DescriptionThe Systems Performance Analysis Group (KBS) at the Johns Hopkins University Applied Physics Laboratory is seeking a Generative AI & Decision Engineer to design, build, and deploy AI-enabled analytical and decision-support applications for Naval and Air Force sponsors. You will lead the development of human-LLM interaction capabilities, Retrieval-Augmented Generation (RAG) systems, and intelligent agents that operate at scale to support a variety of applications. This role will collaborate closely with internal stakeholders and external sponsors, including DoD organizations, to demonstrate and transition cutting-edge AI technologies into operationally relevant environments.
As anAI & Decision Engineer, you will...Architect, develop, and evolve a Generative AI-powered analytical applications that support human-LLM interactions and LLM-driven decision-making at scale.
- Design and implement LLM agents that can autonomously plan, reason, and act using tools such as RAG, analytical tools, and relevant databases.
- Apply prompt engineering techniques with state-of-the-art models to produce data-driven recommendations based operational and developmental data for a variety of systems.
- Design, implement, and manage RAG pipelines using vector databases and frameworks to integrate relevant documentation, prior analytical results, and large information repositories into LLM decision-making.
- Develop and maintain agents capable of: (1) Interpreting database schemas and generating SQL queries to answer user questions (SQL agents). (2) Translating natural language inputs into structured actions and game events stored in a database for downstream simulation and adjudication.
- Experiment with and evaluate prompting strategies to improve reasoning quality, robustness, and transparency of model outputs in high-consequence decision contexts.
- Integrate orchestration and observability tools (e.g., Prefect) to monitor LLM pipelines, track outputs, and provide real-time insight into system behavior during wargame execution.
- Fine-tune and adapt foundation models (e.g., Llama, Mistral) using AWS SageMaker, Hugging Face TRL, and synthetic data generation (e.g., GPT-4 series) to optimize performance on sponsor-specific tasks such as deductive coding, domain knowledge transfer, etc.
- Engage with internal leadership and external sponsors to demonstrate capabilities, collect requirements, and potentially transition systems to operational users.
- Document system architectures, experiments, evaluation results, and operational guidance; prepare and present technical briefings and reports to technical and non-technical stakeholders.
- Collaborate in multidisciplinary teams (AI/ML, software, human factors, operations analysts) to integrate AI capabilities into broader analytic and operational workflows.
QualificationsYou meet our minimum qualifications for the job if you have...- Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, Applied Mathematics, Data Science, or a closely related field.
- Experience building production or prototype applications involving large language models (LLMs) or other generative models.
- Proficiency in Python and at least one modern web/backend framework (e.g., FastAPI, Flask, Django).
- Experience with relational databases, including schema design and query development (e.g., PostgreSQL).
- Hands-on experience with at least one of:
- Retrieval-Augmented Generation (RAG) systems.
- LLM agent frameworks (tool use, ReAct, chain-of-thought-style prompting).
- Vector databases (e.g., Qdrant, ChromaDB). - Demonstrated ability to comprehend and synthesize complex technical or scientific information and make timely, well-reasoned decisions
- Strong written and oral communication skills, including experience preparing technical analyses and presenting findings to a range of audiences.
- Hold an active Secret security clearance and can ultimately obtain Top Secret level clearance. If selected, you will be subject to a government security clearance investigation and must meet the requirements for access to classified information. Eligibility requirements include U.S. citizenship.
You'll go above and beyond our minimum requirements if you have...- Advanced degree (M.S. or Ph.D.) in Computer Science, AI/ML, Applied Mathematics, or related field.
- Experience with:
- LLM frameworks and libraries (e.g., Hugging Face Transformers, TRL, LangChain).
- Fine-tuning and evaluating open-weight models (e.g., Llama, Mistral) on domain-specific tasks.
- Cloud platforms and MLOps tooling (e.g., AWS, SageMaker, Prefect, MLflow).
- Frontend development using React and integration with RESTful backends (e.g., FastAPI).
- Experience developing AI systems in defense, space, or government contexts, including familiarity with military doctrine, wargaming, operational analysis, or mission planning.
- Prior work on applications supporting Navy, DARPA, or other DoD sponsors, particularly in knowledge-management or decision-support contexts.
- Demonstrated ability to engage with sponsors, understand mission needs, negotiate requirements, and translate them into technical solutions.
Additional Information:- This position may require occasional travel to sponsor sites and test events.
- Candidates will be expected to work in multidisciplinary teams and contribute to both research and applied development efforts.
- APL is committed to fostering an inclusive environment and encourages applications from diverse backgrounds.
Minimum Rate$100,000 Annually
Maximum Rate$245,000 Annually
