AI Engineer (.Net Development background)

Role: AI Engineer

Location: Atlanta, GA

Experience: 10+ Years

Summary

Al Engineer designs, builds, customizes, and deploys generative Al solutions using large language models (UMS), multimodal models, and generative systems (text, image, audio, video, code). This role focuses on applying foundation models to real-world business problems through techniques such as prompt engineering fine-tuning, Retrieval-Augmented Generation (RAG), and Al orchestration.

Required Skills & Qualifications

• Required Qualifications and Experience
• 10+ years in consulting, digital transformation, data/Al, or product/solution roles.
• Hands-on experience with at least one major cloud Al stack (Azure, AWS, or Google Cloud).
• Practical exposure to LLM use cases (eg, knowledge assistants, content generation, summarization, document Q&A)
• Proficiency with Python and/or low-code Al tooling: basic SQL for data exploration.

Core Technical Skills

• Programming: .net, C#, Azure, Python (primary), JavaScript/TypeScript, familiarity with backend frameworks
• LLMS & GenAE: Prompt engineering, embeddings, fine-tuning, RAG, agents
• Al Frameworks: LangChain, Llamaindex, Semantic Kernel, Hugging Face
• APIs: REST, WebSockets, function calling, tool use patterns

Models & Platforms

• Experience with commercial and open-source LLM
• GPT-based models, Claude, LaMA, Mistral, Falcon, etc.
• Familiarity with multimodal models (text+ image/audio)

Data & Vector Technologies

• Vector databases: FAISS, Pinecone, Weaviate, Milvus, Azure Al Search
• Document ingestion, chunking, indexing, and semantic retrieval Cloud & DevOps
• Cloud platforms: Azure (preferred), AWS, or Google Cloud Platform
• Containers and deployment: Docker, Kubernetes
• CI/CD, monitoring, logging, cost optimization Evaluation & Optimization
• LLM evaluation techniques (automated and human-based) Prompt testing, A/B experiments, and response quality metrics Performance tuning, token usage optimization, caching strategies

Soft Skills

• Strong problem-solving and system-thinking abilities
• Ability to explain Al behavior, risks, and limitations to stakeholders
• Rapid learning mindset in a fast-evolving domain

Responsibilities

• Generative Al Solution Development