Technical Lead- Fullstack
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Requirements
• This role will lead the design and delivery of end-to-end systems—from user-facing applications to backend services and cloud infrastructure. You will guide engineering teams, drive architectural decisions, and ensure best practices across the full software development lifecycle. • Experience leveraging AI tools and building AI-driven solutions will be a significant advantage, especially for developing intelligent features, automation, and data-driven capabilities within products. • Bachelor’s or Master’s degree in Computer Science, Engineering, or related field. • 8–12 years of software engineering experience, with at least 3+ years in a technical leadership role. • Strong expertise in: • Python (FastAPI preferred) OR Java • ReactJS and TypeScript • REST and GraphQL API development • Asynchronous processing (Celery or similar) • AWS cloud services • Docker, Kubernetes, and containerization • Solid understanding of: • Microservices architectures • Distributed systems design • SQL and NoSQL databases • CI/CD pipelines • Experience building AI-driven applications or integrating AI capabilities into products. • Experience with event-driven systems such as Kafka, SNS/SQS. • Exposure to Domain-Driven Design (DDD) and clean architecture principles. • Knowledge of Infrastructure as Code (Terraform or CloudFormation). • Experience with performance tuning, load testing, and AWS cost optimization. • Strong leadership, mentoring, and stakeholder management abilities. • Excellent communication and documentation skills. • Analytical mindset with strong problem-solving capabilities. • Ability to operate effectively in a fast-paced, agile environment.
Responsibilities
• Technical Leadership • Lead the architecture and design of full-stack applications, including frontend interfaces, backend services, and cloud infrastructure. • Provide hands-on technical guidance to engineering teams and mentor developers across frontend and backend domains. • Define coding standards, enforce code quality, and conduct thorough code reviews. • Drive end-to-end delivery, from architecture and development to deployment and maintenance. • Backend Engineering & API Development • Architect and build backend services using Python/FastAPI (preferred) or Java (Spring Boot/Quarkus). • Design and implement scalable RESTful and GraphQL APIs with a strong focus on performance, security, and maintainability. • Build asynchronous processing pipelines and microservices using tools like Celery, RabbitMQ, Redis, or similar message brokers. • Design efficient database schemas and queries using PostgreSQL, MySQL, or NoSQL databases. • Implement caching strategies and optimise backend services for high throughput and reliability. • Frontend Development • Develop modern web applications using ReactJS and TypeScript. • Design reusable UI components and scalable frontend architecture. • Implement state management, API integrations, and responsive user interfaces. • Collaborate closely with design and product teams to deliver intuitive user experiences. • Ensure frontend applications maintain high standards of performance, accessibility, and maintainability. • Cloud & DevOps • Deploy, manage, and optimise applications on AWS (EC2, ECS/EKS, Lambda, S3, RDS, CloudWatch, IAM, etc.). • Implement CI/CD pipelines, automated testing, and environment provisioning. • Use Docker and Kubernetes for containerization and microservice orchestration. • Ensure system observability through logging, monitoring, and distributed tracing. • Architecture & System Design • Lead discussions on scalability, distributed architecture, caching strategies, and event-driven patterns. • Design full-stack solutions that balance performance, reliability, and user experience. • Drive adoption of cloud-native architectures and modern engineering practices. • Ensure adherence to security best practices and compliance standards. • AI & Intelligent Systems (Advantage) • Leverage modern AI tools and frameworks to enhance developer productivity and product capabilities. • Contribute to or lead the development of AI-powered features, such as intelligent search, conversational interfaces, recommendation systems, or automation tools. • Work with technologies such as LLMs, embeddings, semantic search, and RAG pipelines where relevant. • Evaluate opportunities to integrate AI-driven capabilities into existing products and workflows.