Account Manager

5+ years of experience in customer-facing roles within B2B/SaaS, commercializing technical products.
2+ years in a quota-carrying AE or AM role with ownership of the full post-sales customer journey OR Renewals Managers with prior quota-carrying experience.
Proven experience managing Enterprise/Strategic accounts by effectively navigating relationships from developers to C-level stakeholders and driving account growth through the alignment of technical value with key business outcomes.
In-depth knowledge of AI/ML Development Process, The Software Development Lifecycle (SDLC), OR CI/CD.
Strong collaboration mindset with a demonstrated ability to thrive in highly collaborative, asynchronous, remote-first environments.
Entrepreneurial self-starter with a proven ability to take initiative, quickly learn technical and functional concepts, and build/adapt in high-growth environments without waiting for direction.

Manage a portfolio of strategic accounts, owning all commercial and success aspects of the post-sales journey.
Collaborate with Field Engineering to lead renewal and expansion strategies.
Identify and execute opportunities for upsell, cross-sell, and broader platform adoption.
Partner with ML teams, developers, and technical leaders to align Weights & Biases usage with business goals.
Drive successful onboarding experiences with tailored success plans and enablement programs.
Monitor and guide product adoption through regular check-ins, training sessions, and QBRs.
Cultivate multi-threaded relationships across technical and executive stakeholders.
Serve as a trusted advisor to your customers by understanding their architecture, roadmap, and strategic priorities.
Act as the voice of the customer internally, influencing product and go-to-market strategy.
Work cross-functionally with Product, Engineering, Field Engineering, Support, and Marketing.
Maintain account documentation, health metrics, and forecasts to drive operational visibility.
Help shape the future of Account Management at W&B by contributing to playbooks, processes, and tooling.

Experience supporting or working with LLMOps, MLOps, or data infrastructure teams.
Familiarity with Git, Jupyter, Python, PyTorch, or cloud platforms (AWS, GCP, Azure).
Experience creating and executing growth or activation strategies for technical products.
Exposure to the Foundation Model Builder, AI applications, or Generative AI ecosystem.
Background managing global enterprise accounts with large-scale deployments.