Full Stack Engineering Manager

Job Description :

- Lead and scale engineering team (hiring, mentoring, performance)

- Own end-to-end delivery (sprints, timelines, execution)

- Drive system architecture (full-stack: frontend + backend)

- Collaborate with Product & Design teams

- Ensure code quality, CI/CD, and production stability

- Manage stakeholders and balance tech vs business priorities

- Work on AI/LLM-based product enhancements

- Implement engineering best practices & processes

We are looking for an experienced Engineering Manager to lead and scale a high-performing full-stack engineering team while driving the development of cutting-edge AI/LLM-powered products. This role combines strong technical expertise, people leadership, and delivery ownership. You will be responsible for building robust, scalable systems and ensuring seamless collaboration across Product, Design, and Business teams.

Key Responsibilities :

- Build, lead, and scale a high-performing engineering team (frontend, backend, and AI engineers)

- Drive hiring, onboarding, mentoring, and career development of team members

- Set clear goals, conduct performance reviews, and foster a culture of ownership and accountability

- Promote engineering excellence, innovation, and continuous learning

- Own end-to-end delivery of product features from planning to production

- Manage sprint planning, estimations, timelines, and execution

- Ensure timely and high-quality delivery aligned with business priorities

- Identify risks, remove blockers, and drive execution efficiency

- Design and oversee scalable, secure, and high-performance full-stack architecture

- Make key technical decisions across frontend, backend, and cloud infrastructure

- Ensure system reliability, scalability, and maintainability

- Drive modernization of tech stack where required

- Guide development across frontend (React/Angular/Vue) and backend (Node.js/Java/Python/Go)

- Ensure best practices in API design, microservices, and database architecture

- Optimize application performance, responsiveness, and scalability

- Lead development and integration of AI/LLM-based features (chatbots, copilots, automation tools)

- Work with data scientists and ML engineers to deploy and scale AI models

- Evaluate and implement tools/frameworks for generative AI applications

- Ensure responsible AI practices, data privacy, and model performance monitoring

- Partner with Product Managers and Designers to define requirements and roadmap

- Translate business needs into scalable technical solutions

- Provide technical insights to influence product strategy and prioritization

- Establish and enforce coding standards, design principles, and documentation practices

- Implement CI/CD pipelines, automated testing, and release management processes

- Ensure high code quality, security, and compliance standards

- Drive DevOps culture and continuous improvement

- Communicate effectively with leadership and business stakeholders

- Balance technical trade-offs with business goals and timelines

- Provide regular updates on progress, risks, and metrics

Required Skills & Qualifications :

- Strong experience in full-stack development (frontend + backend)

- Proficiency in one or more backend languages: Node.js / Java / Python / Go

- Experience with modern frontend frameworks (React, Angular, or Vue)

- Solid understanding of system design, distributed systems, and microservices

- Experience with cloud platforms (AWS / GCP / Azure)

- Hands-on experience with CI/CD, DevOps, and containerization (Docker, Kubernetes)

- Exposure to AI/LLM frameworks (OpenAI, LangChain, Hugging Face, etc.)

- Experience building or integrating AI-powered applications

- Understanding of model deployment, evaluation, and monitoring

- Proven experience managing and scaling engineering teams

- Strong mentoring and coaching abilities

- Ability to drive execution in fast-paced environments

- Excellent communication and stakeholder management

- Strong problem-solving and decision-making abilities

- Ability to balance technical depth with business impact

- Experience in building SaaS or platform-based products

- Prior experience in startups or high-growth environments

- Familiarity with data engineering and analytics pipelines

- Exposure to security, compliance, and privacy standards

- On-time and high-quality delivery of product releases

- Team productivity, engagement, and retention

- System performance, uptime, and scalability

- Adoption and impact of AI-driven features

- Improvement in engineering processes and efficiency