Deployment Lead

About the role

You will own the end-to-end execution of enterprise AI infrastructure programs from initial scoping through production stabilization. You translate ambiguous customer requirements into detailed technical and operational plans that balance innovation with delivery predictability. This role demands senior judgment in navigating cross-functional complexity to protect throughput, quality, and margin. You will serve as the primary operational lead for major accounts, interfacing directly with executive stakeholders. You guide cross-functional teams toward shared objectives by aligning engineering, product, and commercial priorities. This position requires proactive risk management and clear communication under conditions of technical ambiguity. You uphold the integrity of Labelbox data workflows while enabling large-scale AI innovation for research and enterprise customers. This role reports to the General Manager and acts as the accountable owner for program success.

Key facts

What you'll do

• Architect intake workflows for major accounts, establishing scope clarity and confirming technical viability before execution begins.
• Design detailed execution plans that synchronize data pipelines, labeling methodologies, and quality assurance checkpoints across distributed workstreams.
• Analyze delivery metrics and unit economics, adjusting staffing and schedules to satisfy performance targets.
• Lead the deployment by coordinating Forward Deployed Engineers, Technical Program Managers, and domain specialists, ensuring technical rigor and alignment with customer goals.
• Collaborate with General Managers to refine long-term account strategy, roadmap direction, and portfolio health.
• Implement cross-functional risk protocols, identifying potential issues early and orchestrating timely resolutions.
• Adapt project plans in response to shifting customer demands without compromising technical integrity or predictability.
• Uphold Labelbox platform standards, enforcing validation protocols that safeguard data and model reliability throughout the project lifecycle.
• Translate complex tradeoffs into language that satisfies customer expectations while preserving the business case.
• Direct teams across multiple time zones, synchronizing efforts to achieve unified delivery outcomes.
• Own a metrics framework that tracks throughput, quality, delivery adherence, and profitability at the program level.
• Evaluate implementation plans alongside engineering teams, identifying potential pitfalls and optimization opportunities.
• Orchestrate the alignment between data creation, labeling, and evaluation workflows to maintain consistency across the AI lifecycle.
• Drive adoption of platform capabilities, ensuring efficient use of tools that convert raw data into structured training sets.

Requirements

You bring three to five years of experience managing intricate deployments within data-focused or AI-centric settings.

You possess the expertise to evaluate implementation plans alongside engineering teams, identifying potential pitfalls and optimization opportunities.

You translate complex tradeoffs into language that satisfies customer expectations while preserving the business case.

You direct teams across multiple time zones, synchronizing efforts to achieve unified delivery outcomes.

You own a metrics framework that tracks throughput, quality, delivery adherence, and profitability at the program level.

You demonstrate comfort operating at the intersection of product delivery, economic accountability, and stakeholder communication.

You uphold rigorous validation standards that protect data integrity and model reliability in large-scale AI deployments.

You operate effectively with ambiguous requirements, converting uncertainty into concrete execution plans.

Nice to have

Direct experience with the Alignerr platform and the Labelbox ecosystem.

Working knowledge of enterprise AI development cycles in research or corporate environments.

Practical notes

Location for this role is specified as San Francisco Bay Area.

Engagement level is defined as Senior customer-facing program ownership.

Compensation details include a base of 190000 USD, target OTE of 260000 USD, equity of 42400 USD, and a bonus of 20 percent of base.

The role reports to the General Manager and involves end-to-end ownership of complex customer programs.

This listing references work with major US AI labs and applied AI research teams.

The company constructs data-centric infrastructure for leading research institutions and enterprises.

The role involves close collaboration with Forward Deployed Engineers, Technical Program Managers, and domain specialists.

You should The role requires fluency in platform standards that convert raw data into structured training sets. Enterprise AI development cycles demand disciplined validation protocols to safeguard data and model reliability. Teams design tasks, run assessments, and track performance across models and datasets. Practitioners use the platform to manage evaluation workflows and iterate on model behavior through structured feedback on real-world scenarios. This Deployment Lead opportunity is centered on program-level ownership where ambiguous requirements must be translated into concrete execution plans. Success depends on the ability to balance technical design with operational and financial discipline. Cross-functional coordination spans multiple time zones and requires clear communication under conditions of technical ambiguity. The position is senior and customer-facing, with direct accountability for protecting throughput, quality, and margin. Alignment with long-term account strategy, roadmap direction, and portfolio health is a core responsibility. Risk protocols must be implemented to identify potential issues early and orchestrate timely resolutions. Adaptation to shifting customer demands must occur without compromising technical integrity or predictability. Metrics frameworks should track throughput, quality, delivery adherence, and profitability at the program level. Labelbox constructs foundational systems that enable large-scale AI innovation for research institutions and enterprises. Since 2018, the company has developed data-centric infrastructure to support this evolution. The integrated offerings include the Enterprise Platform and Tools, the Frontier Data Labeling Service delivered through Alignerr with subject matter experts, and the Expert Marketplace for specialized talent. These elements define the context in which Deployment Leads operate. The role is based in the San Francisco Bay Area and involves senior engagement with complex customer programs.