AI Solutions Architect

Location

San Jose, CA, Sarasota, FL HQ, Kansas City Metro

Full time

Hybrid

Engineering

TENEX is an AI-native, automation-first, built-for-scale Managed Detected and Response (MDR) provider. We are a force multiplier for defenders, helping organizations enhance their cybersecurity posture through advanced threat detection, rapid response, and continuous protection. Our team is composed of industry experts with deep experience in cybersecurity, automation, and AI-driven solutions. Backed by leading investors, we are rapidly growing and seeking top talent to join our mission of revolutionizing the MDR landscape.

As a Staff AI Solutions Architect at TENEX, you will be a critical technical leader, responsible for the end-to-end design, implementation, and deployment of artificial intelligence and machine learning solutions that power our core MDR services. You will translate complex cybersecurity challenges, threat intelligence, and product vision into robust, scalable, and production-ready AI architectures. This role is a key bridge between our Data Science, Product, and Engineering teams, ensuring our AI models deliver maximum impact and operational efficiency for our security analysts and customers.

Culture is one of the most important things —check out our culture deck ex.ai to experience how we champion it, valuing the unmatched collaboration and community of in-person work while offering flexibility for the best of the best.

Location:

This role will require onsite 4 days a week in our San Jose, CA, Kansas City, MO or Sarasota, FL location.

• 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.

• 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.

• Bachelor’s or Master’s degree in Computer…