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.