3 months ago
Responsibilities
- Design, develop, and enhance applications based on foundation models for specific business needs.
- Implement and experiment with generative AI techniques, including Retrieval-Augmented Generation and prompt engineering.
- Lead the implementation of intelligent autonomous agents and multi-agent systems.
- Utilize and contribute to AI agentic frameworks to build robust and scalable agents.
- Develop and integrate Model Context Protocol solutions for standardizing AI application data access.
- Lead the development of full-stack applications integrating generative AI models.
- Work with front-end and back-end technologies to create seamless user experiences.
- Design and implement scalable RESTful APIs and microservices for AI functionalities.
- Deploy, manage, and optimize AI/ML workloads on cloud platforms.
- Implement LLMOps/MLOps and DevOps practices for continuous integration and deployment.
- Stay updated on advancements in generative AI and related fields through research.
- Collaborate effectively with cross-functional teams including product managers and data scientists.
- Mentor junior engineers and promote a culture of technical excellence.
Requirements
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- 5+ years of software development experience with a strong focus on AI/ML.
- Proven experience in building and deploying generative AI models in production environments.
- Demonstrated expertise in designing and implementing agentic AI systems.
- Solid understanding and practical experience with Model Context Protocol for AI system integration.
- Consistent experience in full-stack application development.
- Extensive experience with cloud platforms for AI/ML deployments.
- Experience with LLMOps tools and practices.
- Excellent problem-solving, analytical, and communication skills.
- Ability to work independently and collaboratively in an agile environment.
- Advanced English proficiency.