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THRIVE is looking for a skilled Threat AI Engineer to design, develop, and deploy AI-driven solutions for threat detection, prevention, and response. This role focuses on leveraging machine learning, AI models, and security analytics to identify cyber threats, anomalies, and attack patterns in real time.

The ideal candidate will combine expertise in AI/ML with cybersecurity to strengthen THRIVE’s threat intelligence and defense capabilities.

Key Responsibilities

• Design and develop AI/ML models for cyber threat detection and prediction

• Analyze large-scale security data such as logs, network traffic, and alerts

• Build automated threat intelligence and anomaly detection systems

• Implement AI-based solutions for malware detection, fraud detection, and intrusion prevention

• Collaborate with cybersecurity teams to enhance SOC and threat response workflows

• Continuously monitor and improve model performance and accuracy

• Identify adversarial AI risks and implement defensive strategies

• Ensure secure deployment of AI models using MLOps best practices

• Document threat models, AI pipelines, and security processes

Required Skills & Qualifications

• Bachelor’s or Master’s degree in Computer Science, AI, Cybersecurity, or a related field

• Strong knowledge of Machine Learning, Deep Learning, and data analytics

• Experience with cybersecurity concepts such as SIEM, SOC, IDS/IPS, malware analysis, and threat intelligence

• Proficiency in Python, TensorFlow, PyTorch, or similar ML frameworks

• Experience with cloud platforms (AWS, Azure, or GCP)

• Understanding of network security, endpoint security, and log analysis

• Strong problem-solving and analytical skills

Preferred Qualifications

• Experience with AI-driven security platforms or threat detection tools

• Knowledge of adversarial machine learning and AI security threats

• Familiarity with MITRE ATT&CK framework

• Certifications in cybersecurity or AI (CEH, CISSP, Security+, AI/ML certifications)

• Experience working in SOC or enterprise security environments

Why Join THRIVE?

• Work on advanced AI-powered cybersecurity solutions

• Be part of an innovative and security-focused organization

• Opportunity to solve real-world cyber threat challenges using AI

• Competitive salary, benefits, and career growth opportunities

Overview

Responsibilities

• Perform formal and comprehensive application, infrastructure and other penetration testing assessments where appropriate and required
• Provide well-written, concise, technical and non-technical reports in English
• Perform vulnerability assessments and provide findings with remediation actions
• Support with various client pre-engagement interactions, including scoping activities and proposal drafting to ensure that client needs are met
• Manage and deliver penetration testing project activities within strict deadlines
• Support the QA process to ensure high quality client reports are delivered in accordance with applicable Service Level Agreement (SLA)
• Any other appropriate job duties in line with the associated skill and experience of the post holder

Skills and experience required

• Proven industry experience in application and infrastructure penetration testing
• Deep knowledge of assessing both Windows and Linux environments, including strong knowledge of Active Directory and wireless technologies
• Ability in preparing and launching social engineering campaigns (both phishing and vishing)
• Strong understanding of OWASP, PTES and other penetration testing methodologies
• Knowledge of how modern web apps are designed, developed and deployed across different platforms
• Ability to program or script in your preferred language
• Relevant degree in Computer Science, Ethical Hacking, Engineering or other relevant subject
• Relevant security qualifications (such as OSCP, CEH, GPEN)
• Good knowledge and understanding of network and OS principles
• Good knowledge of various operating systems
• Good knowledge of virtualization

Nice to have

• Knowledge of assessing cloud and hybrid environments (AWS and Azure)
• Knowledge of assessing mobile applications (iOS/Android)
• Knowledge of assessing hardware and embedded IoT devices

Personal Attributes

• Excellent spoken and written communication skills with strong attention-to-detail and accuracy
• A passion for security and networks
• Analytical and problem-solving skills with a can-do attitude and the ability to think laterally
• Self-motivation with a commitment to continued development
• Ability to work independently and as part of a team
• Influencing and negotiation skills with the ability to build relationships at all levels
• Willingness to learn

Benefits

• 25 days annual holiday plus 8 paid public holidays
• An additional day’s annual holiday for your birthday
• Pension/401k contribution
• Subsidized gym membership
• Frequent team events
• Private Healthcare (individual cover only)
• Learning Allowance Benefit
• Flexible working policy

Company Overview

Key Responsibilities

• Define AI-driven growth and marketing strategy

• Lead AI adoption across paid media, CRM, and automation platforms

• Drive predictive modeling for customer acquisition and retention

• Partner with executive leadership on revenue growth initiatives

• Manage senior marketing and AI teams

  Skills & Qualifications

  • 10–15+ years in AI, marketing analytics, or growth leadership

  • Strong background in AI, ML, and customer data platforms

  • Experience with AI-powered ad platforms and MarTech tools

  • Proven leadership and business growth track record

  • Benefits

    • Salary up to $200K

    • Executive bonuses

    • Flexible work model

    • High-impact leadership role

We are seeking a highly experienced Senior AI Manager to lead our Data Science and AI-driven Marketing initiatives. This role requires strong leadership, advanced analytics expertise, and hands-on experience in applying AI to business growth, customer acquisition, and marketing automation.

Key Responsibilities

AI & Data Science Leadership

• Lead end-to-end AI and data science strategy across marketing and business teams

• Design and deploy machine learning models for prediction, segmentation, and personalization

• Oversee data pipelines, model training, validation, and deployment

• Translate complex data insights into business-driven decisions

• AI-Powered Marketing Strategy

  • Drive AI-based marketing solutions (customer targeting, churn prediction, recommendation systems)

  • Implement AI tools for performance marketing, lead scoring, and attribution modeling

  • Optimize campaigns using predictive analytics and real-time data insights

  • Collaborate with marketing teams to improve ROI using AI automation

  Team & Stakeholder Management

  • Manage and mentor data scientists, ML engineers, and marketing analysts

  • Collaborate with leadership, product, sales, and marketing teams

  • Present AI strategies and insights to senior stakeholders

    Required Skills & Qualifications

    Technical Skills

    • Strong expertise in Machine Learning, Deep Learning, and Statistical Modeling

    • Proficiency in Python, SQL, R, and data visualization tools

    • Experience with AI marketing platforms, CRM analytics, and automation tools

    • Hands-on experience with cloud platforms (AWS, Azure, or GCP)

    • Knowledge of GenAI, NLP, recommendation engines, and predictive analytics

    Marketing & Business Skills

    • Deep understanding of digital marketing, performance marketing, and customer analytics

    • Experience applying AI to SEO, paid ads, email automation, and customer journey optimization

    • Strong business acumen with ROI-focused decision-making

      Compensation & Benefits

      • Salary up to $200,000 annually

      • Performance-based bonuses

      • Health insurance & retirement benefits

      • Flexible work environment (Remote/Hybrid)

      • Opportunity to lead high-impact AI transformation projects

Job Description:

We are looking for a Site Reliability Engineer with a passion for astronomy and space technology to join our team. In this role, you will work closely with astronomers, astrophysicists, and data scientists to develop, deploy, and manage scalable infrastructure for astronomical data processing, observatory automation, and space research applications.

Key Responsibilities:

• Design, implement, and maintain CI/CD pipelines for astronomical software and data processing workflows.

• Manage and optimize cloud-based infrastructure (AWS, Azure, or Google Cloud) for large-scale space data storage and analysis.

• Automate deployment, scaling, and monitoring of telescope control systems, astrophysics simulations, and satellite operations.

• Collaborate with scientists and engineers to integrate DevOps best practices into astronomical research projects.

• Implement containerization and orchestration (Docker, Kubernetes) for astronomical data pipelines.

• Enhance system reliability, security, and performance for astronomical observatories and space missions.

• Develop and maintain infrastructure as code (Terraform, Ansible, or CloudFormation).

• Monitor and troubleshoot system performance and astronomical data processing jobs.

Requirements:

• Bachelor's or Master’s degree in Computer Science, Astronomy, Astrophysics, or related fields.

• 3+ years of experience in DevOps, SRE, or Cloud Engineering.

• Proficiency in Linux, Shell scripting, Python, or Golang.

• Experience with cloud services (AWS, Azure, GCP) and containerization tools (Docker, Kubernetes).

• Knowledge of big data processing (Hadoop, Spark, or Apache Airflow) for handling astronomical datasets.

• Familiarity with astronomical data formats (FITS, HDF5) and scientific computing tools.

• Passion for space exploration, astronomy, or satellite technology.

Preferred Qualifications:

• Experience working with astronomical observatories, space agencies, or research institutes.

• Understanding of radio astronomy, optical telescopes, or space mission software.

• Contributions to open-source projects related to space science or DevOps.

Benefits:

• Work on cutting-edge space and astronomy projects.

• Collaborate with leading scientists and space agencies.

• Competitive salary and flexible work environment.

• Opportunity to contribute to groundbreaking astronomical discoveries.

Key Responsibilities:

• Design, implement, and validate security measures within .NET applications.

• Perform code reviews and vulnerability assessments.

• Collaborate with development teams to integrate security into the software lifecycle.

• Develop and enforce secure coding guidelines.

• Educate developers about secure coding standards and threat awareness.

• Stay current with security threats, trends, and technologies.

An Application Security Engineer (.NET) ensures that .NET-based applications are safeguarded against security risks by implementing proactive security strategies. This role involves code review, risk assessment, and close collaboration with developers to embed security practices into each phase of development. Acting as an expert resource, they provide guidance on secure coding and emerging threats, working to protect software assets and organizational data.

Overview:

A Data Ethicist focuses on ensuring that data-driven systems, especially those involving machine learning and AI, are designed, implemented, and maintained in ways that are ethical, fair, and transparent. This role sits at the intersection of data science, philosophy, policy, and law.

Key Responsibilities:

• Analyze datasets and algorithms for bias, fairness, and representativeness.

• Design ethical frameworks for AI and data usage.

• Work with data scientists, engineers, and product teams to implement responsible AI practices.

• Develop tools and metrics to audit models for ethical risk (e.g., fairness, privacy, transparency).

• Collaborate with legal and compliance teams to ensure adherence to regulations like GDPR, CCPA, or AI-specific laws.

• Educate stakeholders on data ethics principles.

Required Skills:

• Strong foundation in data science and machine learning.

• Understanding of ethical theory, philosophy, or AI ethics.

• Experience with explainable AI (XAI) tools and fairness libraries (e.g., IBM AIF360, SHAP, LIME).

• Ability to communicate complex ideas to non-technical stakeholders.

• Familiarity with privacy-enhancing technologies (e.g., differential privacy, federated learning).