Cyber Forward Deployed Engineer - Consultant
- 3+ years of experience in full stack software engineering, application development, or software product delivery
- Bachelor's degree in Computer Science, Computer Engineering, Information Systems, or a technical field
- Strong proficiency in JavaScript/TypeScript, HTML5, CSS3, and modern frameworks (React, Angular, or Next.js).
- 3+ years' experience in Node.js, Python (Django/Flask), or Java (Spring Boot).
- 3+ years' Experience with relational (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g., MongoDB, Redis).
- 3+ years' Experience building and integrating REST APIs, microservices, and serverless architectures.
- 3+ years' Experience deploying applications on AWS, Azure, or GCP.
- Familiarity with Docker, CI/CD pipelines, and development lifecycle tools (e.g., Git, Azure DevOps).
- 1•+ years of hands-on experience building and deploying 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
- AI system architectures and ability to align application pipelines to support them.
- 1+ year of Client-Facing & Delivery experience
- 1+ year experience working directly with business stakeholders to translate requirements into technical solutions.
- Ability to travel 20%, on average, based on the work you do and the clients and industries/sectors you serve.
- Limited immigration sponsorship may be available.
- Familiarity with cybersecurity concepts (e.g., application security, cloud security, identity, detection engineering).
- 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).
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