Jobs at Ralds & Agate

Mission / Purpose of the Job

• The Security Automation Engineer role is responsible for designing, developing, and maintaining automation solutions that enhance the efficiency, accuracy, and responsiveness of the company’s Managed Security Services operations.
• The role builds scalable workflows, scripts, APIs, and automated integrations that streamline alert triage, incident response, threat intelligence, and vulnerability management.
• The position strengthens SOC operations by reducing manual workload, increasing analytical visibility, and enabling continuous security improvement across all environments.

Job Responsibilities

• Develop, maintain, and optimize scripts, pipelines, and automation frameworks for security reporting, alert processing, and incident response activities.
• Build and integrate automated dashboards that provide real-time insights into SOC performance, client security metrics, and detection trends.
• Collaborate with the Reporting/RI team to improve data aggregation, correlation, normalization, and visualization for internal and external reporting.
• Design, implement, and maintain automation scripts, APIs, and system integrations to reduce manual tasks within SOC operations.
• Integrate SIEM, EDR, WAF, threat intelligence feeds, and other security tools into unified dashboards or SOAR platforms to enhance workflow efficiency.
• Implement AI-assisted search, pattern recognition, and automated query pipelines to support proactive threat hunting initiatives.
• Develop automation workflows for vulnerability assessments, including scheduling, scanning, aggregation, correlation, and report generation.
• Support deployment, configuration, and performance monitoring of security tools, ensuring availability and optimal functionality.
• Provide documentation, SOPs, and training to SOC analysts on newly developed automation tools, dashboards, and processes.
• Contribute to incident response activities by developing automated enrichment, correlation, and response scripts that accelerate triage and containment.
• Design and build a Threat Intelligence Platform (TIP) capable of automated ingestion, parsing, tagging, and correlation of commercial and open-source threat feeds.
• Implement automated dark web monitoring, VIP exposure tracking, and alerting frameworks for security intelligence use cases.
• Integrate threat intelligence outputs into SIEM/SOAR workflows to support detection engineering and correlation logic improvements.
• Develop automation workflows for vulnerability assessments, including scheduling, scanning, aggregation, correlation, and report generation.
• Build automated querying and reporting capabilities that provide prioritized vulnerability insights to both internal teams and clients.
• Support continuous improvement of penetration testing workflows through custom scripts, APIs, and task automation where applicable.

Job Specifications: Minimum & Preferred Requirements

• Bachelor’s Degree in Computer Science, Information Security, Engineering, or a related discipline.
• Relevant certifications such as SOAR, SIEM vendor certifications, CompTIA CySA+, GSEC, or equivalent would be an added advantage.
• Additional training in threat intelligence, Python automation, or cloud security is desirable.

Work Experience:

• 4–7 years of progressive experience in security automation, SOC engineering, or cybersecurity workflow automation.
• Hands-on experience with scripting languages such as Python, Bash, or PowerShell.
• Proven ability to build and maintain automation frameworks, APIs, and data engineering workflows.
• Experience with SIEM, SOAR, EDR, WAF, TIP, vulnerability assessment tools, and cloud architecture.
• Demonstrated ability to build dashboards, data pipelines, and automated reporting systems.
• Strong understanding of SOC operations, incident response workflows, and threat intelligence lifecycle.

Competencies, Skills & Attributes:
Knowledge:

• Security automation methodologies and frameworks.
• SOC processes, including alert management, incident response, and detection engineering.
• Threat intelligence lifecycle and IOC enrichment processes.
• Vulnerability assessment tools, scanning techniques, and remediation workflows.
• Cloud and API integration principles.

Skills:

• Python scripting and automation development
• API Integration & Data Engineering
• SOAR Workflow Development
• SIEM/EDR/WAF Integration
• Dashboard Development & Analytics
• Threat Intelligence Engineering
• Vulnerability Data Automation
• Documentation & Technical Writing
• Analytical and problem-solving ability
• Attention to detail and quality assurance.

Behavioural Attributes:

• Strong analytical and technical mindset.
• Proactive with a continuous improvement orientation.
• Strong communication and collaboration skills.
• Ability to work under pressure and meet tight deadlines.
• Integrity, accountability, and reliability.
• Results-oriented with strong ownership of tasks.
• Innovative thinking with a commitment to automation excellence.

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Job Responsibilities

• Define and drive the objective and roadmap for AI software engineering in alignment with business goals.
• Design, implement, and manage software programs with a focus on AI applications and next-generation large language models.
• Lead and scale high-performing engineering teams focused on AI/ML, software development, DevOps, and MLOps.
• Ensure best practices in software engineering, including coding standards, architecture, testing, and documentation.
• Develop and deploy advanced machine learning models, including multimodal AI systems and autonomous AI agents.
• Work with massive sparse expert models and implement longer contextual memory techniques for improved AI performance.
• Implement natural language processing (NLP) advancements for enhanced user experiences.
• Build and optimize AI models for performance, scalability, and efficiency using cloud based resources.
• Implement explainable AI (XAI) practices to ensure transparency and ethical AI development.
• Develop small language models (SLMs) for edge computing and specialized applications
• Create and implement GenAI observability tools and cybersecurity solutions.
• Collaborate with cross-functional teams to integrate AI solutions into existing products
• Stay updated with emerging AI trends including any-to-any multimodal AI, edge AI, and humanoid robotics.
• Participate in data augmentation techniques to improve AI training efficiency Job

Requirements
Education / Business Degree:

• Bachelor’s Degree in Computer Science, Software Engineering, or a related field.

Work Experience:

• 7 - 10 years of relevant working experience in software engineering, AI/ML and 4+ years in senior engineering leadership roles.

Training / Certificates:

• Certified JavaScript Developer.
• Go Lang Developer Certification.
• Microsoft Certified: Azure Solutions Architect Expert.
• AWS Certified Solutions Architect – Associate/Professional.
• Dynamic Programming Algorithms Specialization.
• MongoDB Certified Developer Associate.
• Microsoft Certified: Azure AI Engineer Associate.
• DeepLearning.AI – Large Language Models with Transformers.
• Emotional Intelligence for Leaders.
• People Management Skills.
• Stakeholder Engagement & Management.
• Strategic Communication for Leaders.
• Agile Leadership Training.

Competencies, Skills & Attributes:
Knowledge:

• Knowledge of machine learning algorithms: linear/logistic regression, decision trees, random forests, SVMs, kmeans, etc.
• Knowledge of large language models (LLMs): pretraining, fine-tuning, prompt engineering.
• In-depth understanding of software architecture and system design. • Strong knowledge of RESTful API design and integration.
• Knowledge of DevOps pipelines and container security.
• Understanding of SQL and NoSQL databases: MySQL, MongoDB, Redis.
• Familiarity with ethical principles in AI: fairness, bias, accountability, transparency.
• Knowledge of AI use cases across industries (e.g., NLP chatbots, recommendation engines, fraud detection, computer vision).
• Knowledge of people management and mentoring best practices.

Skills:

• Proficiency in programming languages: Must Have C++ or JavaScript & Rust; Good to have – GoLang.
• Cloud expertise: AWS, Azure, Git and DevOps.
• Strong knowledge of Microservice Architecture, RabbitMQ, and Dynamic Programming.
• Database experience: MySQL, MongoDB, and Redis • Understanding of full-stack development and software engineering concepts.
• Commitment to fostering a culture of collaboration, accountability, and continuous learning.
• Experience with large language model development and fine-tuning.
• Knowledge of multimodal AI systems and autonomous agent development.
• Excellent communication and stakeholder management skills.
• Strategic thinker with the ability to translate business needs into technical solutions.
• Passion for AI ethics, innovation, and building technology that impacts lives.
• Proven ability to lead and mentor high performing engineering teams.
• Strong decision-making and problem-solving capabilities.
• Ability to align technical initiatives with organizational goals
• Experience managing through change and driving transformation
• Commitment to fostering a culture of collaboration, accountability, and continuous learning

Behavioural Attributes:

• Able to connect engineering initiatives to broader business goals.
• Constantly seeks new and better ways to apply AI and software to solve problems.
• Takes full responsibility for the success or failure of initiatives.
• Follows through on commitments and holds self and team to high standards.
• Open to others’ ideas, promotes team input, and fosters collective success.
• Can communicate complex technical concepts in a clear and accessible way.
• Willing to experiment, iterate, and embrace cutting-edge technologies.
• Take full responsibility for the success or failure of initiatives.
• Follows through on commitments and holds self and team to high standards.
• Follows through on commitments and holds self and team to high standards.
• Works effectively with cross-functional teams (Product, Data, Security, Business).
• Provides clear direction, mentorship, and supports team growth.
• Responds constructively to change and leads others through uncertainty.
• Open to others’ ideas, promotes team input, and fosters collective success.