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 Open. Claw 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 & Open. Claw Integration: Develop and maintain AI agents using tools such as Open. Claw. 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

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 & Open. Claw Experience: Experience with AI platforms like Open. Claw 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 Tensor. Flow, Py. Torch, or similar. Data Engineering: Knowledge of data pipelines, ETL processes, and working with large datasets for training AI models.