Job Summary
Sev1Tech is seeking an experienced AI Technical Lead to spearhead a dynamic team of Twenty (20) AI professionals in advancing secure, resilient, and integrated AI systems. This role focuses on driving secure-by-design adoption, vulnerability management for intelligent systems, cross-sector AI integration, and the development of strategic AI roadmaps. The ideal candidate will combine deep technical expertise in AI with strong leadership skills to deliver innovative solutions that enhance observability, reliability, and security across AI deployments. This position plays a critical role in ensuring our AI initiatives align with industry best practices and organizational goals, fostering a culture of innovation and proactive risk management.
Key Responsibilities
- Lead and mentor a team of 20 AI engineers, data scientists, and specialists, providing technical guidance, performance feedback, and professional development opportunities to ensure high team productivity and collaboration.
- Champion secure-by-design principles in AI development, embedding security considerations from the outset of system architecture and throughout the lifecycle.
- Develop and implement robust vulnerability management strategies for intelligent systems, including identification, assessment, mitigation, and monitoring of risks in AI models and infrastructure.
- Drive cross-sector, industry, and systems AI integration efforts, collaborating with stakeholders to ensure seamless interoperability and scalability of AI solutions across diverse environments.
- Spearhead the creation and execution of comprehensive AI roadmaps, aligning them with business objectives, emerging technologies, and regulatory requirements.
- Oversee the design and deployment of AI observability frameworks, tools, and processes to monitor model performance, detect anomalies, and maintain system integrity.
- Collaborate with cross-functional teams, including security, operations, and product management, to integrate AI best practices and deliver high-impact outcomes.
- Stay abreast of advancements in AI, machine learning, observability tools, and security trends, applying insights to enhance team capabilities and project deliverables.
- Manage project timelines, budgets, and resources to ensure on-time delivery of initiatives while maintaining quality standards.
Potential Deliverables
- AI observability reference architecture that incorporates secure-by-design principles, providing a blueprint for scalable and secure monitoring of AI systems.
- Custom dashboards and reporting mechanisms offering real-time and historical insights into model health, data drift, and AI-related logging to support proactive decision-making.
- Standard Operating Procedures (SOPs) for model retention, rollback processes, and root cause analysis to streamline operations and minimize downtime.
- Incident response procedures tailored for model failures and anomalies, including detection protocols, escalation paths, and recovery strategies.
- A comprehensive AI Roadmap outlining short- and long-term strategies, technology adoption plans, and milestones for AI maturation within the organization.
- Comparative analysis and recommendations on open-source and commercial AI observability tools, evaluating factors such as features, cost, integration ease, and security to inform procurement decisions.