Head of Platform Engineering, Control Services

Soni Resources

Information Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's or Master's in Computer Science, Engineering, IT, Business, or related field.
  • Significant leadership experience in software/platform engineering.
  • Strong expertise in cloud-native and distributed systems.
  • Experience with enterprise platform initiatives and shared engineering capabilities.
  • Demonstrated strategic and architectural planning for technology platforms.
  • Solid knowledge of enterprise security, compliance, and risk management.
  • Proficiency in modern software delivery practices, including CI/CD and reliability engineering.

Responsibilities

  • Define and execute the enterprise platform engineering strategy.
  • Collaborate with stakeholders to deliver scalable platform solutions.
  • Lead development of automation and governance frameworks.
  • Build and nurture high-performing engineering teams.
  • Establish engineering standards for reliability and scalability.
  • Oversee design and delivery of reusable platform services.
  • Drive continuous improvement in engineering practices.

Benefits

  • Comprehensive health insurance packages.
  • Generous paid time off policies.
  • Continuous professional development opportunities.
  • Flexible work arrangements, including remote work options.
Full Job Description
Head of Platform Engineering

Position Overview

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.

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