Applied AI Engineer

Booz Allen Hamilton•McLean, VA

23h•$77,600 - $176,000

About The Position

As an Applied AI Engineer on Booz Allen’s national security team, you will train, test, deploy, and maintain models that learn from data. You will define the direction of critical solutions by applying suitable machine-learning algorithms and technologies, and collaborate with data engineers, data scientists, solutions architects, and MLOps engineers to deliver solutions that process data and information at scale. You will also guide clients as they evaluate AI and ML algorithms, tools, and frameworks, helping address challenges and shape AI strategy for national security customers. The role involves rapidly prototyping, developing, evaluating, tuning, and iterating on use-case-specific AI capabilities, including chat systems, user-facing applications, and domain-specific copilots. You will work with Mission Integration teams and product stakeholders to translate mission needs into business-facing AI capabilities and adapt solutions to different domains and operational requirements.

Requirements

Experience with software engineering, applied AI and ML, or full-stack development, including AI integrations.
Experience rapidly prototyping, developing, and iterating on use-case-specific AI solutions such as chat systems, user-facing applications, and domain-specific copilots.
Experience evaluating and tuning AI outputs, including refining prompts, optimizing retrieval logic, and implementing custom heuristics.
Experience with Python and building API endpoints with tools such as FastAPI or Flask, or using rapid UI frameworks such as Streamlit or Gradio to demonstrate AI capabilities.
Ability to work closely with Mission Integration teams and product stakeholders to translate mission needs into refined, business-facing AI capabilities.
Ability to pivot between domains and use cases and adapt AI solutions to operational requirements.
Ability to obtain a Secret clearance.
Bachelor's degree.

Nice To Haves

Experience with human-in-the-loop (HITL) evaluation, AI red teaming, or assessing conversational interfaces for safety and hallucination mitigation.
Experience with front-end technologies such as React or TypeScript for end-to-end user-facing product delivery.
Experience deploying and managing analytical dashboards or mechanisms to track user interactions and model performance.
Experience with user experience (UX) best practices tailored to conversational AI and generative interfaces.
Secret clearance.
Security+ Certification.

Responsibilities

Train, test, deploy, and maintain machine-learning models.
Define solution direction by selecting and applying appropriate ML algorithms and technologies.
Collaborate with data engineers, data scientists, solutions architects, and MLOps engineers to deliver AI solutions and process data at scale.
Guide clients as they navigate AI and ML algorithms, tools, and frameworks.
Rapidly prototype, develop, evaluate, tune, and iterate on use-case-specific AI solutions, including chat systems, user-facing applications, and domain-specific copilots.
Work with Mission Integration teams and product stakeholders to translate mission needs into refined, business-facing AI capabilities.
Adapt AI solutions to different domains and operational requirements.