Full Stack Engineering Manager

Deloitte’s Cyber Digital Trust & Privacy practice helps organizations build and sustain confidence in their digital products, platforms, services, data practices, and customer experiences. Our work brings together digital trust, online protection, privacy, AI governance, identity, data protection, cybersecurity, and regulatory compliance capabilities.

As a Full Stack Engineering Manager you will operate at the intersection of client-facing advisory, product engineering, and hands-on technical delivery. You will help clients address complex challenges across digital trust, online protection, privacy, artificial intelligence governance, and data protection by translating business and regulatory requirements into scalable, production-grade technology solutions.

Full Stack Engineering Managers work directly in client environments to architect, build, integrate, deploy, and improve solutions. Depending on the engagement, you may develop trust and safety capabilities, implement product compliance controls, operationalize privacy-by-design practices, build governance for generative or agentic AI, or deploy data protection and cryptographic solutions. These capabilities support Deloitte’s broader Digital Trust & Privacy mission: helping organizations build confidence in their digital products, platforms, services, data practices, and customer interactions.

This role is designed for a technically strong consultant who can move from ambiguity to implementation, collaborate with product and engineering teams, and communicate effectively with business, security, privacy, legal, and compliance stakeholders.

Recruiting for this role ends on 12/31/2026.

Work you'll do

As a Full Stack Engineer Manager on the Digital Trust & Privacy team, you will be responsible for:

• Translating client business objectives, risk requirements, and policy expectations into technical architecture, product requirements, engineering backlogs, and implementation plans
• Leading design, development, integration, deployment, testing, and troubleshooting of production-grade solutions within client environments, including artificial intelligence (AI) and generative AI (GenAI)-enabled capabilities, technical guardrails, and data protection integrations
• Building APIs, automations, workflows, integrations, dashboards, and other technical components, while embedding governance into development and deployment workflows through automated checkpoints, controls-as-code, policy enforcement, and continuous monitoring
• Prototyping and iterating rapidly with clients and internal specialists to validate approaches, shape solution direction, and support pursuits through demonstrations, proofs of concept, estimates, and pricing inputs
• Managing client delivery across scope, timelines, quality, client satisfaction, financials, and continuous improvement, while resolving implementation, integration, data, and deployment challenges
• Leading multidisciplinary teams and building reusable accelerators, documentation, knowledge transfer, and engineering best practices across engagements

The Team

Full Stack Engineering team is a multidisciplinary group that turns these capabilities into practical solutions. We work alongside client engineering, security, privacy, data, risk, compliance, product, and business teams to move from strategy & policy to implementation & measurable outcomes.

Your work may include:

• Helping digital platforms improve trust and safety and address online harms.
• Enabling product teams to meet privacy and product compliance expectations.
• Building technical governance and guardrails for generative and agentic AI.
• Protecting sensitive data across cloud, collaboration, application, and enterprise environments.
• Implementing data discovery, classification, data loss prevention (DLP), encryption, public key infrastructure (PKI), and related cryptographic capabilities.
• Developing Deloitte products and accelerators that make complex digital trust and privacy capabilities easier to deploy and operate.

The team values technical curiosity, practical problem solving, disciplined engineering, client empathy, and the ability to make complex requirements actionable.

Qualifications

Experience leading technical workstreams, multidisciplinary teams, or engineering delivery teams; managing delivery scope, timelines, quality, risks, dependencies, and client communications; coaching or mentoring other professionals; and shaping pursuits, estimates, prototypes, technical demonstrations, or solution proposals

Candidates will have experience in one or more of the following:

• Digital trust and online protection.
• Trust and safety.
• Security & Privacy.
• Product compliance.
• AI governance.
• Data protection.
• Cryptography

Required:

• 7+ years of experience building and deploying production-grade solutions using Python, Java, or Node.js,
• 7+ years of experience translating client requirements into target-state solution architectures using REST APIs, microservices, event-driven architectures, or serverless components
• 2+ years of experience delivering solutions on AWS, Microsoft Azure, or Google Cloud Platform (GCP) including containers, CI/CD pipelines, and version control tools
• 1+ years of experience designing or deploying generative artificial intelligence (AI) or large language model (LLM) solutions in a client or production environment, including experience delivering, governing, or operationalizing generative AI, LLM, or agentic AI solutions
• Bachelor’s degree in Computer Science, Engineering, Information Technology, Cybersecurity, or related.
• Ability to travel 25-50%, on average, based on the work you do and the clients and industries/sectors you serve.

Preferred Experience:

• Working with senior client stakeholders to facilitate architecture or risk decisions.
• Owning product roadmaps, technical backlogs, or reusable engineering assets.
• JavaScript or TypeScript and React or Next.js for application or demo development.
• Developing or deploying technical controls for generative AI, LLM, or agentic AI applications.
• AI use-case inventories, risk tiering, human oversight, tool access controls, prompt-injection mitigations, logging, monitoring, or controls-as-code.
• Kubernetes, GitOps, Elasticsearch, OpenSearch, Neo4j, PyTorch, or TensorFlow.
• Regulated industries such as financial services, healthcare, or public sector environments, including work aligned to Sarbanes-Oxley (SOX), Payment Card Industry Data Security Standard (PCI DSS), Federal Financial Institutions Examination Council (FFIEC), Health Insurance Portability and Accountability Act (HIPAA), or General Data Protection Regulation (GDPR).

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 build and sustain professional relationships
• Ability to lead projects or workstreams
• Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
• Strong interpersonal skills and professional demeanor
• Ability to meet deadlines
• Ability to mentor and provide clear guidance to others

Limited immigration sponsorship may be available.