Remote AI Engineer
Careerscape is recruiting a Remote AI Engineer for our client — a fast-scaling technology company based in Atlanta. This 100% remote opportunity is ideal for a builder-minded ML practitioner who thrives at turning cutting-edge AI research into real, production-ready software. If you love shipping LLM-powered products, architecting retrieval systems, and making AI agents actually work in the wild — let's talk.
Responsibilities
- Design, build, and deploy production-grade AI systems powered by large language models (LLMs) including GPT, Claude, Gemini, and open-source models like Llama and Mistral
- Develop Retrieval-Augmented Generation (RAG) pipelines using vector databases such as Pinecone, Weaviate, Chroma, or pgvector
- Build and orchestrate agentic AI workflows using frameworks like LangChain, LlamaIndex, LangGraph, or CrewAI
- Fine-tune, evaluate, and optimize foundation models using techniques including LoRA, QLoRA, RLHF, and supervised fine-tuning
- Develop robust evaluation frameworks and AI observability systems to measure model quality, hallucination rates, and production performance
- Design and implement prompt engineering strategies, including few-shot prompting, chain-of-thought reasoning, and structured output generation
- Integrate AI capabilities into existing products through APIs, SDKs, and microservices
- Collaborate with product, data science, and engineering teams to translate business requirements into scalable AI solutions
- Deploy and monitor AI workloads on AWS SageMaker, Azure ML, Google Vertex AI, or Hugging Face Inference Endpoints
- Implement MLOps best practices including model versioning, CI/CD for ML, A/B testing, and automated retraining pipelines
- Stay current with emerging AI research, open-source models, and industry best practices in generative and agentic AI
Requirements
- 3+ years of experience as an AI engineer, machine learning engineer, or applied ML researcher
- Strong proficiency in Python and modern ML libraries including PyTorch, TensorFlow, and Hugging Face Transformers
- Hands-on experience building production applications with LLMs via OpenAI, Anthropic, Google, or open-source model APIs
- Demonstrated experience building RAG systems, including document chunking, embeddings, vector search, and reranking
- Working knowledge of at least one agent framework (LangChain, LlamaIndex, LangGraph, AutoGen, or CrewAI)
- Experience with vector databases and semantic search implementations
- Familiarity with cloud AI platforms — AWS, Microsoft Azure, or Google Cloud Platform
- Understanding of MLOps tooling such as MLflow, Weights & Biases, Kubeflow, or SageMaker Pipelines
- Experience with containerization (Docker) and API frameworks (FastAPI, Flask)
- Strong grasp of software engineering fundamentals — version control, testing, code review, system design
- Relevant credentials are a plus: published ML research, open-source contributions, AWS/Azure/GCP ML certifications, or a portfolio of shipped AI projects
- Ability to work independently in a fully remote environment and communicate technical concepts to non-technical stakeholders
Benefits
- Competitive salary with bonus and equity opportunity
- Medical, dental, and vision insurance
- Flexible PTO and paid holidays
- Fully remote with flexible scheduling
- 401(k) with employer match
- Annual learning & development budget including GPU credits, conference attendance, and certifications
- Access to premium AI tools and API credits (OpenAI, Anthropic, and more)
- Home office stipend and top-tier equipment provided
- Team offsites and virtual collaboration culture
- Clear career path into Senior AI Engineer, Staff AI Engineer, AI Tech Lead, or Head of AI roles
Job Type: Full-Time | Work Type: Remote | Industry: Information Technology | Experience: Mid-Senior
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