Director of Engineering

SaaSAudit is hiring, with BeautifulCode managing the recruitment process. Location: Hyderabad Work Type - Onsite (Not a remote)  About SaaSAudit SaaSAudit, an AI-native compliance automation platform, is helping organizations comply with industry best practices and regulatory frameworks such as SOC2, ISO27001, CIS, NIST, PCI-DSS, GDPR, and others. Using AI frontier models and an agentic framework, it delivers automated workflows, evidence collection, control validation, remediation guidance, vendor risk management, and an audit center—all in a single platform. SaaSAudit enables organizations to complete SOC2 compliance in days instead of months, while delivering 50%+ time and cost savings. About Role We are seeking a highly motivated and hands-on Director of Engineering to lead our dynamic engineering team. The ideal candidate will have a strong command of Python for backend development, expertise in React for building intuitive user interfaces, and a solid understanding of both SQL and NoSQL databases. This role also requires someone proficient with Generative AI tools (such as GitHub Copilot, Google Gemini, OpenAI’s GPT models, etc.) to enhance productivity, improve code quality, and explore innovative solutions. You should have led teams of 5+ engineers and have end-to-end experience designing and building production GenAI applications —ideally in a product-based company. You will be instrumental in architecting, designing, developing, and deploying robust and scalable enterprise cloud applications, from concept to production. This is an excellent opportunity for someone who thrives in a fast-paced environment and is passionate about building cutting-edge technology while embracing the power of AI-assisted development. As a Director of Engineering, you will combine strong technical leadership with hands-on execution to shape our engineering culture and deliver high-impact products. Key Responsibilities Leadership & Strategy Lead, mentor, and grow engineering teams (5–15+ engineers) with a focus on ownership, technical depth, and delivery excellence Define and drive engineering strategy, architecture decisions, and long-term technical roadmap. Collaborate closely with product, design, and leadership to translate business needs into scalable technical solutions. Establish and enforce engineering best practices, code quality standards, and operational excellence frameworks. Champion a culture of AI-assisted development, rapid iteration, and continuous innovation. Own hiring, onboarding, performance management, and capability development for the engineering org.  Hands-On Technical Leadership Remain deeply hands-on in architecture, system design, critical-path coding, and reviews. Architect and build end-to-end GenAI applications (RAG, orchestration, vector search, guardrails/evals, observability). Develop high-performance backend systems using Python (Django, Flask, FastAPI). Build interactive and responsive UI experiences using React.js. Own application architecture, microservices, and cloud deployments on Google Cloud Platform (GCP). Manage data architecture across SQL (PostgreSQL, MySQL, Cloud SQL) and NoSQL (MongoDB, Redis, Firestore, Datastore) systems. Implement CI/CD pipelines, observability, security best practices, and performance optimization (especially for LLM workloads). Troubleshoot and resolve complex production issues, ensuring reliability, scalability, and uptime. Demonstrate familiarity with leading Foundation AI models such as Google Gemini, OpenAI ChatGPT, and other frontier LLMs, including best practices for integrating them into production systems. Apply knowledge of Agentic frameworks to design and build multi-step, autonomous, and workflow-driven AI systems that augment or automate business processes. Required Skills & Qualifications Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience. 6+ years of professional experience in full-stack software engineering. 2+ years leading or managing teams of 5+ engineers. Proven track record of shipping production-ready software in a fast-paced environment. Hands-on experience building production GenAI applications. Strong proficiency in Python, backend frameworks, and cloud-native architectures. Expertise in React.js, modern JavaScript (ES6+), HTML5, CSS3. Deep experience with SQL and NoSQL databases. ProLiciency with Docker, Kubernetes, GKE, and modern DevOps practices. Strong familiarity with Generative AI tools used in active development workflows. Excellent communication, leadership, and problem-solving skills. Ability to balance hands-on engineering with organizational leadership