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As a Senior Product Manager at Assembled, you will lead product vision and strategy, focus on onboarding and AI workforce management, drive integrations and analytics, mentor junior PMs, and ensure high product quality.

The Technical Recruiter will drive full-cycle recruiting for engineering, product, and design roles, partnering with hiring managers and utilizing AI to enhance recruiting strategies while maintaining a strong candidate experience.

Manage financial operating models, support planning cycles, track KPIs, contribute to board materials, and analyze pricing strategies. Requires excellent modeling skills.

The Strategic Partnerships Manager will build and manage critical partnerships to drive revenue, scale integrations, and enhance executive relationships leveraging AI tools.

The Engineering Manager for Forecasting and Scheduling will lead a team in developing algorithms and user interfaces to optimize workforce management, combining technical direction with product decisions while collaborating with various teams.

Lead technical deployments and customer onboarding for mid-market and enterprise accounts. Manage project execution, integrate with APIs and databases, document product functionality, refine deployment best practices, and liaise with Sales, Product, and Engineering to drive activation, retention, and product improvements.

Drive operational execution through renewal processing in Salesforce, support Tier 1 ticket handling in Zendesk, maintain data accuracy, and handle other operational tasks as business needs shift.

The Product Manager will drive AI-powered workforce experiences, manage integrations, conduct customer research, and ensure data accuracy while mentoring junior PMs and championing product quality.

As a Software Engineer on the AI Products Team, you'll develop features integrating LLMs, improve AI infrastructure, enhance model performance, and engage with customers to shape user-friendly solutions.

The Software Engineer will develop forecasting interfaces, optimize scheduling for support agents, and enhance MLOps for efficient model deployment.