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Ridgeline

AI-native front-to-back office investment platform

AI Product Manager - AI Platform, Quality and Evaluation

Technical Product ManagementConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • At least 5 years of product management experience building highly technical platform, infrastructure, or developer-focused products.
  • Demonstrated experience shipping production AI products powered by large language models.
  • Experience defining products that incorporate large language model evaluation frameworks, AI quality measurement, and continuous model evaluation.
  • Deep understanding of offline and online evaluation methodologies, model benchmarking, regression testing, and AI quality metrics.
  • Experience with large language model observability platforms such as Datadog LLM Observability, Langfuse, LangSmith, Arize AI, Braintrust, Galileo, or similar AI quality and evaluation solutions.
  • Familiarity with prompt engineering, experimentation frameworks, evaluation datasets, and large language model-as-a-judge techniques for generative AI applications.
  • Experience partnering effectively with software engineers, machine learning engineers, AI researchers, and cross-functional stakeholders.
  • Strong analytical skills and the ability to translate AI performance signals into product decisions.
  • Ability to learn about cutting-edge technologies while cultivating expertise in investment management workflows and enterprise AI.
  • An aptitude for problem solving.
  • Ability to communicate effectively.

Responsibilities

  • Define and execute the product strategy and roadmap for the AI Quality Platform.
  • Build scalable large language model evaluation frameworks and automated evaluation harnesses that enable continuous model validation.
  • Establish standardized offline and online evaluation methodologies, golden datasets, and quality benchmarks across AI products.
  • Define the roadmap for AI observability, enabling teams to monitor quality, latency, cost, reliability, and user outcomes in production.
  • Partner with engineering and AI researchers to build continuous regression testing and experimentation capabilities for generative AI systems.
  • Drive product decisions using AI quality metrics, customer feedback, and quantitative evaluation data.
  • Collaborate with engineering teams to deliver platform capabilities that enable trusted, measurable, and continuously improving AI experiences.
  • Translate advances in foundation models, evaluation techniques, and AI tooling into platform capabilities that create customer value.
  • Prioritize product investments using customer insights, product analytics, and measurable business outcomes.
  • Communicate product vision, roadmap, and priorities across technical and executive stakeholders.
  • Foster a collaborative environment rooted in ownership, continuous learning, experimentation, and transparency.

Desired Qualifications

  • Experience building products around retrieval-augmented generation, AI agents, Model Context Protocol, or model orchestration frameworks.
  • Experience with synthetic data generation and automated evaluation pipelines.
  • Experience building internal developer platforms or machine learning infrastructure products.
  • Experience in enterprise software as a service, developer platforms, or financial technology.

About the Company

Ridgeline

AI-native front-to-back office investment platform

Ridgeline delivers a single, cloud-based platform for investment management that unifies front-to-back office functions (client engagement, portfolio management, trading, compliance, reconciliation, accounting, and reporting) on one real-time data set. Its AI-native approach embeds Ridgeline AI throughout the platform, including digital coworkers, a conversational reporting assistant, and workflow automation, plus Market Intelligence integrated into workflows. It distinguishes itself from competitors by building the system from the ground up with an enterprise software approach and tying pricing to multi-year SaaS contracts that scale with assets under management. The company aims to help asset managers, wealth managers, and RIAs run their businesses more efficiently, reduce data silos, automate complex workflows, stay compliant, and produce timely financial reporting.

Company size
201-500
Company stage
Series E
Total funding
$250M
Headquarters
Incline Village-Crystal Bay, Nevada
Founded
2018

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