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Agentic AI Engineer
Booz Allen HamiltonCore Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and implementing intelligent agent architectures, developing multi-agent systems, and optimizing machine learning models for production environments. Proficient in evaluating system performance and reliability while leveraging cloud technologies and advanced data integration techniques.
Highest-signal resume keywords
Machine Learning EngineeringMulti-Agent Systems DevelopmentCloud Environments (AWS, Azure)RAG Architecture and Knowledge GraphsTop Secret Clearance
Tech Stack
Tools & technologiesAbout the role
Key responsibilities & impact- Design and implement intelligent agent architectures that can reason, plan, and take actions
- Develop and deploy multi-agent systems using MCP and A2A protocols
- Build advanced RAG pipelines integrating unstructured data with Knowledge Graphs
- Fine-tune SLMs for specific domains and optimize them for edge device performance using ONNX, GGML, or Ollama
- Develop evaluation frameworks to test agent reliability, safety, and performance
- Move agent systems from prototype to production, including ReAct loops and human-in-the-loop processes
Requirements
What you’ll need- 2+ years of experience in software development
- 2+ years of experience as an ML engineer building production-grade ML solutions
- Experience with Docker or Kubernetes, GenAI, LLMs, deep learning, reinforcement learning, AI agents, agentic workflows, or complex automation frameworks
- 2+ years of experience with LangChain, LangGraph, AutoGen, PydanticAI, CrewAI, or LlamaIndex
- 2+ years of experience working in cloud environments, including AWS and Azure
- Experience evaluating architectural tradeoffs and designing robust service-based software applications for scalable use
- Experience with MCP and A2A protocols
- Experience with RAG architecture and Knowledge Graphs, including Neo4j or NebulaGraph
- Experience fine-tuning LLMs or SLMs using Hugging Face, PEFT, or LoRA
- Experience evaluating LLM performance and behavior
- Experience building observation layers using Grafana, Langfuse, LangSmith, or Phoenix
- Knowledge of modern software design patterns, including microservice design or edge computing
- Ability to adapt in a rapidly changing environment and navigate ambiguity
- Top Secret clearance required
- Bachelor’s degree
- Master’s degree in a CS or AI field preferred
- Doctorate degree in CS or Statistics a plus
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 virtual meetings
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Software DevelopmentDeep LearningReinforcement LearningFine-Tuning LLMsMCP ProtocolsA2A ProtocolsDockerKubernetesLangChainNeo4j
Soft Skills
AdaptabilityProblem-Solving
Tools & Technologies
ONNXGGMLOllamaGrafanaLangfuseLangSmithPhoenix
Certifications & Qualifications
Bachelor's DegreeMaster's Degree in CS or AIDoctorate Degree in CS or StatisticsTop Secret Clearance
Industry Keywords
AI AgentsAgentic WorkflowsComplex Automation FrameworksObservation LayersMicroservice DesignEdge Computing