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Founding CTO / Head of Engineering

💼 Full-time🗓 2026-06-25

Core

Architecting an AI-driven DevOps platform that uses Machine Learning to predict infrastructure failures, optimize cloud spend, and automate CI/CD workflows.

Role type

Founding CTO / Head of Engineering

Builds

Enterprise platform for autonomous infrastructure management

Domain

Cloud Infrastructure / DevOps / Machine Learning

Deliverable

production ML models | product features | infrastructure

Required skills

Kubernetes architecture, MLOps pipeline design, distributed systems engineering, LLM integration, Infrastructure as Code, predictive analytics, security compliance (SOC2/ISO), technical fundraising, early-stage team building

Preferred skills

Prior founder experience, high-growth startup background, balance of research and engineering focus

Technologies

Go, Python, Kubernetes, Terraform, Vector Databases, LangChain, Pinecone, Service Meshes (Istio)

Responsibilities

Design core architecture integrating LLMs and predictive analytics into DevOps toolchains; Develop MLOps pipelines for continuous model training and deployment; Define technical roadmap and shipping milestones; Hire and cultivate the first engineering team

Seniority

Founding, hands-on IC with strategic leadership

Rewrite
## About the Role We are building the future of autonomous infrastructure. Our mission is to eliminate the manual overhead of DevOps by using Machine Learning to predict failures, optimize cloud spend, and automate complex CI/CD workflows. As our Founding CTO, you will transition our vision from a prototype to a market-leading enterprise platform. ## Key Responsibilities - Architect the "AI for DevOps" Engineer - Design the core architecture that integrates LLMs and predictive analytics into traditional DevOps toolchains. - Build the data ingestion layer to process massive logs, metrics, and traces for real-time AI inference. - Select the foundational stack: (e.g., Go/Python, Kubernetes, Terraform, and Vector Databases). - MLOps & Product Innovation - Develop the MLOps pipeline to ensure our internal models are continuously trained, validated, and deployed securely. - Innovate on "Self-Healing" infrastructure concepts and automated root-cause analysis (RCA). - Balance "Research" (AI accuracy) with "Engineering" (System reliability). - Strategic Leadership & Fundraising - Partner with the CEO to finalize our current funding round; provide technical due diligence for investors. - Define the 12-month technical roadmap and set aggressive shipping milestones. - Lead the "Security-First" initiative, ensuring the product meets SOC2/ISO standards for enterprise adoption. - Building the "A-Team" - Hire the first 3–5 engineers (Backend, ML, and Frontend). - Cultivate a culture of extreme ownership, technical curiosity, and speed. ## Technical Requirements - DevOps Mastery: Expert-level knowledge of Kubernetes (EKS/GKE/AKS), Service Meshes (Istio), and Infrastructure as Code. - AI/ML Integration: Proven experience deploying ML models into production. Familiarity with LangChain, Pinecone, or specialized DevOps-AI frameworks. - Backend Scale: Experience building distributed systems that handle high-throughput data streams. - Founder Grit: You have either been a founder before or were an early hire at a high-growth startup. You prefer building to managing. ## The Equity & Growth Offer - 5% Equity Stake: A significant piece of the company, reflecting your role as a true partner in the venture. - Direct Influence: You own the technical vision. There are no "legacy" systems—you decide the stack. - Funding Path: Join at the inflection point as we secure the capital to scale the team and operations. ## Selection Criteria - The "Generalist" Specialist: You must be able to write the Terraform scripts yourself while simultaneously fine-tuning a transformer model. - Communication: Ability to explain complex AI-DevOps concepts to non-technical investors and high-level enterprise clients.
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