Senior SOC Engineer (AI & Automation)

CPX

Responsibilities:

• Develop, implement, and maintain AI-driven full-stack solutions that enhance user experiences and optimize internal workflows.
• Develop and operate scalable backend services and APIs for AI/ML workloads using languages such as Python, Typescript, Node.js etc.
• Build and enhance platform components such as, feature and embeddings stores, vector search/semantic search infrastructure, evaluation dashboards, prompt/version management, and feedback loops.
• Implement security, data protection, and responsible AI guardrails, ensuring safe and compliant use of models and data.
• Apply best practices using, Azure and on-prem containerization, CI/CD pipelines (Azure Devops / Gitlab). Infrastructure-as-Code for scalable deployments.
• Work closely with Product, Data Science, Data Engineering, Design, and DevOps/SRE teams to translate business problems into robust technical solutions.
• Integrate Automation and AI technologies with existing SOC tools and technologies, orchestrating workflows across disparate security systems for seamless response coordination.
• Monitor the performance of the Automation and AI technologies, identifying and addressing any issues or bottlenecks to ensure optimal functionality and reliability.
• Maintain comprehensive documentation of AI workflows, configurations, and procedures. Provide training and guidance to internal users and engineers.

Qualifications:

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.

Educational Experience

• 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.