AI Engineer

iQuasar LLC is hiring an AI Engineer for an unnamed federal client. The role develops, deploys, and evaluates AI/ML and generative AI solutions, including agentic systems and LLM-based features, in distributed and cloud environments.

Responsibilities:

• 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

Requirements:

• US Citizens Only
• Ability to Obtain Public Trust
• 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