Responsibilities
- Define AI Solution Architecture & Vision: Focusing on our entire security platform, setting the technical strategy, design patterns, and execution roadmap for all new and existing AI/ML features, including threat detection, risk scoring, and automation.
- Lead Technical Design & Prototyping: Creating high-level and detailed architectural designs, technical specifications, and proof-of-concepts for complex AI systems, ensuring they meet strict requirements for performance, scalability, and security.
- Drive MLOps and Deployment Excellence: Establishing best practices for model development lifecycle, CI/CD pipelines, monitoring, and automated retraining to ensure reliable, high-quality, and continuous operation of AI models in a production environment.
- Collaborate with Data Science and Engineering: Select appropriate technologies, optimize model performance, and ensure seamless integration of AI services into the existing platform architecture and customer-facing interfaces.
- Serve as a Technical Expert: Advisor to executive leadership, product managers, and customers, articulating the value, technical feasibility, and architectural trade-offs of proposed AI solutions.
- Ensure Security and Compliance: Designing AI solutions with robust data governance, privacy controls, and adherence to security best practices relevant to a regulated MSSP environment.
- Mentor and Elevate Technical Talent: Give guidance across the Engineering and Data Science teams, fostering a culture of architectural excellence, reproducible research, and deployment rigor.
Requirements
- 8+ years of progressive experience in software engineering, data science, or machine learning, with 3+ years in a dedicated Solutions Architect or equivalent senior technical role for an AI/ML product.
- Proven track record of designing, building, and deploying large-scale, enterprise-grade AI/ML systems in a production environment, preferably within a major cloud platform (AWS, Azure, or GCP).
- Deep expertise in MLOps principles, containerization (Docker, Kubernetes), model serving frameworks, and cloud-native services for data and machine learning.
- Expertise in common programming languages for data science (e.g., Python) and familiarity with big data technologies (e.g., Spark, distributed databases).
- Strong experience designing for the cybersecurity, enterprise SaaS, or B2B technology industry is required, with a focus on threat detection, security operations (SOC), and incident response workflows.
- Strong understanding of security data types (logs, network telemetry, endpoint data) and experience in how AI/ML can be applied to simplify and automate threat analysis and response.
- Knowledge of complex data architectures for high-volume, real-time data ingestion and processing.
- Exceptional communication, whiteboarding, and technical presentation skills, with a proven ability to translate highly technical concepts into clear, concise rationale for both technical and non-technical stakeholders, including executive leadership.
- Strong strategic thinking and analytical skills to resolve complex architectural trade-offs and prioritize solutions based on business value and risk reduction.
- A strong passion for applying AI to solve critical, real-world security challenges.
Nice to Have
- Relevant certifications in cloud architecture (e.g., AWS Certified Solutions Architect), MLOps, or cybersecurity are a strong plus.
Work Arrangement
Hybrid
Additional Information
- Offers reflect role location, internal equity, experience, skills, education, and certifications.
- Base salary for this position in San Jose, CA: $250,000 - $350,000.
