Artificial Intelligence Specialist

Overview

Work Model:
Hybrid – 3 days onsite / 2 days remote

We are looking for a hands-on AI Architect to design, build, and deploy production-grade Generative AI systems on AWS. This role goes beyond experimentation—you will architect secure, scalable, and cost efficient GenAI solutions used by real users in enterprise environments. You will work closely with engineering, data, and product teams to deliver LLM-powered applications, including RAG-based document intelligence, chatbots, and AI assistants.

• Architect and implement Generative AI solutions using LLMs (GPT, Claude, Mixtral, etc.)
• Design and deploy Retrieval-Augmented Generation (RAG) pipelines for document Q&A and enterprise search
• Build semantic search and embedding pipelines using vector databases (FAISS, Open Search, Pinecone)
• Select and optimize LLM models, prompts, and inference strategies for accuracy, latency, and cost
• Design secure, scalable architectures on AWS (Bedrock, Sage Maker, Lambda, API Gateway, S3)
• Fine-tune models using PEFT techniques (LoRA, QLoRA) when required
• Partner with MLOps teams to product ionize models with CI/CD, monitoring, and rollback
• Optimize GenAI systems for cost, latency, and throughput
• Collaborate onsite with cross-functional teams (3 days/week in Raleigh)

• Generative AI & LLMs
• Strong understanding of LLM architectures and inference
• Hands-on experience with RAG systems in production
• Knowledge of LoRA / QLoRA / PEFT techniques
• Experience mitigating hallucinations and improving factuality

• Semantic embeddings (Sentence-BERT, OpenAI, etc.)
• Chunking strategies and metadata handling
• Vector similarity search (cosine, dot-product)
• Serverless & APIs:
  Lambda, API Gateway

• Experience with Lang Chain, Haystack, FastAPI (or similar)
• Familiarity with async processing and caching layers

• Model versioning and monitoring
• Rollback strategies and drift detection
• Performance and cost monitoring

• Experience with knowledge graphs integrated into GenAI
• Healthcare / Pharma / regulated industry experience
• Exposure to self-hosted open-source LLMs

• Bachelor’s or Master’s degree in Computer Science, AI/ML, or related field
• 7+ years in software/ML engineering, with 2+ years in GenAI/LLMs
• Proven experience deploying AI systems to productio