategies, and observability requirements. • Sufficient technical depth to participate in architecture discussions with Engineering. • Hands-on familiarity with at least one modern AI/ML stack, vector databases, and model serving infrastructure. • Experience defining API contracts and SDK developer experiences—including versioning strategies, deprecation policies, and changelog communication. • Comfort working with data engineering concepts: ETL/ELT pipelines, feature stores, schema registries, event streaming (Kafka, Kinesis), and data quality frameworks. • Strong written communication skills for technical audiences.

🏖️ Benefícios

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