Responsibilities
- Design, develop, and deploy AI-powered software applications and enterprise solutions.
- Build and optimize AI Agents, Copilots, and Agentic AI workflows using modern LLM technologies.
- Develop Retrieval-Augmented Generation (RAG) systems integrated with enterprise knowledge bases.
- Integrate Large Language Models (LLMs) such as OpenAI, Anthropic Claude, Gemini, DeepSeek, Qwen, and other foundation models into business applications.
- Design scalable backend services and APIs to support AI applications.
- Integrate AI solutions with third-party systems including ERP, CRM, HRMS, databases, and cloud services.
- Build and maintain prompt engineering strategies, evaluation pipelines, and model optimization workflows.
- Collaborate with Product Managers, UI/UX Designers, and Software Engineers to deliver high-quality AI products.
- Optimize AI application performance, scalability, security, and operational costs.
- Research, evaluate, and adopt emerging AI technologies, frameworks, and best practices.
- Write clean, maintainable, and well-documented code following software engineering best practices.
- Participate in code reviews, architecture discussions, and technical planning.
Job Requirements
Must Have
- Bachelor's Degree in Computer Science, Software Engineering, Artificial Intelligence, or a related field.
- > 5 years of software development experience .
- Strong programming skills in Python, Node.js (TypeScript), or both.
- Experience building applications using REST APIs and modern backend frameworks.
- Hands-on experience with one or more LLM providers
- Experience with Prompt Engineering and LLM application development.
- Familiarity with Git and collaborative software development practices.
- Strong analytical, debugging, and problem-solving skills.
- Good communication skills and ability to work in an Agile environment.
Preferred Skills
- Experience with AI orchestration frameworks
- Experience building multi-agent AI systems.
- Experience implementing RAG architectures.
- Familiarity with vector databases.
- Experience with SQL and NoSQL databases.
- Experience deploying applications using Docker and Kubernetes.
- Experience with AWS, Azure, Google Cloud, or Tencent Cloud.
- Experience with CI/CD pipelines and DevOps practices.
- Familiarity with frontend technologies such as React or Next.js is an advantage.