Fullstack DevOps Engineer

As a Full Stack Lead Engineer, your role will involve leading the end-to-end design and development of scalable software solutions. You will work across various full-stack layers including Backend, Frontend, APIs, integrations, and data systems. Your responsibilities will include owning and driving software release cycles, ensuring adherence to engineering best practices, coding standards, and quality benchmarks. Additionally, you will leverage AI tools for debugging, root cause analysis, automated code reviews, and drive adoption of AI-assisted development practices across teams. Key Responsibilities: - Lead end-to-end design and development of scalable software solutions - Work across full-stack layers including Backend, Frontend, APIs, integrations, and data systems - Own and drive software release cycles - Ensure adherence to engineering best practices, coding standards, and quality benchmarks - Leverage AI tools for debugging and root cause analysis - Drive adoption of AI-assisted development practices - Design systems that integrate across cloud platforms, third-party services, and legacy systems - Drive continuous improvement in engineering practices, productivity, and quality - Oversee CI/CD pipelines, release management, and deployment strategies - Ensure system scalability, performance, and reliability on cloud platforms - Work closely with DevOps teams to implement automation, monitoring, and observability - Communicate complex technical concepts clearly to both technical and non-technical stakeholders Qualifications Required: - Strong experience in at least one primary stack: .NET / Java / Node.js / Python / MERN - Proven experience across Backend development, Frontend frameworks, and Database systems - Hands-on experience with cloud platforms (AWS, Azure, or GCP) - Exposure to DevOps practices and experience working in multi-stack, distributed system environments - Practical experience using AI tools and strong understanding of AI-assisted coding, debugging, and review workflows - Proven experience in leading engineering teams and client-facing roles - Ability to balance hands-on coding with leadership responsibilities - Delivery of high-quality, scalable solutions and effective adoption of AI-augmented engineering practices - Improved team productivity and engineering quality benchmarks As a Full Stack Lead Engineer, your role will involve leading the end-to-end design and development of scalable software solutions. You will work across various full-stack layers including Backend, Frontend, APIs, integrations, and data systems. Your responsibilities will include owning and driving software release cycles, ensuring adherence to engineering best practices, coding standards, and quality benchmarks. Additionally, you will leverage AI tools for debugging, root cause analysis, automated code reviews, and drive adoption of AI-assisted development practices across teams. Key Responsibilities: - Lead end-to-end design and development of scalable software solutions - Work across full-stack layers including Backend, Frontend, APIs, integrations, and data systems - Own and drive software release cycles - Ensure adherence to engineering best practices, coding standards, and quality benchmarks - Leverage AI tools for debugging and root cause analysis - Drive adoption of AI-assisted development practices - Design systems that integrate across cloud platforms, third-party services, and legacy systems - Drive continuous improvement in engineering practices, productivity, and quality - Oversee CI/CD pipelines, release management, and deployment strategies - Ensure system scalability, performance, and reliability on cloud platforms - Work closely with DevOps teams to implement automation, monitoring, and observability - Communicate complex technical concepts clearly to both technical and non-technical stakeholders Qualifications Required: - Strong experience in at least one primary stack: .NET / Java / Node.js / Python / MERN - Proven experience across Backend development, Frontend frameworks, and Database systems - Hands-on experience with cloud platforms (AWS, Azure, or GCP) - Exposure to DevOps practices and experience working in multi-stack, distributed system environments - Practical experience using AI tools and strong understanding of AI-assisted coding, debugging, and review workflows - Proven experience in leading engineering teams and client-facing roles - Ability to balance hands-on coding with leadership responsibilities - Delivery of high-quality, scalable solutions and effective adoption of AI-augmented engineering practices - Improved team productivity and engineering quality benchmarks