Cyber
Deloitte Cyber helps clients navigate an increasingly complex and fast-changing threat landscape. We simplify complexity, strengthen resilience, and enable organizations to grow with confidence while proactively managing cybersecurity risk.
The Team
Deloitte’s Cyber Engineering team is building the technology foundation for the next generation of cybersecurity services. We bring together product thinking, engineering depth, and cybersecurity domain expertise to design and deploy modern platforms and AI-enabled solutions for our clients. Join us as we build future-ready capabilities with technologies shaping the future of Cybersecurity.
Position Summary
As a Cyber Forward Deployed Engineering Manager, you will operate at the intersection of client delivery, engineering execution, and solution shaping. You will lead cross-functional teams to design, build, and deploy high-quality cybersecurity and AI-enabled solutions in client environments. This role requires strong technical depth, delivery ownership, and the ability to translate ambiguous business and cybersecurity needs into scalable, production-ready solutions.
You will be expected to manage workstreams end-to-end, guide architecture and engineering decisions, mentor engineers, and engage directly with client stakeholders to drive outcomes. You will also play a key role in pursuits, prototypes, and product feedback loops that shape reusable capabilities across Deloitte’s Cyber Engineering offerings.
Must-Have Skills
Core Engineering & Architecture
- 9–15 years of hands-on experience in software engineering, including meaningful experience leading full-stack engineering teams and complex technical deliveries.
- Strong proficiency in JavaScript/TypeScript, HTML5, CSS3, and modern frontend frameworks such as React, Angular, or Next.js.
- Strong backend development experience in Node.js, Python (Django/Flask/FastAPI), or Java (Spring Boot).
- Experience designing and delivering scalable applications using relational databases (e.g., PostgreSQL, MySQL) and NoSQL technologies (e.g., MongoDB, Redis).
- Deep experience building and integrating REST APIs, microservices, event-driven services, and serverless architectures.
- Experience architecting and deploying cloud-native applications on AWS, Azure, or GCP.
- Strong familiarity with Docker, CI/CD pipelines, Git-based workflows, and engineering lifecycle tools such as Azure DevOps or GitHub.
- Ability to make sound architecture decisions, evaluate trade-offs, and enforce engineering quality, security, and maintainability standards.
AI / GenAI Capabilities
- 2+ years of hands-on experience building and deploying GenAI, LLM, or agentic AI solutions in client, enterprise, or production environments.
- Experience with at least one frontier GenAI platform such as Anthropic, Google, or OpenAI, including hands-on use of products such as Claude API, Claude Code, Gemini API, Vertex AI Agent Builder, Grounding, GPT-4o, Responses API, Assistants API, or OpenAI Agents SDK.
- Strong understanding of AI application architectures, including orchestration, grounding, prompt workflows, model integration, evaluation, security, and operationalization.
- Ability to align application design and engineering pipelines to support AI-enabled use cases in secure, scalable production settings.
Client Leadership & Delivery Ownership
- Proven ability to independently lead defined workstreams or products end-to-end with high-quality, timely delivery.
- Experience working directly with senior business and technical stakeholders to translate requirements into architecture, roadmaps, and delivered solutions.
- Strong communication skills with the ability to explain technical concepts, risks, dependencies, and trade-offs to both technical and non-technical audiences.
- Demonstrated experience leading engineers, reviewing designs and code, and driving accountability across delivery teams.
- Strong ownership mindset with a focus on client outcomes, delivery rigor, and continuous improvement.
Good-to-Have Skills
- Familiarity with cybersecurity domains such as application security, cloud security, identity, SOC engineering, detection engineering, or cyber analytics.
- Experience in product engineering or platform engineering environments.
- Experience with DevSecOps practices and secure software development lifecycle.
- Exposure to search and analytics platforms such as Elasticsearch/OpenSearch and graph databases such as Neo4j.
- Experience with Kubernetes, GitOps, infrastructure as code, and advanced cloud-native engineering patterns.
- Cloud certifications across AWS, Azure, or GCP.
- Familiarity with ML frameworks such as TensorFlow or PyTorch.
- Experience supporting proposals, technical demos, proofs of concept, or early-stage solution shaping in consulting or client-facing environments.
Work You Will Do
1. Solution Delivery & Engineering Leadership
- Lead the design, development, and deployment of high-quality cybersecurity and AI-enabled solutions aligned to client requirements, enterprise architecture, and security expectations.
- Own technical delivery across one or more workstreams, including planning, architecture, issue resolution, quality management, and execution oversight.
- Guide engineering teams through solution design, implementation, testing, deployment, and post-launch stabilization.
- Identify technical risks, delivery dependencies, and design trade-offs early, and drive mitigation plans to maintain delivery confidence.
- Establish and uphold engineering best practices across code quality, documentation, testing, observability, and security.
2. Client Engagement & Solution Shaping
- Partner with client stakeholders to define technical approaches, clarify requirements, and shape pragmatic, scalable solutions to cybersecurity challenges.
- Support pursuits and pre-sales efforts through technical storytelling, demos, prototypes, architecture inputs, and feasibility assessments.
- Influence solution direction by balancing client priorities, engineering practicality, cybersecurity requirements, and reusable platform opportunities.
- Act as a trusted technical leader who can bridge business goals and engineering execution.
3. Team Leadership & Capability Building
- Mentor and develop engineers through coaching, design reviews, and day-to-day delivery leadership.
- Promote a strong team culture centered on accountability, collaboration, learning, and engineering excellence.
- Help teams adopt delivery discipline, reusable patterns, and effective operating rhythms to improve execution quality and speed.
4. Product Feedback & Continuous Improvement
- Capture delivery insights and translate them into reusable product, platform, or engineering improvements.
- Distinguish between client-specific customization and scalable enhancements that can strengthen Deloitte’s broader Cyber Engineering capabilities.
- Enable client teams and internal teams through structured knowledge transfer, practical documentation, and durable runbooks.
Education
- Bachelor’s or Master’s degree in Computer Science, Engineering, Information Technology, or a related field.
