Engineering Manager - Forecasting & Scheduling

Assembled•San Francisco, CA

9d•$230,000 - $270,000

About The Position

Assembled is seeking an Engineering Manager for their Forecasting & Scheduling team. This is a full-stack product team responsible for developing algorithms and user experiences that help support organizations optimize staffing by ensuring the right people are working at the right times. The role offers significant autonomy in setting technical direction and making product decisions, requiring close collaboration with Product Management, Design, ML Engineers, and the Go-To-Market team. The Engineering Manager will also engage directly with customers to ensure the product effectively transforms their support operations. This position is crucial in advancing Assembled's vision of a hybrid AI and human collaboration model in customer support operations, particularly in reimagining Workforce Management for the AI era where AI agents and human agents coexist.

Requirements

T-shaped leadership: Broad understanding of team and company goals, with the ability to dive deep when necessary.
Strong team building skills: Ability to excite the team about the future and recruit high-quality engineers.
Ability to pitch the team's vision effectively and gain buy-in.
Accountability: Holding oneself and the team accountable for delivering value to customers quickly and effectively.
Championing technical investment: Driving initiatives for debt reduction and infrastructure modernization.
Strong product instincts: Understanding what to build, not just how to build it.
Experience deploying AI thoughtfully as a force multiplier.

Nice To Haves

Background in operations research or an adjacent quantitative field (Optimization, queueing theory, simulation, applied math, or ML with a heavy optimization bent).

Responsibilities

Set technical direction and make product decisions for the Forecasting & Scheduling team.
Partner closely with PM, design, ML engineers, and GTM teams.
Work directly with customers to understand their needs and ensure product impact.
Define the future of Workforce Management in the AI era, balancing AI agents and human agents.
Address deep technical challenges, including NP-hard constraint problems and forecasting models.
Improve the speed of schedule generation (e.g., make it 10x faster).
Lead and manage a sizable team, fostering a positive and productive work environment.
Champion technical investments, including paying down debt and modernizing infrastructure.
Make informed decisions about when to take on technical debt to move fast.
Contribute to product strategy and roadmap, potentially wearing a PM hat when needed.
Thoughtfully deploy AI as a force multiplier for the team (e.g., codegen, prototyping, research synthesis) while avoiding negative consequences.