AWS Agentic AI Platform Engineer

Booz Allen Hamilton•San Antonio, TX

22h•$99,000 - $225,000

About The Position

As an experienced AI/ML engineer, you know that machine learning and generative AI are critical to understanding and processing large, complex datasets. Your ability to apply statistical learning, large language models, retrieval techniques, and agentic workflow patterns makes you an integral part of delivering secure, customer-focused solutions. We need your technical knowledge and desire to problem-solve to help mission organizations transform fragmented data and manual processes into trustworthy AI-enabled decision support and workflow automation. As an AI/ML engineer on our national security team, you’ll train, test, deploy, and maintain machine learning models and agentic applications that learn from data, retrieve governed knowledge, interact with approved tools and services, and support human decision-making. In this role, you’ll own and help define the direction of mission-critical solutions by applying best-fit ML algorithms, foundation models, retrieval architectures, and agent orchestration patterns. You’ll be part of a talented team of machine learning engineers across the company and collaborate with data engineers, data scientists, software engineers, cloud and DevSecOps engineers, solutions architects, product owners, and mission subject matter experts to deliver secure AWS-based capabilities that process structured and unstructured data, automate complex workflows, and produce traceable outputs. Your skills and technical expertise will guide clients as they navigate the landscape of AI/ML algorithms, tools, frameworks, evaluation methods, and production deployment patterns. Work with us to solve real-world challenges and define AI/ML strategy for national defense mission-support operations.

Requirements

2+ years of experience with AI/ML engineering, data science, software engineering, data engineering, or cloud engineering
Experience developing AI/ML applications using Python
Experience developing agentic AI or large language model applications, retrieval-augmented generation systems, or predictive machine learning models
Experience integrating AI/ML capabilities with APIs, data stores, cloud services, or enterprise applications
Experience developing, deploying, or supporting applications on AWS
Knowledge of AI/ML evaluation methods for model quality, retrieval relevance, task success, latency, cost, or system performance
Knowledge of software engineering and DevSecOps practices, including version control, automated testing, CI/CD, containerization, and infrastructure as code
Ability to translate operational needs into testable technical requirements and collaborate with multidisciplinary engineering and mission teams
Ability to obtain a Secret clearance
Bachelor’s degree

Nice To Haves

Experience developing agentic AI applications using AWS Strands Agents, LangGraph, LangChain, LlamaIndex, or comparable frameworks
Experience with Amazon Bedrock, Amazon SageMaker AI, Amazon OpenSearch Service, Knowledge Bases for Amazon Bedrock, Amazon Bedrock Guardrails, or related AWS AI/ML services
Experience implementing retrieval-augmented generation, embeddings, vector search, reranking, knowledge graphs, Model Context Protocol, Agent-to-Agent communication, or structured tool-calling integrations
Experience developing Python APIs, microservices, or durable workflows using FastAPI, Pydantic, OpenAPI, Temporal, AWS Step Functions, Amazon EventBridge, or comparable technologies
Experience with Docker, Kubernetes, Amazon EKS, Amazon ECS, Terraform, AWS CloudFormation, AWS CDK, or CI/CD automation
Experience with MLOps or LLMOps, including automated evaluation, prompt or model versioning, observability, tracing, drift monitoring, or rollback controls
Experience supporting AWS GovCloud, FedRAMP High, DoD Impact Level 4 or 5, or another regulated or high-assurance cloud environment
Experience with computer vision, multimodal AI, geospatial analytics, graph neural networks, temporal or dynamic graph networks, network science, or social network analysis
Secret clearance
AWS AI/ML, Software Development, Architecture, DevOps, Cloud Operations, or Security Certification or CompTIA Security+ Certification

Responsibilities

Train, test, deploy, and maintain machine learning models and agentic applications.
Apply statistical learning, large language models, retrieval techniques, and agentic workflow patterns.
Define the direction of mission-critical solutions by applying best-fit ML algorithms, foundation models, retrieval architectures, and agent orchestration patterns.
Collaborate with data engineers, data scientists, software engineers, cloud and DevSecOps engineers, solutions architects, product owners, and mission subject matter experts.
Deliver secure AWS-based capabilities that process structured and unstructured data, automate complex workflows, and produce traceable outputs.
Guide clients as they navigate the landscape of AI/ML algorithms, tools, frameworks, evaluation methods, and production deployment patterns.