Junior Software Engineer

We are seeking a highly skilled and versatile

Full-Stack Software Engineer / Developer

with specialized expertise in

Artificial Intelligence (AI)

and the capability to operate as a

Solution Architect . The ideal candidate will design, develop, and deploy scalable end-to-end software systems — integrating cutting-edge AI solutions — while collaborating closely with clients to deliver innovative, business-driven technology solutions. This role requires a balance of

front-end and back-end development skills , deep understanding of

AI technologies , and the strategic thinking of a

solution architect .

Qualifications Core Requirements Bachelor’s degree in Computer Science, Software Engineering, Data Science, or related field. 1–3 years of professional experience in full-stack software development. Proficiency in front-end technologies: HTML, CSS, JavaScript, and frameworks such as React.js (preferred), Vue.js, or Angular. Proven experience in back-end development using Node.js (preferred), Python, Java, Ruby, or similar languages. Strong knowledge of SQL and NoSQL databases, including schema design and query optimization. Experience in RESTful API development and integration. Strong understanding of OOP principles and modern software development practices. Hands-on experience with CI/CD pipelines, Git, and deployment to production environments. Familiarity with Agile / Scrum development methodologies.

AI & Solution Architecture Skills Experience implementing and deploying machine learning models and integrating AI into production systems. Knowledge of LLM fine-tuning, prompt engineering, and AI deployment workflows. Understanding of RAG pipelines, vector databases, and cloud-based AI architectures. Ability to design, document, and present system architectures to both technical and non-technical audiences.

Additional Qualifications Experience building LLM-based chatbots, AI automation platforms, or intelligent SaaS products. Knowledge of LangChain, Pinecone, Weaviate, or other vector database solutions. Familiarity with containerization and orchestration (Docker, Kubernetes). Certifications such as AWS Machine Learning, Google Cloud AI Engineer, or Solution Architect Professional.

Responsibilities Translate business requirements into technical system designs and end-to-end AI-driven solutions. Develop and implement AI models and integrate them into full-stack applications. Manage the entire software development lifecycle (SDLC) — from design to deployment. Provide technical support and guidance during implementation and post-deployment phases. Collaborate with cross-functional teams (data engineers, frontend developers, DevOps) to deliver complete solutions. Advise the business team on AI trends, opportunities, and strategic innovation. Design solutions with scalability, maintainability, and security in mind. Recommend appropriate technologies, architectures, and frameworks based on client needs and project goals. Serve as a technical consultant for stakeholders, presenting solutions and guiding decision-making.