Associate Developer(Full Stack with AI)

Job Description: We are seeking a dynamic and forward-thinking Full Stack Web Developer to build and optimize scalable web applications while integrating advanced technologies like AI/ML and workflow automation. The ideal candidate will possess expertise across both front-end and back-end development and have practical experience with AI model development, automation tools like n8n, and configuring intelligent AI agents within orchestrated environments. Additionally, the candidate should have a deep understanding of integrating AI systems like OpenClaw or any Agentic AI to enhance application functionality and efficiency. Key Responsibilities: Full Stack Development: Design, develop, and deploy scalable, high-performance web applications. You will work with both front-end and back-end technologies to ensure seamless user experience and backend functionality. AI & Automation Integration: Integrate AI/ML models into the application stack. Work with tools like n8n to automate workflows, enhance process efficiencies, and integrate various applications. Agentic AI & OpenClaw Integration: Develop and maintain AI agents using tools such as OpenClaw. This includes adding new skills, configuring intelligent agents, and creating job schedules that are automatically triggered within orchestrated environments. Automation & Workflow Configuration: Configure and optimize workflow automation pipelines and integrate multiple applications into a unified, seamless system that reduces manual processes. Continuous Improvement & Optimization: Actively engage in identifying and implementing improvements to both the application architecture and the development lifecycle to enhance performance and user experience. Collaboration & Cross-Functional Work: Work closely with product managers, AI specialists, and other team members to understand requirements and deliver features that align with business goals. Testing & Quality Assurance: Conduct unit and integration tests to ensure the application is robust and functions as intended. Help establish best practices for testing, CI/CD pipelines, and automation in development workflows. Requirements Required Skills & Qualifications: Proven Experience: Minimum of 1-2 years in full-stack web development, with hands-on experience in both front-end and back-end technologies. Tech Stack: Strong proficiency in modern web development technologies such as JavaScript (React, Angular, Node.js, etc.), HTML5, CSS3, TypeScript, and server-side frameworks like Express.js, Django, or Ruby on Rails. AI & Automation Tools: Strong experience with AI/ML models and familiar with automation tools such as n8n to configure workflows and applications seamlessly. Agentic AI & OpenClaw Experience: Experience with AI platforms like OpenClaw or similar Agentic AI tools. Ability to add new skills to AI agents, integrate multiple systems, and create job schedules. Database Proficiency: Strong knowledge of relational and NoSQL databases (e.g., MongoDB, PostgreSQL, MySQL), including querying, schema design, and performance optimization. API Development: Solid experience in designing and developing RESTful and GraphQL APIs. DevOps & CI/CD: Familiarity with DevOps practices and tools like Docker, Kubernetes, Jenkins, or similar platforms to streamline deployment and automation pipelines. Version Control & Collaboration Tools: Proficient in version control using Git and collaboration tools such as Jira, Slack, and others. Problem-Solving: Strong problem-solving skills, with the ability to work on complex systems and debug challenging issues. Excellent Communication: Ability to collaborate effectively with both technical and non-technical teams. Strong written and verbal communication skills. Desired Skills (Optional but a Plus): Cloud Platforms: Experience with cloud platforms such as AWS, Azure, or Google Cloud for application deployment and scaling. Experience with Microservices: Familiarity with designing, implementing, and managing microservices architecture. AI Model Optimization: Experience in optimizing AI models and working with platforms for AI deployment like TensorFlow, PyTorch, or similar. Data Engineering: Knowledge of data pipelines, ETL processes, and working with large datasets for training AI models.