Cyber
Deloitte Cyber understands the unique challenges and opportunities businesses face in cybersecurity. Deloitte’s Cyber team helps our clients navigate the ever-changing threat landscape. We simplify complexity, and enable businesses to operate with resilience, grow with confidence, and proactively manage their security posture.
The Team:
Deloitte’s Cyber Engineering is a new team that is spearheading the buildout of Cybersecurity technology that will underpin the next generation of our Cybersecurity services. Join us as we work with technologies shaping the future of Cybersecurity to build future capabilities today.
Position Summary
As a Cyber Forward Deployed Engineer (FDE), you will work at the intersection of client engagement and hands-on engineering, embedding directly with client engagement teams to design, build, and deliver high-quality cybersecurity and AI-enabled solutions. You will support end-to-end technical delivery while contributing to solution shaping, influencing product direction, and providing appropriate support when needed for clients’ post-deployment.
Must-have skills
Core Engineering & Architecture
- 5-8+ years of hands-on experience in full stack development across frontend and backend technologies.
- Strong proficiency in JavaScript/TypeScript, HTML5, CSS3, and modern frameworks (React, Angular, or Next.js).
- Backend expertise in Node.js, Python (Django/Flask), or Java (Spring Boot).
- Experience with relational (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g., MongoDB, Redis).
- Experience building and integrating REST APIs, microservices, and serverless architectures.
- Experience deploying applications on AWS, Azure, or GCP.
- Familiarity with Docker, CI/CD pipelines, and development lifecycle tools (e.g., Git, Azure DevOps).
AI / GenAI Capabilities
- 1+ years of hands-on experience building and deploying Agentic AI/GenAI/LLM-powered solutions in client or production environments
- 1+ years of experience with one of the following Frontier Gen AI Platforms: Anthropic, Google or Open AI, including hands on experience with one of the following key platforms/products; Claude API, Claude for Enterprise, Claude Code, Gemini API, Vertex AI Agent Builder, Grounding, Google Workspace integration, GPT-4o, Assistants API, Responses API, OpenAI Agents SDK
- Understanding of AI system architectures and ability to align application pipelines to support them.
Client-Facing & Delivery Ownership
- Ability to independently own defined scope end-to-end with consistent, high-quality output.
- Experience working directly with business stakeholders to translate requirements into technical solutions.
- Strong communication skills with the ability to articulate technical concepts, risks, and trade-offs.
- Strong accountability and ownership mindset in achieving client outcomes.
Good-to-Have Skills
- Familiarity with cybersecurity domains (e.g., application security, cloud security, identity, detection engineering).
- Familiarity with product engineering environments
- Experience with DevSecOps practices and secure software development lifecycle.
- Exposure to search/analytics platforms (Elasticsearch/OpenSearch) or graph databases (Neo4j).
- Knowledge of Kubernetes, GitOps, or advanced cloud-native patterns.
- Cloud certifications (AWS, Azure, GCP).
- Basic familiarity with ML frameworks (TensorFlow, PyTorch).
Work you will do:
1. Solution Delivery & Engineering
- Translate business and cybersecurity needs into high-quality technical solutions (including AI/GenAI-enabled capabilities where applicable), and deploy them for clients in alignment with their requirements and architecture
- Identify, troubleshoot, and resolve technical issues within scope
2. Technical Pre-Sales & Solution Shaping
- Partner with stakeholders to help shape technical solutions during pursuits, including leading demos/POCs/prototypes
- Contribute to solution design, ensuring alignment between client needs and delivery feasibility.
3. Product Feedback & Continuous Improvement
- Capture and translate delivery learnings into actionable product or platform improvements, distinguishing reusable enhancements from client-specific needs.
- Enable client teams through structured knowledge transfer, clear documentation, and practical runbooks.
Education
- Bachelor’s or Master’s degree in Computer Science, Engineering, Information Technology, or a related field.
