AI Engineer

Title: AI Engineer Location: Peachtree City, GA 30269 Contract: 1+ year. Long-term. Industry: Automotive. Overview: We are seeking an experienced AI Engineer to architect, implement, and optimize advanced AI solutions, with a particular focus on Large Language Models (LLMs), agentic pipelines, workflow automation, and generative AI. You will contribute to high-impact initiatives in engineering automation, intelligent knowledge retrieval, and autonomous agent-driven workflows, leveraging the latest advancements in AI research and toolkits. Core Responsibilities: • Design and build advanced AI-driven systems utilizing LLMs (e.g., Azure OpenAI GPT Models, Claude, Llama, Mistral, Gemini, and open-source models) for tasks such as text understanding, generation, summarization, and contextual reasoning within engineering workflows. • Architect and deploy agentic pipelines (multi-agent systems, autonomous LLM agents, chain-of-thought/reasoning systems) for process automation, decision support, and engineering knowledge orchestration. • Develop and implement Advanced Retrieval-Augmented Generation (RAG) solutions combining LLMs with vector databases, search engines, and enterprise knowledge sources for high-fidelity document analysis and Q&A. • End-to-end automation of complex human-in-the-loop processes by chaining LLMs, expert systems, and external tools using orchestration frameworks (such as LangChain, LlamaIndex, Haystack, CrewAI, etc.). • Evaluate, select, and integrate modern and emerging AI tools, APIs, and infrastructure (LLMOps, vector stores, document loaders, prompt management, agents’ frameworks, etc). • Fine-tune, deploy, and monitor LLMs on private/in-house datasets to solve unique domain challenges and maintain compliance/privacy. • Stay current with the fast-evolving AI landscape (open weights, small/efficient models, guardrails, synthetic data, evaluation techniques, multimodal models, etc.) and bring new approaches into the organization. Essential Qualifications: • Bachelor’s/Master’s/PhD in Computer Science, Artificial Intelligence, or related field. • Deep expertise in building with LLMs (commercial and open source): prompt engineering, model selection, fine-tuning, and evaluation. • Hands-on experience developing agentic pipelines and workflow automations using frameworks like LangChain, LlamaIndex, Semantic Kernel, Haystack, and orchestration of cloud/on-prem LLM endpoints. • Proven track record designing RAG systems (vector database management, chunking strategies, search optimization, retrieval pipelines—using Pinecone, Weaviate, FAISS, ChromaDB, Elastic, etc.). • Working knowledge of multi-modal AI (text/audio/image/diagram/video handling), Graph-based retrieval, knowledge graphs, and semantic search. • Strong Python skills, deep experience with modern AI/ML/NLP libraries (Transformers, • Pydantic, FastAPI, HuggingFace, Azure OpenAI, etc. • Experience integrating AI solutions into real-world engineering or enterprise applications (APIs, plugins, workflow tools, agent frameworks, MLOps/LLMOps). • Familiarity with advanced prompting, guardrails/AI safety, evaluation, and monitoring of AI systems, and leveraging synthetic data. Preferred/Bonus: • Experience optimizing for model cost, latency, reliability, and scaling in production. • Understanding of privacy, security, and compliance in LLM/AI applications (PII scrubbers, access controls, audit trails). • Experience orchestrating multi-agent/agentic workflows (CrewAI, AutoGen, OpenAgents, etc.). • Familiarity with CI/CD for AI pipelines, containerization (Docker), and cloud AI services • (Azure ML, AWS Sagemaker, GCP Vertex). General: • Strong critical thinking and research skills, enthusiastic about rapid learning and experimenting with new AI capabilities. • Excellent communication and documentation abilities. • Ability to work in fast-moving, highly collaborative environments with evolving requirements.