Job description

As an Engineering Manager in Deloitte Cyber’s Digital Trust & Privacy practice, you will help clients solve complex identity, access, and data protection challenges through AI-enabled engineering solutions. This role sits at the intersection of client engagement and hands-on delivery, combining domain depth with the ability to architect, build, and deploy production-grade solutions. You will lead teams, shape technical solutions during pursuits, develop reusable accelerators, and drive high-quality outcomes for clients and teams alike. Recruiting for this role ends on 12/31/2026. Work you'll do As an Engineering Manager on the Digital Trust & Privacy team, you will be responsible for: • Translating client business needs and Digital Trust & Privacy requirements into AI-enabled technical solutions aligned to target architecture and delivery objectives • Leading the hands-on design, integration, deployment, and operation of production-grade solutions, including troubleshooting and resolving technical issues within scope • Shaping technical solutions during pursuits by leading demonstrations, proofs of concept, prototypes, effort estimation, and pricing inputs • Managing client delivery by overseeing scope, timelines, quality, customer satisfaction, and continuous improvement across engagements • Building team and client capability through reusable accelerators, documentation, knowledge transfer, and engineering best practices A successful candidate would possess these skills: • Ability to work independently and collaborate as part of a team • Effective written and verbal communication skills, meticulous attention to detail and quality of work product, ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment • Ability to build and sustain professional relationships, lead projects or workstreams and meet deadlines • Ability to mentor and provide clear guidance to others The team Deloitte’s Cyber Digital Trust & Privacy practice helps organizations address identity, access, and data protection needs across Identity Governance and Administration, Web and Application Programming Interface Access Management, Privileged Access Management, Public Key Infrastructure, directories, privacy engineering, data access governance, and data discovery. The team is building AI-driven cyber services and engineering capabilities designed to help clients strengthen resilience, simplify complexity, and operate with greater confidence in a changing threat landscape. Qualifications Required: • Bachelor’s degree in Computer Science, Engineering, Information Technology, Cybersecurity, or a related field; alternatively, equivalent demonstrated experience • 7+ experience in one or more Digital Trust & Privacy domains such as Identity Governance and Administration (IGA), Web Access Management (WAM), Privileged Access Management (PAM), Public Key Infrastructure (PKI), Directories, or Data Protection • 5+ experience translating client requirements into target-state solution architectures using Representational State Transfer application programming interfaces, microservices, event-driven architectures, or serverless components • 5+ experience building and deploying production-grade solutions using one or more of the following - Python, Java, or Node.js • 2+ experience delivering solutions on Amazon Web Services, Microsoft Azure, or Google Cloud Platform, including containers, continuous integration and continuous delivery pipelines, and version control tools • 6 months to a year of experience designing or deploying generative artificial intelligence or large language model solutions in a client or production environment • Ability to travel 25-50%, on average, based on the work you do and the clients and industries/sectors you serve. • Limited immigration sponsorship may be available. Preferred: • Front-end / full-stack breadth — JavaScript/TypeScript and a modern UI framework (React / Next.js) for building demo apps and lightweight delivery tooling leveraging agentic coding tools (e.g., Claude Code, Codex, Cursor etc.) • Industry depth in a regulated vertical (financial services, healthcare, public sector) and exposure to associated compliance regimes (SOX, PCI DSS, FFIEC, HIPAA, GDPR). • Edge / fraud and bot-mitigation experience (WAF, credential-stuffing and ATO countermeasures) adjacent to CIAM. • Kubernetes, GitOps, and advanced cloud-native delivery patterns. • Search/analytics or graph platforms relevant to identity analytics (Elasticsearch/OpenSearch, Neo4j). • Familiarity with ML frameworks (PyTorch, TensorFlow) and model evaluation. • Relevant certifications — CISSP, cloud (AWS/Azure/GCP), or platform-specific IAM certifications (SailPoint, Okta, CyberArk, Saviynt • The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $155,600 to $306,800. You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance. #CyberDTP27

Requirements

Must-haves

Recruiting for this role ends on 12/31/2026.
Work you'll do
As an Engineering Manager on the Digital Trust & Privacy team, you will be responsible for:
Translating client business needs and Digital Trust & Privacy requirements into AI-enabled technical solutions aligned to target architecture and delivery objectives
Leading the hands-on design, integration, deployment, and operation of production-grade solutions, including troubleshooting and resolving technical issues within scope
Shaping technical solutions during pursuits by leading demonstrations, proofs of concept, prototypes, effort estimation, and pricing inputs
Managing client delivery by overseeing scope, timelines, quality, customer satisfaction, and continuous improvement across engagements
Building team and client capability through reusable accelerators, documentation, knowledge transfer, and engineering best practices
A successful candidate would possess these skills:
Ability to work independently and collaborate as part of a team
Effective written and verbal communication skills, meticulous attention to detail and quality of work product, ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
Ability to build and sustain professional relationships, lead projects or workstreams and meet deadlines
Ability to mentor and provide clear guidance to others
Bachelor’s degree in Computer Science, Engineering, Information Technology, Cybersecurity, or a related field; alternatively, equivalent demonstrated experience
5+ experience building and deploying production-grade solutions using one or more of the following - Python, Java, or Node.js
2+ experience delivering solutions on Amazon Web Services, Microsoft Azure, or Google Cloud Platform, including containers, continuous integration and continuous delivery pipelines, and version control tools
6 months to a year of experience designing or deploying generative artificial intelligence or large language model solutions in a client or production environment
Ability to travel 25-50%, on average, based on the work you do and the clients and industries/sectors you serve.

Nice-to-haves

Industry depth in a regulated vertical (financial services, healthcare, public sector) and exposure to associated compliance regimes (SOX, PCI DSS, FFIEC, HIPAA, GDPR).
Edge / fraud and bot-mitigation experience (WAF, credential-stuffing and ATO countermeasures) adjacent to CIAM.
Kubernetes, GitOps, and advanced cloud-native delivery patterns.
Search/analytics or graph platforms relevant to identity analytics (Elasticsearch/OpenSearch, Neo4j).
Familiarity with ML frameworks (PyTorch, TensorFlow) and model evaluation.
Relevant certifications — CISSP, cloud (AWS/Azure/GCP), or platform-specific IAM certifications (SailPoint, Okta, CyberArk, Saviynt

Application prep

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Keywords to mirror

aipythonjavanode.jsazurejavascripttypescriptreactnext.jskubernetesmlawsgcp

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