AI Engineer

We're   looking for a talented and motivated individual to join our team as a n   AI Engineer . In this role,   you'll   have the opportunity to work on   cutting-edge   projects that combine generative AI, agentic systems, machine learning (ML), Large Language Models (LLMs), and prompt engineering to drive innovation.   You'll   be responsible for   designing, developing, and deploying complex solutions in distributed and cloud environments, working with large datasets and text-based data to create innovative technical solutions.   This role is fully remote.  On an exception basis may be required to come in once a quarter for planning purposes to Washington, DC.

Build and deploy agentic AI systems capable of autonomous decision-making, tool use, and multi-step task execution   Implement end-to-end AI/ML and GenAI projects, from understanding business needs to data preparation, model development,   deployment   and monitoring   Develop LLM-based features such as retrieval-augmented generation (RAG) with citations, text summarization, and embedding pipelines   Design and   optimize   prompts using prompt engineering techniques for LLMs to achieve desired outcomes   Work with Large Language Models (LLMs) such as Claude, GPT, Gemini, Llama, etc. via APIs or cloud AI platforms to develop solutions for specific tasks   Evaluate and test GenAI features: building test sets, grounding and citation checks, LLM-as-judge scoring, and production quality monitoring   Design, develop, and   optimize   machine learning models using Python   Deploy and manage solutions in distributed and cloud environments   Collaborate with cross-functional teams to guide business decisions   Job Requirements:   Bachelor's/ Master's   degree in CS, Data Science, Engineering, or Mathematics field   2+ years of hands-on AI/ML engineering experience, including demonstrable LLM application work   Experience building agentic AI systems (agents with tool/function calling, planning or task decomposition, and multi-step execution), or strong working knowledge of agent architectures and frameworks such as   LangGraph ,   CrewAI , Strands, or   AutoGen   Working knowledge of the modern LLM stack: prompt engineering, RAG, embeddings, and structured outputs   Experience in one or more areas of machine learning / artificial intelligence such as classification, clustering, anomaly detection, sentiment analysis, and NLP problems such as text categorization, topic modeling, entity extraction, and text summarization   Ability to think critically about AI or ML system design, including model selection, tradeoffs, and real-world deployment considerations   Experience evaluating AI/ML systems: testing, measuring accuracy, and catching hallucinations   Programming experience using Python and   iPython   notebooks; good SQL skills   Excellent communication skills to communicate with wide technical and business users   Demonstrate ability to quickly learn new tools and paradigms to deploy   cutting edge   solutions   Adept at simultaneously working on multiple projects, meeting deadlines, and managing expectations   Preferred Skills:   Experience with prompt engineering techniques such as few-shot learning, zero-shot learning, and chain-of-thought prompting   Experience with cloud platforms (AWS or Azure) and their AI/ML services such as AWS Bedrock, AWS SageMaker, Azure OpenAI, or Azure AI Foundry, and core services such as S3 and Lambda functions   Experience in using deep learning frameworks such as   PyTorch   or   Keras , etc.   Experience in   MLOps   to operationalize the model building process and monitor models in production   Familiarity with search and vector retrieval such as Elasticsearch,   Solr , or vector databases   Familiarity with version control systems, specifically Git, and experience with platforms like Azure DevOps   Familiarity with Linux and cloud CLI tools   Experience