Senior Agentic AI Engineer

Nyla Technology Solutions•Annapolis Junction, MD

20h•$156,000 - $184,000

About The Position

The Senior Agentic AI Engineer will support critical defense and intelligence customer missions by developing and deploying NLP and NER capabilities for LLM solutions using LangGraph. The role leads supervised and unsupervised model training, fine-tuning, and validation workflows to enable dynamic knowledge extraction from multilingual, unstructured data without a predefined ontology. It also involves working with customer data sources, building high-quality training and evaluation datasets, applying data-quality techniques, and ensuring solutions meet enterprise compliance, security, governance, and end-user access requirements. An active TS/SCI clearance with a polygraph is required. The annual base salary range is $156,000–$184,000 USD, excluding discretionary bonus compensation and benefits. Actual compensation may vary based on geographic location, work experience, education, and skill level.

Requirements

Active security clearance at the TS/SCI polygraph level.
Hands-on proficiency developing, orchestrating, and training NLP/NER capabilities for LLM solutions using LangGraph.
Strong experience in supervised and unsupervised model training, fine-tuning, and validation for automated knowledge extraction from unstructured, multilingual natural-language data without a predefined ontology.
Deep understanding of customer data sources, retrieval techniques, and preprocessing pipelines for training and evaluation datasets.
Mastery of techniques for validating, cleaning, and enriching training data.
Strong understanding of enterprise data compliance, security policies, and governance protocols.
Bachelor’s degree in Data Science, Computer Science, Computational Linguistics, Mathematics, or a related technical discipline plus 10 or more years of professional experience in data science, NLP, or software engineering; alternatively, an associate’s degree plus 12 or more years of specialized technical experience in lieu of a degree.

Nice To Haves

Experience with cross-lingual embeddings, multilingual transformer architectures, and low-resource language processing.
Familiarity with RAG architectures, vector stores such as Qdrant, ChromaDB, PGVector, or Pinecone, and semantic search indexing.
Proficiency in Python and modern ML/DL libraries such as PyTorch, Hugging Face Transformers, SpaCy, and LangChain.
Experience deploying containerized AI microservices with Docker and Kubernetes and setting up MLOps pipelines for continuous model monitoring and evaluation.

Responsibilities

Develop, orchestrate, train, and deploy NLP and NER capabilities for LLM solutions within LangGraph agentic AI frameworks.
Lead supervised and unsupervised model training, fine-tuning, and validation workflows for automated knowledge extraction from multilingual, unstructured data without a predefined ontology.
Work with customer data sources and retrieval techniques to prepare high-quality training and evaluation datasets.
Validate, clean, and enrich training data to support high-quality pipelines and seamless system integration.
Ensure AI solutions comply with enterprise data, security, governance, regulatory, and end-user access requirements.