AI Engineer

Guidehouse

AI Engineer building, testing, and deploying AI applications and services at Guidehouse. Collaborating with teams to iterate on use cases and deliver scalable solutions.

Posted 6/30/2026full-timeMcLean • Virginia • 🇺🇸 United StatesMid-LevelSenior💰 $98,000 - $163,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying AI applications and services, with a strong focus on cloud-native solutions and modern DevOps practices. Proficient in integrating AI capabilities and maintaining cloud resources while adhering to responsible AI practices and compliance requirements.

Highest-signal resume keywords

AI Application DevelopmentCloud-Native ServicesGenerative AI ExperienceCI/CD and DevOps PracticesDocumentation and Collaboration

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine Learning EngineeringData Pipeline ImplementationAPI DevelopmentContainerizationInfrastructure as CodeTroubleshooting Production SystemsVector DatabasesEmbeddingsPrompt OrchestrationFunction/Tool Calling

Soft Skills

Growth MindsetCross-Functional Collaboration

Tools & Technologies

AWSAzureGCPDockerKubernetesTerraformDatabricksPalantir

Industry Keywords

Responsible AI PracticesSecurity ComplianceCommercial SectorPublic Sector

Tech Stack

Tools & technologies

AWSAzureCloudDockerGoogle Cloud PlatformKubernetesMicroservicesTerraform

About the role

Key responsibilities & impact

Build, test, and deploy AI applications and services, translating solution designs and reference architectures into working, demo-ready components
Implement data and ML pipelines (ingest, transform, feature stores, vector indexes) and wire up retrieval-augmented generation (RAG) and agentic workflows
Package and serve models (LLMs and traditional ML) via APIs and microservices using containers and orchestration (e.g., Docker, Kubernetes)
Stand up and maintain cloud resources and AI platforms (AWS, Azure, GCP; Palantir; Databricks), including CI/CD, IaC (e.g., Terraform), secrets, and observability
Integrate AI capabilities (prompt orchestration, tool/function calling, embeddings, fine-tuning) into applications and services
Collaborate with data scientists, platform engineers, and product teams to iterate on use cases, deliver POCs/MVPs, and harden them for scale
Contribute to demos, technical documentation, and solution content for proposals and pitch materials
Follow responsible AI practices and security/compliance requirements across commercial and public sector environments

Requirements

What you’ll need

US Citizenship is required
Bachelor’s degree is required
Minimum THREE (3) years of experience in software, data, or ML engineering, including building and operating cloud-native services
Minimum ONE (1) year of hands-on experience with Generative AI and/or agentic patterns (e.g., RAG, function/tool calling, prompt orchestration)
Proficiency with at least one major cloud (AWS, Azure, or GCP) and modern DevOps practices (Git, CI/CD, containerization, infrastructure as code)
Familiarity with vector databases and embeddings and LLM application frameworks
Ability to troubleshoot production systems (logs, metrics, traces)
Write clear documentation/runbooks and collaborate in cross-functional teams
Growth mindset with interest in expanding into broader architecture responsibilities over time

Benefits

Comp & perks

Medical, Rx, Dental & Vision Insurance
Personal and Family Sick Time & Company Paid Holidays
Position may be eligible for a discretionary variable incentive bonus
Parental Leave and Adoption Assistance
401(k) Retirement Plan
Basic Life & Supplemental Life
Health Savings Account, Dental/Vision & Dependent Care Flexible Spending Accounts
Short-Term & Long-Term Disability
Student Loan PayDown
Tuition Reimbursement, Personal Development & Learning Opportunities
Skills Development & Certifications
Employee Referral Program
Corporate Sponsored Events & Community Outreach
Emergency Back-Up Childcare Program
Mobility Stipend