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Overview
As a Senior SOC Engineer specializing in AI/ML, Backend development, and Distributed systems, you will drive innovation to strengthen our Security Operations Center capabilities. This role involves designing, deploying, and managing AI-powered automation workflows, productionizing ML/GenAI solutions, and building scalable backend services to optimize incident response and operational efficiency. You will leverage cloud-native technologies (Azure), DevOps practices, and MLOps tools to implement secure, compliant deployments, including vector search and RAG pipelines. Collaboration with cross-functional teams and mentoring junior engineers are integral to this position
Responsibilities
Responsibilities:
Skills:
As a Senior SOC Engineer specializing in AI/ML, Backend development, and Distributed systems, you will drive innovation to strengthen our Security Operations Center capabilities. This role involves designing, deploying, and managing AI-powered automation workflows, productionizing ML/GenAI solutions, and building scalable backend services to optimize incident response and operational efficiency. You will leverage cloud-native technologies (Azure), DevOps practices, and MLOps tools to implement secure, compliant deployments, including vector search and RAG pipelines. Collaboration with cross-functional teams and mentoring junior engineers are integral to this position
Responsibilities
Responsibilities:
- Automation and AI technologies Management: Develop, implement, and maintain AI-driven full-stack solutions that enhance user experiences and optimize internal workflows.
- Backend Services & API Development: Develop and operate scalable backend services and APIs for AI/ML workloads using languages such as Python, Typescript, Node.js etc.
- AI/ML Platform Evolution: Build and enhance platform components such as, feature and embeddings stores, vector search/semantic search infrastructure, evaluation dashboards, prompt/version management, and feedback loops.
- Security & Responsible AI: Implement security, data protection, and responsible AI guardrails, ensuring safe and compliant use of models and data.
- Cloud-Native & DevOps Practices: Apply best practices using, Azure and on-prem containerization, CI/CD pipelines (Azure Devops / Gitlab). Infrastructure-as-Code for scalable deployments.
- Cross-Functional Collaboration: Work closely with Product, Data Science, Data Engineering, Design, and DevOps/SRE teams to translate business problems into robust technical solutions.
- Integration and Orchestration: Integrate Automation and AI technologies with existing SOC tools and technologies, orchestrating workflows across disparate security systems for seamless response coordination.
- Performance Monitoring and Optimization: Monitor the performance of the Automation and AI technologies, identifying and addressing any issues or bottlenecks to ensure optimal functionality and reliability.
- Documentation and Training: Maintain comprehensive documentation of AI workflows, configurations, and procedures. Provide training and guidance to internal users and engineers.
Skills:
- Proven hands-on experience deploying AI/ML and Generative AI solutions in production environments, including fine-tuning, and integrating transformer-based models, as well as designing and implementing RAG pipelines and advanced semantic search systems.
- Proficiency in programming experience in Python, Typescript, and scripting for automation.
- Experience with MLOps, including CI/CD for ML workflows, model deployment, and monitoring performance and data drift.
- Expertise in one or more AI/ML frameworks and tools such as Hugging Face Transformers, Agno AI, LangChain, MLflow, vLLM, Ollama, or equivalent platforms for model deployment and orchestration.
- Experience building and managing distributed, scalable services with robust observability (metrics, logs, traces, dashboards, alerts).
- Experience with MLOps, including CI/CD for ML workflows, model deployment, and monitoring performance and data drift.
- Any certification in AI and ML technologies.
- Any certification in platform and automation is a plus.
- Bachelor’s or master’s degree in computer science, Information Technology, Cybersecurity, or related field.
- A minimum of 7 years of experience in software engineer with strong exposure in machine learning, backend development and distributed systems.
- Prior experience in a technical role within a cybersecurity domain is preferred.
Key Skills
Ranked by relevance
ai
devops
mlops
cicd
cybersecurity
typescript
python
incident response
containerization
machine learning
gitlab
mlflow
cloud
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- Posted
- Jan 06, 2026
- Type
- Full-time
- Level
- Mid-Senior
- Location
- Abu Dhabi
- Company
- CPX
Industries
Computer
Network Security
Categories
Engineering
Information Technology
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