LLT3-Intelligent Cloud & AI Systems Engineering

1. Core Manufacturing Test Responsibilities • Ensure manufacturing test platforms continue to meet uptime and reliability requirements. • Collaborate with engineering teams on test strategies, test plans, and debug process plans for manufacturing. •Optimize manufacturing test solutions to reduce cycle time, improve test coverage, and enhance system reliability. •Perform root cause analysis of software and hardware failures occurring within the manufacturing test processes. 2. Project Management Responsibilities •Participate in project meetings to align with stakeholders and manage expectations. •Handle requirements gathering and stakeholder management to ensure efficient project execution. •Gather and incorporate continuous user feedback for iteration and improvement. •Coordinate and facilitate access to data sources for AI-driven testing improvements. 3. System Architecture (Lambda & AI Integration) •Set up RAG + LLM pipelines for data retrieval and AI-based processing. •Develop controller/orchestration logic for vector database queries, LLM calls, and result formatting. •Integrate systems with infrastructure, data ingestion pipelines, and AI architecture. 4. Cloud Infrastructure & Deployment (AWS-based) •Deploy and maintain core services (Load Balancers, EC2, Security Groups, IAM roles). •Ensure scalability & monitoring (auto-scaling, usage tracking, optimization). •Enhance security & reliability (access control, backup management, high availability setup). 5. AI/LLM Model Engineering & Optimization •Model selection: Evaluate different LLMs and determine the best fit for manufacturing applications. •Fine-tuning & adapters: Perform LoRA/Adapter/lightweight training for customization. •Model lifecycle management: Maintain version control, tracking, and evaluation metrics. 6. CoT & Prompt Engineering •Design structured prompt templates to ensure accuracy and reliability in AI responses. •Implement Chain-of-Thought (CoT) optimization to enhance LLM reasoning. •Conduct performance tuning for optimal prompt styles and output quality. 7. Data Ingestion & Proactive Alert Development •Develop automated data collection bots leveraging AI agents and Copilot frameworks. •Implement metadata & vector indexing using embedding models for structured data retrieval. •Design proactive notification systems for manufacturing anomaly detection and AI-driven ecosystem expansion.