Vice President of Engineering

TRC Talent Solutions

Manufacturing
San Francisco, CA, United StatesPosted July 13, 2026Ref: 21194_73661
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Job Description

The Opportunity: Building the Executive Layer at a Pivotal Inflection Point

About the Role

We are seeking a VP of Engineering to organize and lead a cross-functional backend organization spanning AI engineering, data quality and annotation, product, and software engineering. This leader will own the technical operations that support our customer-facing Forward Deployed Engineering (FDE) function, while also driving an independent engineering and product roadmap that advances the company beyond immediate customer delivery needs.


A central mandate will be to improve the remote managed software solution stack, strengthen the stability of the overall AI fleet, reduce friction in FDE led deployments, and enable continued software and AI iterations, upgrades, and updates at scale.


The successful candidate will be a senior technical leader with multiple startup experiences, ideally at Series A to Series B stage companies, and a proven track record operating at Senior Director, Head of Engineering, or VP Engineering level. They will bring the authority, judgement, and presence required to align a growing engineering organization around a clear technical vision and execution mandate.
 

Key Responsibilities

Lead and scale a cross-functional backend organization of approximately 20 people across AI engineering, data quality and annotation, product, and software engineering.


Define and communicate a compelling backend, AI, data, and platform engineering vision that aligns the broader engineering organization.


Own backend technical operations supporting the customer-facing FDE organization, partnering closely with the VP of Forward Deployment to ensure customer implementations are scalable, reliable, and repeatable.


Drive the engineering and product roadmap independently from customer-specific work, ensuring the platform evolves strategically rather than reactively.


Build operating rhythms, execution standards, and technical review mechanisms that improve quality, velocity, reliability, and accountability.


Recruit, coach, and develop senior engineering, AI, data, and product leaders, while raising the overall bar for technical decision-making and organizational performance.


Partner with executive leadership to translate company strategy into engineering priorities, resourcing plans, and measurable outcomes.


Establish strong collaboration between backend engineering, AI teams, data operations, product management, and forward deployment teams.


Ensure technical architectures and operational processes can support field deployments, edge environments, industrial use cases, and enterprise-grade reliability requirements.


Requirements

Extensive experience in senior engineering leadership roles, ideally at Senior Director, Head of Engineering, or VP Engineering level.


Multiple startup experiences, with strong preference for candidates who have operated at Series A to Series B stage companies.


Demonstrated success leading cross-functional engineering organizations of medium size, approximately 20 individuals or larger.


Proven experience leading teams that include backend software engineers, AI or ML engineers, data quality or annotation functions, and product partners.


Strong technical leadership across backend systems, data-intensive platforms, AI-enabled products, and production-grade software delivery.


Experience setting technical direction, making high-stakes architecture decisions, and bringing senior stakeholders into alignment around a clear engineering mandate.


Track record of building execution systems that balance customer delivery, platform maturity, product roadmap progress, and engineering excellence.


Ability to operate effectively in ambiguous, fast-moving startup environments with limited process and high expectations for ownership.


Preferred Experience

Experience in field fleet solutions, industrial automation, edge AI, robotics, manufacturing technology, logistics technology, or adjacent operational technology domains.


Experience supporting customer-facing deployment, solutions engineering, forward deployed engineering, or field engineering teams.


Familiarity with production AI systems, data labelling or annotation pipelines, model evaluation workflows, and real-world data quality operations.


Experience building platforms that support distributed, edge, or hybrid cloud environments.


Prior experience partnering directly with enterprise customers while maintaining a scalable product and platform strategy.


Leadership Profile

Authoritative and credible technical presence, capable of aligning senior engineers, product leaders, and executives around a shared vision.


Strategic operator who can distinguish between customer-specific urgency and long-term product or platform leverage.


Hands-on enough to challenge architecture and technical plans, while senior enough to lead through managers and senior individual contributors.


High-agency leader who brings structure, prioritization, and clarity to complex cross-functional environments.


Strong communicator who can represent engineering strategy to executive leadership, customers, and internal teams.


Talent magnet who can hire, retain, and develop exceptional engineering leaders and technical contributors.


Success in This Role Looks Like

The backend, AI, data, product, and SWE teams are operating as a cohesive engineering organization with clear ownership and execution standards.


The FDE organization is strongly supported by scalable backend systems, reliable technical operations, and repeatable deployment patterns.


The company has a clearly articulated engineering and product roadmap that progresses independently of customer-specific demands.


Engineering decision-making improves in speed, quality, and consistency through strong leadership, architecture discipline, and operational cadence.


The organization is aligned around a technical vision that supports growth in industrial, field, edge AI, and automation-oriented markets.

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