Director – Customer Engineering

Jobtailor

Holmdel Township (NJ)

On-site

USD 180,000 - 260,000

Full time

8 days ago

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Job summary

Jobtailor is seeking a senior leader to drive AI adoption and customer engagements from a technical leadership position in the US. You will guide architectures, mentor teams, and govern delivery across customer engineering while building trusted relationships with executive stakeholders.

The role emphasizes strong expertise in Generative AI, cloud-native architectures, and incident management, with a track record of delivering measurable business value in enterprise settings.

Qualifications

10+ years software engineering, Cloud, or DevOps with at least 5 years in leadership roles.
Experience leading enterprise AI, Cloud, or digital transformation initiatives.
Strong knowledge of Generative AI, Agentic AI, LLMs, RAG, and AI orchestration frameworks.
Experience leading customer engagements, incident management, and engineering governance.
Experience with AWS, modern cloud-native architectures, CI/CD and Kubernetes.
Proven ability to mentor technical leaders and drive engineering excellence.
Experience in insurance, financial services, or SaaS organizations.
Experience leading globally distributed engineering teams.
Master’s degree in computer science, Engineering, or a related field (preferred).
AWS and AI/ML certifications (preferred).

Responsibilities

Lead AI adoption and customer AI engagements delivering measurable business value.
Serve as the technical lead for customer AI engagements with architecture and delivery guidance.
Identify customer AI use cases to improve engineering productivity and operational efficiency.
Act as final US escalation point for major customer issues and production outages.
Lead incident response, coordinate cross-functional teams, drive timely resolution of critical issues.
Mentor Delivery Leads and engineering teams on AI technologies and best practices.
Establish engineering standards, best practices, and delivery governance across Customer Engineering.
Build trusted relationships with customers and executive stakeholders while ensuring delivery excellence.

Skills

AI Leadership

Generative AI

AWS Experience

Incident Mgmt

Engineering Governance

Tech Mentorship

Digital Transformation

Cloud Computing

Kubernetes

CI/CD

Education

MS in CS

Tools

AWS

Kubernetes

CI/CD

Job description

Lead AI adoption and customer AI engagements that deliver measurable business value
Serve as the technical lead for customer AI engagements, providing architecture and delivery guidance
Identify customer AI use cases that improve engineering productivity and operational efficiency
Act as the final US escalation point for major customer issues and production outages
Lead incident response, coordinate cross-functional teams, and drive timely resolution of critical issues
Mentor Delivery Leads and engineering teams on AI technologies and engineering best practices
Establish engineering standards, best practices, and delivery governance across Customer Engineering
Build trusted relationships with customers and executive stakeholders while ensuring delivery excellence

Requirements

10+ years of software engineering, Cloud, or DevOps experience with at least 5 years in leadership roles
Experience leading enterprise AI, Cloud, or digital transformation initiatives
Strong knowledge of Generative AI, Agentic AI, LLMs, RAG, and AI orchestration frameworks
Experience leading customer engagements, incident management, and engineering governance
Experience with AWS, modern cloud-native architectures, CI/CD and Kubernetes
Proven ability to mentor technical leaders and drive engineering excellence
Experience in insurance, financial services, or SaaS organizations
Experience leading globally distributed engineering teams
Master’s degree in computer science, Engineering, or a related field (preferred)
AWS and AI/ML certifications (preferred)

Core Competencies

Demonstrates expertise in leading AI adoption and customer engagements, with a strong focus on engineering productivity and operational efficiency. Proven ability to mentor teams, establish best practices, and drive incident management in complex environments.

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