Senior AI Engineer

Leidos•Fort Meade, MD

6d•$107,900 - $195,050

About The Position

Our program provides our customer's Operations organization with the best possible solutions for their mission needs. We achieve this through rapid prototyping, new development, and advanced technology research. From leading-edge visualizations to analytic development, we're always pushing the boundaries to find new and better data sources and tradecraft to answer intelligence questions. With a focus on collaboration and a fast-paced environment, our prototype development program is the ideal place to grow your skills and make a real impact. Seeking motivated Senior AI Engineers to support high-impact mission opportunities applying Artificial Intelligence and Machine Learning to complex data and analytic challenges. Engineers will work with mission stakeholders to translate operational needs into secure, scalable AI capabilities spanning machine learning, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), agentic AI, and advanced knowledge systems. The ideal candidate combines strong AI/ML fundamentals with hands-on engineering experience and understands how to evaluate, deploy, secure, and sustain AI capabilities throughout their lifecycle.

Requirements

Bachelor’s degree in computer science, plus 8-years of relevant experience or equivalent.
Strong proficiency with Python and demonstrated experience designing or developing AI/ML solutions.
Understanding of the complete AI lifecycle from data ingestion and model development through deployment, monitoring, and sustainment.
Active TS/SCI with Polygraph required to be considered for this role.

Nice To Haves

Knowledge of customer corporate tools, data repositories, and secure mission computing environments is highly desirable.
Experience with Large Language Models and Generative AI, including tokenization, embeddings, attention concepts, prompt engineering, context management, and LLM interfaces.
Experience developing or integrating RAG, vector search, or knowledge retrieval systems.
Understanding of machine learning and statistical fundamentals, model training and validation, performance metrics, bias/variance considerations, and experimentation.
Experience evaluating AI systems for accuracy, relevance, groundedness, hallucination, robustness, and scalability.

Responsibilities

Collaborate with mission stakeholders, analysts, data scientists, and engineers to understand operational challenges and translate requirements into effective AI/ML solutions.
Design and develop capabilities for knowledge extraction, information discovery, summarization, decision support, workflow automation, and analysis of structured and unstructured data.
Build solutions capable of processing large, complex, and potentially multilingual datasets while ensuring that AI-generated results are relevant, traceable, and useful to mission users.
Design, develop, integrate, test, and optimize AI/ML applications using Python and modern AI frameworks.
Apply supervised, unsupervised, semi-supervised, and deep learning techniques, including classification, clustering, recommendation approaches, neural networks, and transformer architectures.
Develop LLM applications using prompt engineering, embeddings, context management, chunking, and retrieval techniques.
Design RAG architectures incorporating document ingestion, vector search, metadata, reranking, and hybrid semantic/keyword retrieval.
Develop agentic AI workflows capable of task planning, tool use, multi-step execution, workflow automation, and multi-agent coordination.
Build data pipelines supporting preprocessing, feature extraction, data validation, deduplication, labeling, and augmentation.
Optimize models through model selection, fine-tuning, hyperparameter tuning, benchmarking, and latency-versus-accuracy analysis.