Risk Consulting - Digital Risk; Cloud, AI Platforms - Senior Consultant - Bay Area

Other locations:
Anywhere in Region

EY’s Digital Risk practice is supporting leading Technology, Media & Telecommunications (TMT) companies as they scale cloud-native, AI-enabled, and platform-based operating models. Based in San Francisco, this role provides the opportunity to work with high-growth and global technology organizations operating on microservices architectures and AI-driven engineering environments
.

We are seeking a Senior Consultant to support risk, compliance, and control activities across modern, highly automated technology ecosystems. This role requires a strong foundation in SOX, cloud environments, and software development practices
, including exposure to AI-assisted development and product development life cycles (PDLC/SDLC).

You will work with engagement teams and client stakeholders to support the design, assessment, and implementation of scalable, audit-ready risk and compliance frameworks within complex technology environments.

As a Senior Consultant in our Digital Risk practice, you will contribute to the delivery of Digital Risk engagements, executing key activities across work streams and supporting overall engagement objectives in cloud-native environments. You will work closely with Managers and Senior Managers, as well as client stakeholders, to deliver risk and control solutions within modern technology ecosystems.

In this role, you will:

• Execute activities across cloud platforms, microservices architectures, and AI-enabled development environments
  , including risk assessments, control design, and testing
• Support engagement teams by working with client stakeholders (e.g., IT, engineering, and business teams) to deliver clear, accurate, and actionable outputs
• Perform analysis and documentation of IT controls, processes, and system environments
  , ensuring completeness and quality of deliverables
• Contribute to the design and evaluation of controls across Dev Ops, CI/CD pipelines, SDLC/PDLC processes, and distributed platforms
  , including APIs, microservices, and data environments
• Support identification and assessment of risks within AI-enabled development environments and automated engineering workflows
• Manage individual tasks and deliverables, maintaining accountability for deadlines, quality, and attention to detail

Demonstrate foundational understanding of cloud-native architectures, distributed systems, and modern engineering practices
, and apply that knowledge to support control assessments and risk analysis.

Exhibit an AI-aware mindset
, recognizing risks associated with AI-assisted development and automation within engineering workflows. Demonstrate developing architecture fluency
, with the ability to interpret system components, data flows, and dependencies.

Build credibility with engineering, Dev Ops, and data teams
, collaborating effectively within technical environments. Apply knowledge of TMT sector operating models to understand evolving risk considerations.

Communicate clearly and effectively, translating technical concepts into structured and understandable outputs for engagement teams and client stakeholders.

Operate with strong attention to detail, organization, and accountability, managing multiple priorities while contributing to high-quality deliverables.

A bachelor’s or master’s degree in business, accounting, computer science, engineering, or a related field.

A minimum of 3 years of experience in IT risk, Digital Risk, or technology consulting
, with exposure to TMT sector clients or technology environments.

Hands‑on experience or exposure to:

• Cloud platforms (e.g., AWS or similar environments)
• Microservices and distributed architectures
• Dev Ops and CI/CD pipelines

Experience supporting:

• IT general controls (ITGCs) and automated control environments
• Risk assessments, control testing, and documentation activities
• Engagements involving cloud-based or distributed technology systems

Basic understanding of how control frameworks (e.g., SOX, internal controls) apply within modern technology environments.

Exposure to data platforms and AI-enabled development environments …