AI Architect

We are seeking a highly innovative and experienced Senior Engineer/Architect to lead the design and development of a cutting-edge agentic AI system for automotive applications. This role will be pivotal in building a platform capable of autonomously executing complex tasks by leveraging Large Language Models (LLMs) and integrating with diverse systems via APIs and command-line interfaces. You will be responsible for architectural decisions, tool selection, and ensuring the scalability, robustness, and security of this critical AI platform. A deep understanding of LLM capabilities, agentic AI principles, and practical experience in system integration are essential. Responsibilities: • Architecture & Design: Design and architect a scalable and robust agentic AI platform for automotive use cases, focusing on autonomous task execution and system integration. • Agent Framework Selection: Evaluate and select appropriate agentic AI frameworks (LangChain, AutoGPT, CrewAI, or similar) or AWS provided frameworks. • LLM Integration: Integrate and manage connections to various LLMs (publicly available or privately hosted), optimizing performance and cost-effectiveness. • Tool Integration: Design and implement mechanisms for seamlessly connecting the agentic AI system to external systems via REST APIs, command-line interfaces (CLI), and other protocols. This includes robust error handling and security considerations. • AWS/Open-Source Implementation: Leverage AWS services (e.g., Lambda, ECS, EC2, Step Functions, API Gateway, SQS, DynamoDB) or open-source alternatives for building and deploying the AI platform. • System Interaction Layer: Develop and maintain a reliable and secure layer for interacting with various automotive systems, including diagnostic tools, testing frameworks, and data repositories. • Prompt Engineering & Optimization: Lead efforts in prompt engineering to optimize LLM responses for specific automotive tasks. • Observability & Monitoring: Implement comprehensive monitoring, logging, and tracing capabilities for the agentic AI system. • Scalability & Reliability: Design for scalability, resilience, and high availability, anticipating future growth and increasing complexity. • Security: Implement robust security measures to protect sensitive data and prevent unauthorized access. • Tooling & Technology Evaluation: Continuously research and evaluate new tools and technologies in the AI and automation space. • Mentorship: Mentor and guide junior engineers, fostering a collaborative and innovative environment. • Documentation: Create and maintain detailed documentation of the system architecture, design, and implementation.