Head of Platform Engineering

Soni; Hazlet Township (NJ); On-site; USD 216,000 - 264,000; Full time

Job summary

Soni is seeking a senior technology leader to drive the strategy, architecture, and delivery of enterprise platform engineering capabilities. This role ensures secure, scalable, and well-governed technology delivery across the enterprise, partnering with engineering, security, risk, product, and business stakeholders.

The ideal candidate will oversee automation, governance, and engineering standards, build high-performing teams, and influence distributed organizations to adopt common platform

Qualifications

• Experience leading software/platform engineering organizations.
• Strong knowledge of cloud-native systems in production.
• Proven ability to drive strategy and governance.

Responsibilities

• Define strategy and roadmap for platform engineering.
• Partner with stakeholders to translate requirements into scalable platform solutions.
• Lead automation, governance, and operational frameworks.
• Build and retain high-performing engineering teams.
• Establish engineering standards and practices.
• Oversee reusable platform services delivery.
• Drive continuous improvement through automation and observability.
• Ensure platform meets scalability, security, compliance.
• Establish operating models, metrics, governance.
• Influence senior stakeholders across organizations.

Skills

Leadership

Strategic thinking

Cloud architecture

Education

Bachelor's or Master's in CS/Engineering/IT

Tools

AWS

Kubernetes

CI/CD pipelines

Job description

A leading enterprise organization is seeking a senior technology leader to lead the strategy, architecture, and delivery of platform engineering capabilities that enable secure, scalable, and well-governed technology delivery across the enterprise.

This leader will oversee the development of shared platform services, automation, governance capabilities, and engineering standards that improve developer productivity, operational reliability, security, and compliance. The ideal candidate combines deep technical expertise with strong organizational leadership and the ability to influence across complex, matrixed environments.

Key Responsibilities

• Define and execute the strategy and roadmap for enterprise platform engineering and control capabilities.
• Partner with engineering, architecture, security, risk, product, and business stakeholders to translate complex requirements into scalable platform solutions.
• Lead the development of automation, governance, and operational frameworks that improve efficiency and strengthen compliance.
• Build, develop, and retain high-performing engineering teams, including hiring, mentoring, coaching, and succession planning.
• Establish engineering standards and practices that promote reliability, consistency, security, scalability, and operational excellence.
• Oversee the design and delivery of reusable platform services that accelerate adoption and improve developer productivity.
• Drive continuous improvement through automation, observability, performance measurement, engineering best practices, and operational discipline.
• Ensure platform capabilities meet enterprise requirements for scalability, resilience, security, compliance, and auditability.
• Establish effective operating models, metrics, and governance processes for platform services.
• Influence senior stakeholders and align distributed engineering organizations around common technology strategies and standards.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, Business, or a related field.
• Significant experience leading software/platform engineering organizations and developing senior technical leaders.
• Strong technical expertise designing, building, and operating cloud-native and distributed systems in production environments.
• Experience leading enterprise platform initiatives such as infrastructure platforms, developer platforms, security platforms, data/AI platforms, or other shared engineering capabilities.
• Demonstrated experience defining strategy, architecture, roadmaps, and execution plans for enterprise technology platforms and governance capabilities.
• Strong understanding of enterprise security, compliance, risk management, and technology governance.
• Experience delivering APIs, workflow and orchestration platforms, policy management capabilities, or other shared engineering services.
• Strong knowledge of modern software delivery practices, including architecture governance, CI/CD, automated testing, reliability engineering, monitoring, observability, and incident management.
• Proven ability to influence senior stakeholders and align diverse teams around common technology objectives.
• Track record of delivering scalable, reusable solutions that create long-term enterprise value.

Preferred Qualifications

• Experience with modern AI/ML platforms, intelligent automation, agent-based architectures, large language model ecosystems, or AI developer enablement.
• Knowledge of AI governance practices, including responsible AI, data privacy, access controls, content safeguards, and human oversight.
• Experience operating enterprise workloads in a major public cloud environment, particularly AWS.
• Familiarity with cloud services and technologies such as container orchestration, serverless computing, API management, identity and access management, databases, monitoring, and managed AI/ML services.
• Experience designing and operating multi-tenant platforms with role-based or attribute-based access controls, policy-driven authorization, and secure environment segregation.
• Knowledge of enterprise observability, including distributed tracing, telemetry, operational analytics, service health monitoring, and technology cost transparency.
• Experience developing developer enablement capabilities such as templates, SDKs, reference architectures, self-service provisioning, and standardized engineering workflows.
• Experience working in highly regulated environments with significant security, compliance, retention, governance, and audit requirements.
• Familiarity with MLOps, AI operations, model governance, and production machine-learning lifecycle management.
• Experience integrating third-party technologies while maintaining architectural flexibility and minimizing vendor dependency.
• Demonstrated ability to operate effectively within large, global, matrixed organizations with distributed teams and competing priorities.

Compensation:

Up to $240,000 annually

Compensation is based on a range of factors that include relevant experience, knowledge, skills, other job-related qualifications