Senior AI Engineer, AWS

General Dynamics Information Technology

. Design, build, and ship autonomous and multi-agent systems in production using Amazon Bedrock and Bedrock AgentCore .

Posted 10/19/2026full-timeRockville • Maryland • United StatesSenior💰 $129,813 - $166,750 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing scalable AI architectures on AWS, utilizing Amazon Bedrock and related technologies. Proficient in operationalizing AI agents with a focus on reliability, security, and compliance in production environments.

Highest-signal resume keywords

Amazon BedrockGenerative AI ApplicationsInfrastructure as CodePrompt EngineeringAWS Well-Architected Framework

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI Agent DesignRAG PipelinesPython ProficiencyDevOps PracticesMulti-Agent OrchestrationFoundation ModelsVector DatabasesCI/CD PipelinesTerraformCloudFormation

Soft Skills

Communication SkillsConsulting SkillsTroubleshooting SkillsMentoring

Tools & Technologies

Amazon SageMakerAmazon QDockerAWS CDKBedrock AgentCore

Certifications & Qualifications

AWS CertificationsPublic Trust

Industry Keywords

AI StrategyData PrivacySecurity ControlsRegulated EnvironmentsScientific Research

Tech Stack

Tools & technologies

AWSCloudDockerPythonTerraform

About the role

Key responsibilities & impact

Design, build, and ship autonomous and multi-agent systems in production using Amazon Bedrock and Bedrock AgentCore
Select, evaluate, and integrate foundation models on Amazon Bedrock
Design, implement, and evaluate RAG pipelines, including retrieval quality and RAG evaluation
Apply prompt engineering and model customization
Design highly available, scalable, and secure AI architectures on AWS using the Well-Architected Framework and generative-AI best practices
Contribute to AI strategy, reference architectures, and reusable accelerators
Operationalize AI agents with automated evaluation, guardrails, observability, cost and latency optimization, CI/CD, and Infrastructure as Code
Own reliability, quality, and performance of deployed agents
Implement responsible-AI guardrails, data privacy, and security controls, including Bedrock Guardrails, IAM, encryption, and PII handling
Ensure compliance with relevant frameworks
Architect, implement, and evolve AWS cloud solutions supporting generative AI applications, multimodal LLMs, RAG, vector search, knowledge integration, agentic capabilities, and distributed cloud AI services
Engineer full-stack AWS solution plumbing for production GenAI applications
Partner with application developers, AI engineers, cloud engineers, platform developers, security teams, customers, and stakeholders
Translate requirements into scalable, well-architected cloud platform solutions
Serve as a senior technical resource and customer-facing advisor
Mentor junior engineers and communicate recommended AI approaches and tradeoffs to technical and non-technical stakeholders
Stay current with the AWS AI landscape

Requirements

What you’ll need

Bachelor's degree in Computer Science, AI/Data Science, Engineering, or equivalent practical experience
8+ years of relevant experience
Proven experience designing, building, and running AI agents or generative AI applications in production
Hands-on experience with Amazon Bedrock, Bedrock AgentCore, Amazon SageMaker, and Amazon Q
Knowledge of foundation models, prompt engineering, RAG and RAG evaluation, vector databases, tool/function calling, multi-agent orchestration, memory, and agent evaluation
Practical experience with at least one agent framework: Strands Agents, LangGraph, LangChain, CrewAI, or Bedrock Agents SDK
Experience with Infrastructure as Code using Terraform, CloudFormation, or AWS CDK
Experience with CI/CD pipelines for AI/ML workloads
Deep AWS experience across compute, networking, storage, identity, security, monitoring, and APIs
Experience with DevOps/CI-CD practices, Docker, and operational support
Strong architecture, troubleshooting, consulting, and communication skills
Ability to independently own complex solutions and collaborate across technical and non-technical stakeholders
Strong Python proficiency with software engineering practices including version control, testing, and code review
Ability to obtain and maintain a Public Trust
NACLC (T3) public trust requirement
No security clearance currently possessed or required to obtain
US citizenship is not required
Preferred: Well-Architected Framework and GenAI reference architecture/reusable accelerator experience
Preferred: LLMOps/MLOps tooling, model evaluation, observability, prompt management, and guardrails
Preferred: Fine-tuning or customizing foundation models; knowledge bases and vector stores including Amazon OpenSearch, Aurora pgvector, and Amazon Kendra
Preferred: Relevant AWS certifications
Preferred: Experience supporting scientific research, federal government, healthcare, or regulated environments

Benefits

Comp & perks

Full benefits
Medical plan options, including some with Health Savings Accounts
Dental plan options
Vision plan
401(k) plan with pre-tax and post-tax contributions and company match
Full flex work weeks where possible
Paid time off, including vacation, sick, personal, holiday, parental, military, bereavement, and jury duty leave
Typically 15 days of paid leave per calendar year
10 paid holidays per year
Up to 160 hours of paid family leave in a rolling 12-month period for eligible employees
Short- and long-term disability benefits
Life insurance
Accidental death and dismemberment insurance
Personal accident insurance
Critical illness insurance
Business travel and accident insurance
AI-powered career tool identifying career steps and learning opportunities
Internal mobility team supporting career goals
Wellness programs
Award-winning culture of innovation
Military-friendly workplace