- Company Name
- TENEX.AI
- Job Title
- Head of Platform Engineering
- Job Description
-
**Job Title:** Head of Platform Engineering
**Role Summary:**
Strategic leader responsible for defining and executing the technical vision, architecture, and roadmap of a high‑performance, AI‑driven cybersecurity platform. Ensures scalability, reliability, security, and operational excellence while leading a multidisciplinary platform, data, and infrastructure engineering organization.
**Expectations:**
- Deliver a platform capable of ingesting petabytes of security data and processing billions of events daily.
- Establish and meet SLOs/SLIs, drive automation, and minimize operational toil.
- Foster a culture of engineering rigor, DevSecOps, and continuous improvement.
- Align platform strategy with product and security operations needs.
**Key Responsibilities:**
- Define platform strategy, architecture, and technology stack.
- Own and prioritize the platform engineering roadmap.
- Lead Site Reliability Engineering, on‑call rotations, and incident response.
- Implement advanced monitoring, observability, automated provisioning, and disaster recovery.
- Manage and mentor engineering managers and engineers across platform, data, and infrastructure domains.
- Standardize CI/CD, IaC, security testing, and deployment processes (DevSecOps).
- Drive adoption of cloud‑native patterns, modern data stores, and distributed computing frameworks.
- Collaborate with product management and security operations to translate requirements into scalable solutions.
**Required Skills:**
- 8+ years software/platform engineering experience; 3+ years managing multiple engineering teams or a large platform portfolio.
- Proven track record building and operating scalable, secure enterprise SaaS platforms.
- Deep expertise in SRE, microservices, containerization (Docker, Kubernetes), and cloud platforms (AWS, GCP, Azure).
- Strong knowledge of cybersecurity technologies (SIEM, EDR, Threat Intelligence) and compliance frameworks (SOC 2, ISO 27001).
- Extensive experience with real‑time data pipelines and large‑scale data architectures (Kafka, Spark, Flink).
- Hands‑on experience with AI/ML infrastructure, MLOps, vector databases, and feature stores.
**Required Education & Certifications:**
- Bachelor’s degree in Computer Science, Engineering, or related field; Master’s degree preferred.
- Relevant certifications (e.g., AWS Certified Solutions Architect, Certified Kubernetes Administrator, CISSP, CISM) are a plus.