- Company Name
- Curative AI, Inc.
- Job Title
- VP of Engineering
- Job Description
-
**Job title:** VP of Engineering
**Role Summary:**
Strategic leader responsible for building and scaling the engineering organization of an AI‑driven healthcare SaaS company. Drives the technical vision, architecture, and delivery of AI/ML products, data pipelines, and cloud infrastructure, while mentoring teams and ensuring high quality, secure, and compliant solutions.
**Expectations:**
- Translate business strategy into actionable engineering plans.
- Scale engineering teams to support rapid growth while maintaining excellence.
- Deliver production‑ready AI/ML models and data platforms that meet customer needs.
- Foster a culture of continuous improvement, innovation, and high performance.
- Represent engineering capabilities internally and externally to support sales and product strategy.
**Key Responsibilities:**
- Define and execute the engineering roadmap across Data, Software, DevOps, AI, and IT.
- Build, mentor, and lead high‑performance engineering teams; set hiring, training, and career development standards.
- Architect scalable, secure, and reliable AI systems, data pipelines, and software platforms.
- Oversee AI/ML model development lifecycle, from research to production deployment.
- Design and maintain efficient, scalable data engineering solutions that support AI workloads.
- Champion DevOps practices, CI/CD pipelines, infrastructure‑as‑code, and cloud strategy.
- Ensure IT operations, security, and compliance meet regulatory and internal standards in collaboration with the CISO.
- Collaborate cross‑functionally to capture requirements, prioritize features, and deliver market‑ready products.
- Manage engineering resources, budgets, and timelines; make strategic build‑vs‑buy decisions.
- Serve as a technical evangelist, supporting sales, marketing, and partner engagements.
**Required Skills:**
- 10+ years in engineering leadership within AI‑driven SaaS or healthcare technology.
- Deep expertise in modern software development, AI/ML frameworks, data engineering, and cloud infrastructure.
- Proven track record implementing DevOps, CI/CD, and infrastructure‑as‑code at scale.
- Experience building large‑scale data pipelines and AI model deployment pipelines.
- Strong communication, mentoring, and talent‑scaling abilities.
- Ability to translate business objectives into technical roadmaps and operational plans.
**Required Education & Certifications:**
- Master’s degree or higher in Computer Science, Engineering, Data Science, or related technical field (preferably AI/ML).
- Certifications in cloud platforms (AWS, Azure, GCP), AI/ML, or DevOps are advantageous but not mandatory.