About The Role :
To create and advance a foundational AI infrastructure for the Developer Platform.
This involves ensuring the development of robust systems for context, knowledge, and memory management, which are critical for enhancing AI-driven development experiences and improving agent functionality.
Success Metrics :
Increased accuracy and effectiveness of AI agents through enhanced data context and knowledge systems.
Enhanced developer productivity by providing immediate access to accurate and useful information.
What You'll Do :
- Team Leadership : Lead and mentor a small team of 4-5 AI engineers, fostering a collaborative and innovative work environment.
- Memory Systems Management : Design and manage shared memory systems, including the development of rules and best practice registries for AI agents.
- AI Documentation : Implement and oversee strategies for AI-first documentation generation, ensuring the health and discoverability of documentation.
- Code Context Infrastructure : Maintain repository and module summaries, providing comprehensive context for AI agents.
- Knowledge Graph & Data Ingestion : Vectorize engineering data and create knowledge graphs to facilitate advanced knowledge retrieval.
- Tooling and Client Development : Develop and maintain MCP servers / clients and other tools critical for enhancing the AI Developer Experience.
- Collaboration and Integration : Engage with AI Platform and AI DevEx teams to ensure seamless integration and alignment with broader organizational goals.
What You'll Need :
Educational Background : Hold a degree in Computer Science, Artificial Intelligence, Machine Learning, or a closely related field.Expertise in Large Language Models (LLMs) : Demonstrated experience with both unimodal and multimodal LLMs and agentic systems.Framework Proficiency : Skilled in using frameworks such as CrewAI, LangChain, and LangGraph to facilitate autonomous decision-making and workflow automation.Emerging AI Technology Awareness : Knowledgeable about emerging AI technologies, including agentic systems, MCP, and A2A protocol, and understanding their potential applications.Programming Skills : Proficient in writing clean, elegant, and bug-free code, particularly in languages such as Java and Go.Problem-solving Abilities : Possess exceptional analytical and problem-solving skills with a focus on delivering scalable solutions.Leadership and Mentorship : Ability to mentor junior engineers and actively contribute to team development and growth.Preferred Qualifications :
Cloud Computing Knowledge : Proficient in utilizing cloud computing infrastructure to support scalable AI / ML applications.AI / ML Framework Expertise : Experience with leading AI / ML development frameworks and tools, including TensorFlow, PyTorch, and Hugging Face, for building advanced AI solutions.AI Monitoring and Observability : Familiarity with AI monitoring and observability tools such as Langfuse, Prometheus, and Grafana, or similar platforms to ensure effective system performance and management.Vector and RAG Models : Skilled in embedding generation and retrieval using VectorDB and RAG ingestion techniques for enhancing AI data processing capabilities.(ref : hirist.tech)