Artificial Intelligence Software Engineer

Booz Allen Hamilton

. Create and implement complete end-to-end AI and machine learning solutions .

Posted 10/13/2026full-timeUnited StatesMid-LevelSenior💰 $55,200 - $126,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and implementing AI and machine learning solutions, with a strong focus on full-stack development and DevSecOps practices. Proficient in utilizing LLM frameworks and conducting systems engineering analysis for mission-critical systems.

Highest-signal resume keywords

AI And Machine Learning SolutionsFull-Stack DevelopmentDevSecOps ToolsAgile MethodologyModel-Based Systems Engineering

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software Programming ApplicationsLLM Inference EnginesRESTFul APIsNode.jsJavaScriptReactModel Context ProtocolSystems Engineering AnalysisSoftware Product TestingQA/QC

Soft Skills

CollaborationUser-Focused Solutions

Tools & Technologies

GitHub ActionsCameoMagicDrawSparxEADOORSIBM RhapsodyMATLABSTKModelCenterTeamCenter

Certifications & Qualifications

OCSMPASEPGCPAzureAWSSecurity+

Industry Keywords

Digital EngineeringAI-Driven SolutionsIdentity VerificationBiometricsMission-Critical Systems

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformJavaScriptNode.jsReact

About the role

Key responsibilities & impact

Create and implement complete end-to-end AI and machine learning solutions
Develop user-focused solutions that increase organizational efficiency and enable better decision-making
Modernize AI-driven digital engineering capabilities
Ensure solutions consider the broader ecosystem, operating environment, future functionality, and enhancements
Apply leading-edge principles, theories, and concepts to provide innovative solutions
Build expertise in LLM frameworks, DevSecOps, and full-stack development
Design, modify, develop, write, and implement software programming applications using methods such as Agile
Build and manage CI/CD pipelines using DevSecOps tools such as GitHub Actions
Participate in identity verification through advanced biometrics and artificial intelligence
Collaborate with colleagues and customers as required by the role

Requirements

What you’ll need

Experience designing, modifying, developing, writing, and implementing software programming applications using methods such as Agile
Experience working with full-stack LLM solutions
Experience with LLM inference engines
Experience with Cursor or AI-assisted coding tools
Experience with full-stack development, including RESTFul APIs, Node.js, JavaScript, or React
Knowledge of Agile methodology and DevSecOps tools such as GitHub Actions
Ability to obtain a Secret clearance
Bachelor's degree
Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information
Experience implementing and utilizing Model Context Protocol (MCP) in software or digital engineering projects
Experience performing systems engineering analysis for government or mission-critical systems, including the DoW
Experience with Model-Based Systems Engineering (MBSE) tools such as Cameo, MagicDraw, SparxEA, DOORS, and IBM Rhapsody
Experience with MagicDraw plug-in development and Teamwork Cloud administration
Experience with MATLAB, STK, ModelCenter, or TeamCenter
Experience with AWS, Azure, or GCP
Experience with software product testing and QA/QC
Experience with LLM inference engines such as vLLM and llama.cpp
Master's degree is nice to have
Industry certifications such as OCSMP, ASEP, GCP, Azure, AWS, and Security+ are nice to have
AI tools may not be used to assist with interview responses unless explicitly permitted

Benefits

Comp & perks

Health benefits
Life insurance
Disability benefits
Financial benefits
Retirement benefits
Paid leave
Professional development
Tuition assistance
Work-life programs
Dependent care
Recognition awards program
Identity verification and fraud-prevention process
Camera-on expectation during interviews and assessments
Full-time employment benefits eligibility for employees working at least 20 hours per week regularly