This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description The Senior Firewall Engineer will serve as a technical lead on our Cybersecurity and Infrastructure team. In this role, you will be a key member of our Infrastructure and SOC team, helping to support security teams with incident resolution, maintain security tools, and operate as a technical lead. - Perform routine system maintenance, apply policy updates, and troubleshoot customer-reported issues related to firewall or VPN functionality. - Support teams with scan configuration and troubleshooting, ensuring systems are updated with the latest code versions, and coordinate with the vendor to address any technical issues. - Full lifecycle maintenance of the server, provisioning and troubleshooting RSA tokens, and ensuring that all users who require RSA access can authenticate securely and without interruption. - Assist security teams with issue resolution, perform routine maintenance, and ensure the tool remains fully operational and aligned with program security requirements. Qualifications - Bachelor's degree and 9 years of experience, or an additional 4 years of experience in lieu of a degree. - Prior experience supporting Palo Alto Firewalls and PRISMA VPN. - Experience with NESSUS Scanners and NESSUS Agent Manager. - Experience with RSA Authentication Manager. - At least 3 years of experience with Palo Alto. Company Description

At Ford Motor Company, we believe freedom of movement drives human progress. We also believe in providing you with the freedom to define and realize your dreams. With our incredible plans for the future of mobility, we have a wide variety of opportunities for you to accelerate your career potential as you help us define tomorrow’s transportation. The future of smart mobility hinges on the intelligent application of data, metrics, and analytics. As part of our Global Data Insight & Analytics (GDI&A) team, you'll play a pivotal role. We serve as Ford's trusted advisers, providing clear insights into business conditions, customer needs, and the competitive environment. Our work empowers key decision-makers to act decisively and positively. By leveraging your expertise in data and analytics, you can contribute to timely, evidence-based decision-making. Ford's GDI&A department is on the hunt for talented individuals skilled in Machine Learning, Big Data, Statistics, Econometrics, and Optimization. Our mission is to foster evidence-based decisions by unlocking insights from data. Our projects span various domains, including Connected Vehicle, Smart Mobility, Operations, Manufacturing, Supply Chain, Logistics, and Warranty Analytics. We're looking for exceptional Machine Learning and AI scientists who are eager to engage in all project stages, from problem identification to model deployment. Ideal candidates are self-motivated, have a strong sense of initiative, and a lifelong passion for learning to navigate the rapidly evolving field of mobility technology. We offer the freedom to conduct original research, select the most suitable methodologies, and tackle world-class machine learning challenges. This role involves applying AI and ML to innovate in areas such as autonomous vehicles, cybersecurity, customer interaction, and product design. You'll be part of a forward-thinking team dedicated to using AI and ML to create groundbreaking solutions and shape our strategic direction in these fields and beyond.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description This role involves supporting the development of next-generation AI capabilities within a cybersecurity technology platform. - Contribute to the design and implementation of advanced AI systems capable of interpreting large volumes of security data. - Focus on building production-ready AI infrastructure that can scale with the platform's evolving capabilities. What You'll Be Building - Advanced NLP Systems: Develop natural language processing models capable of extracting structured insight from unstructured documents, threat intelligence feeds, and security reports. - LLM / Retrieval Systems: Build retrieval-augmented intelligence systems that generate contextual security insights and assist with automated risk analysis. - Knowledge Graph Architecture: Design dynamic knowledge graph structures that map relationships among assets, vulnerabilities, and regulatory frameworks. - Real-Time AI Pipelines: Develop scalable ML pipelines that process security data streams and deliver actionable insights. Key Responsibilities - AI Architecture & Engineering: - Designing and deploying production-grade NLP models for security intelligence analysis. - Developing knowledge graph systems connecting assets, vulnerabilities, and compliance frameworks. - Building LLM-based intelligence capabilities to support automated cyber risk insights. - Technical Delivery: - Implementing robust MLOps pipelines to support model lifecycle management. - Optimising model performance for real-time or near-real-time security analysis. - Collaborating with domain specialists to translate cybersecurity concepts into machine learning models. - Strategic Contribution: - Contributing to the technical roadmap for AI capabilities within the platform. - Researching emerging AI techniques relevant to cybersecurity and risk analysis. - Supporting architecture decisions that enable long-term scalability. Qualifications - Advanced degree in Computer Science, AI/ML, Mathematics, or a related technical field. - 5+ years of experience building production AI/ML systems. - Strong expertise in NLP frameworks (e.g., spaCy, Hugging Face, OpenAI APIs). - Experience working with knowledge graph technologies (e.g., Neo4j, Neptune, or similar). - Hands-on experience with LLM/RAG architectures. - Strong programming skills in Python with frameworks such as PyTorch or TensorFlow. - Comfortable working within cloud environments (AWS, Azure, or GCP). - Experience working with cybersecurity data or threat intelligence. - Familiarity with frameworks such as NIST, ISO 27001, SOC 2, DORA, or OWASP. - Experience building ML systems within regulated industries. Engagement Structure This role is structured as a fractional technical engagement (approximately 8 hours per week) for experienced engineers interested in contributing to the technical foundation and development of an emerging cybersecurity technology platform at an early stage. Participation is aligned with the company's current growth phase and is structured around long-term strategic involvement and shared upside as the platform scales. This opportunity is well-suited to engineers who enjoy solving complex technical problems and contributing to foundational systems in emerging technology environments.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description The Elasticsearch Engineer will continuously improve and scale the Elasticsearch infrastructure that powers our high-profile, high-visibility cybersecurity and risk-management platform. You will own the Elasticsearch clusters (provisioning, upgrades, backup/restore, and troubleshooting) managed with Ansible, and you will design, evolve, and operate data-ingest pipelines plus Elastic Fleet policies and integrations using Ansible. This is a full-time, remote position. Rotation on-call hours required. What You’ll Do - Meet professional obligations with efficient work habits—hit deadlines, honor schedules, and coordinate resources/meetings effectively. - Build strong cross-functional relationships with SecOps, SRE/Platform, Dev, and Compliance. - Maintain a professional image and adhere to all company policies/procedures. - Produce clear runbooks, diagrams, and training for junior staff; lead knowledge-shares. - Participate in and contribute to collaborative engineering/design reviews. - Plan and execute zero/minimal downtime Elasticsearch cluster upgrades with rollback and validation steps. - Implement and test cluster backups/restores; regularly perform DR exercises. - Diagnose and resolve cluster issues (performance, shards, mappings, ILM, security). - Create and maintain Elasticsearch ingest pipelines parsing (Grok, processors, ECS alignment, Painless). - Create and maintain index/component templates, ILM and SLM policies. - Create and maintain Elastic Agent integrations via Ansible, adapting data to Elastic Common Schema. - Build cluster, agent, and data ingest monitoring & alerting (throughput, latency, drop/error rates) with dashboards Kibana and ElastAlert; respond to incidents. - Capacity planning and performance tuning. - Own OS configuration management for Elastic nodes using Ansible (idempotent playbooks, CI validation). - Partner with Security to improve data quality, normalization, and retention policies. - “Other duties as assigned” in support of platform reliability and data integrity. Qualifications - High School Diploma or GED equivalent, required. - Elastic Certified Engineer (ECE) or equivalent knowledge, required. - 2+ years hands-on Elasticsearch engineering in production, required. - Ansible experience for automated configuration management, required. - Extensive experience with Grok patterns and ingest pipeline parsing. - Experience with GitHub (PR workflow, code reviews, Actions/CI). - Some programming experience to be able to comprehend and troubleshoot existing PowerShell and Python scripts. Requirements - ETL/data-engineering experience outside Elastic (e.g., Kafka, Fluent Bit, Airflow). - Programming in Bash, Python, PowerShell, Ruby or Go for tooling, automation, and QA. - Security certifications (e.g., CISSP, CISM, CISA, Security+, CEH). - Exposure to Elastic security features, RBAC, TLS, PII handling. - Experience with Elastic’s tooling such as Rally. - Familiarity with ECS, ILM, SLM, Hot-Warm-Cold architectures, index and component templates, data stream and concrete index strategies. - Experience with Linux hardening, systemd, and performance tuning for Elastic nodes. - Observability practices (SLOs, error budgets), and metrics/logs/traces integration. Benefits - 100% employer-funded insurance for employee-only medical, dental, and vision coverage. - Generous employer-funded insurance for family medical, dental, and vision coverage. - 401 (k) plan with company match. - Employer-sponsored life insurance. - Paid parental leave. - 3 weeks of paid time off, accrued annually. - 8 company-paid holidays and 2 floating holidays each year. - Certification and training reimbursement program for approved learning expenses. - 100% remote position (must be located within an approved state in the United States). - On-call Rotation: 1 week on/1 week off. - Company equipment provided.