Vice President of Engineering

AI Engineers, Inc.
United States
6 days ago
Apply on bmarkits.com
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
2 years minimum
Compensation
$175,000.0 - $200,000.0
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Big Data Cloud Computing Cloud Engineering Databases Continuous Integration Data Infrastructure Linux Disaster Recovery Systems Development Life Cycle Release Management Software Engineering
+7 more
Web Platforms ReactJS Backend Kubernetes Information Technology Data Analytics Golang

Job description

Our client is seeking a Vice President of Engineering to lead the engineering organization responsible for a mission-critical cloud platform and the products built around it.

This is a highly visible leadership role with ownership of engineering execution, technical direction, architecture, security, infrastructure, and team development. The VP will lead an experienced, distributed engineering organization while remaining technically engaged in architecture and production systems.

Working closely with executive and product leadership, this individual will shape engineering strategy, establish investment priorities, improve delivery predictability, and guide the continued evolution of the platform.

The ideal candidate is a proven engineering leader who can operate comfortably with executives while maintaining the technical depth to engage directly with architects and senior engineers., Engineering Leadership & Team Development

  • Lead, develop, and retain an experienced engineering organization.
  • Establish clear expectations, career paths, technical standards, and accountability.
  • Hire and develop senior engineering talent and technical leaders.
  • Build a culture of shared ownership across development, code review, releases, and production operations.
  • Develop engineering managers and senior technical leaders.

Architecture & Platform Strategy

  • Own the technical direction and long-term architecture of a cloud-native platform.
  • Guide decisions around scalability, reliability, security, performance, and cost.
  • Partner with senior technical leaders on architecture and platform investments.
  • Maintain a strong focus on infrastructure and platform health.
  • Evaluate technology investments based on business value, reliability, risk, and cost.

Engineering Delivery & Execution

  • Own the engineering lifecycle from intake through release and production support.
  • Establish effective SDLC, capacity planning, forecasting, and release management practices.
  • Translate business and product priorities into realistic engineering commitments and delivery plans.
  • Improve predictability around scope, timelines, dependencies, and risk.
  • Maintain strong testing, release quality, and production support processes.
  • Align product priorities with engineering capacity and technical realities.

Security, Compliance & Infrastructure

  • Oversee technical security controls, remediation efforts, and incident response.
  • Guide cloud infrastructure strategy, reliability, disaster recovery, and cost management.
  • Ensure production systems remain secure, reliable, and scalable.
  • Partner with security and compliance stakeholders on customer and regulatory requirements., * Partner directly with executive leadership on technology strategy, investment priorities, risks, and tradeoffs.
  • Work closely with Product to evaluate technical feasibility and shape the product roadmap.
  • Communicate complex technical decisions clearly to non-technical stakeholders.
  • Participate in customer, partner, RFP/RFI, and security-review discussions as the engineering representative.
  • Balance scope, timing, resources, and technical risk to ensure commitments are achievable.

AI-Assisted Engineering

  • Advance the organization’s established AI-assisted and agentic software development practices.
  • Establish appropriate standards for quality, security, verification, and human oversight.
  • Measure the impact of AI adoption across productivity, quality, security, engineering workload, cost, and business value.
  • Determine where AI-driven automation is appropriate versus where human review remains essential., * Lead an experienced engineering organization supporting a mission-critical technology platform.
  • Partner directly with executive and product leadership to shape technology strategy and investment.
  • Influence architecture, security, infrastructure, engineering delivery, and AI adoption.
  • Work with a technically strong team in a modern cloud-native environment.
  • Help advance an established AI-assisted engineering culture.
  • Fully remote within the United States.

Requirements

Work Authorization: Candidates must be authorized to work in the U.S. without current or future employment-based visa sponsorship., * 15+ years of software engineering experience, including 5+ years leading engineering teams and 2+ years as the senior-most engineering leader for a company, business unit, or comparable organization.

  • Strong hands-on architecture experience with cloud-native backend systems.
  • Deep understanding of Linux, containerized services, CI/CD, infrastructure as code, and production reliability.
  • Proven experience building and managing an effective engineering delivery system, including SDLC, capacity planning, forecasting, and release management.
  • Experience owning security controls, remediation, and incident response within a regulated, audited, or security-sensitive production environment.
  • Practical experience using AI-assisted development tools and workflows in production.
  • Ability to work directly with executives, customers, and other senior stakeholders and clearly communicate technical tradeoffs.
  • Demonstrated success hiring, developing, and retaining senior engineers within lean or distributed organizations.
  • Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
  • Demonstrated career stability with meaningful multi-year tenures., * Experience in healthcare, life sciences, clinical research, or other regulated environments.
  • Experience with Go, Kubernetes, and cloud-native architectures.
  • Experience with both relational and document databases.
  • Experience driving organization-wide adoption of AI-assisted software development.
  • Familiarity with modern data platforms and data-intensive applications.
  • Experience with React or modern front-end architectures.
  • Experience leading engineering organizations within companies of approximately 50-300 employees.
  • Experience supporting platforms serving significant daily user volumes.
  • Background in marketing technology, digital platforms, advertising, or campaign/data-driven products.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on bmarkits.com
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

3:03 min

Career evolution in data engineering and AI platforms

Maria Apazoglou · Coffee With Developers

52 sec

Running persistent Linux environments directly on Windows

Ben Breard Ben Breard · World Congress 2025

1:08 min

Building solutions with open source GoLang infrastructure tools

Jad Wahab · LIVE

1:52 min

Structuring and scaling the backend engineering team

Stefan Lingler Stefan Lingler +1 · Coffee With Developers

2:14 min

Exploring internal AI product initiatives and global engineering roles

Maria Apazoglou · Coffee With Developers

3:55 min

Demonstrating .NET installation on Debian and Azure Linux

Silvano Coriani Silvano Coriani · Europe 2026 Virtual

Videos

See all

Related articles

See all