Design, develop, and maintain full-stack web applications, RESTful APIs, cloud deployments, CI/CD pipelines, automated tests, and scalable infrastructure. Collaborate with product and design teams in an Agile environment, while contributing to AI-driven capabilities such as conversational AI, RAG, intelligent assistants, and data-driven insights. Apply software engineering best practices, optimize performance and security, and stay current with emerging cloud, automation, and AI technologies.
Key Responsibilities
- Design, develop, and maintain responsive, high-quality web applications across the full stack.
- Collaborate with product managers and designers to translate business requirements into technical specifications.
- Develop and integrate RESTful APIs.
- Ensure application scalability, performance optimization, and security compliance.
- Implement CI/CD pipelines and automated testing for reliable and repeatable deployments.
- Work with cloud platforms (Azure, AWS, or GCP) for hosting, monitoring, and scaling applications.
- Participate in Agile ceremonies (daily stand-ups, sprint planning, retrospectives) and contribute to continuous improvement.
- Contribute to the design and integration of AI-driven features (conversational ai, MCP, RAG, intelligent assistants, data-driven insights, etc.).
- Stay current with emerging technologies and advocate best practices in software engineering and AI adoption.
Core Technical Skills
- Frontend: React.js / Angular, TypeScript, HTML5, CSS3, Tailwind / Material UI.
- Backend: Node.js / .NET / Python (FastAPI / Django / Flask)
- Database: SQL (PostgreSQL, MySQL), NoSQL (MongoDB, Cosmos DB).
- API Development: REST, GraphQL, WebSocket.
- Cloud & DevOps: Azure / AWS / GCP, Docker, Kubernetes, GitHub Actions / Azure DevOps / Jenkins.
- Testing: Playwright, NUnit, or similar frameworks.
- Version Control: Git, GitHub / Azure DevOps Repos.
Optional / Nice-to-Have Skills
- AI & Machine Learning: Familiarity with LLMs (OpenAI, Anthropic, Mistral), LangChain, or LangGraph.
- Conversational AI: Experience with tools like Dialogflow, Botpress, or Twilio Conversations.
- Agentic AI: Exposure to autonomous agents, workflow orchestration (n8n, make, or similar), and context-aware automation.
- Data Processing: Knowledge of data pipelines, vector databases (Pinecone, Weaviate, Chroma), or embedding-based search.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field (or equivalent experience).
- Strong problem-solving and collaboration skills.
- Ability to work independently and deliver high-quality code in an Agile environment.
- Passion for continuous learning and emerging technologies, especially in AI and automation.
The Company reserves the right:
1. To convene only the best qualified candidates to participate in the selection exercise.
2. Not to make any appointment following this advertisement.
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