Senior AI Solutions Engineer

GXO Logistics, Inc.

. Design, build, configure, and enhance AI-powered applications, workflows, and automations using LLMs, orchestration frameworks such as ADK or LangChain, and Google Cloud Platform services .

Posted 9/29/2026full-timeHouston • Texas • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and implementing AI-powered applications and workflows using LLMs and orchestration frameworks, with a strong focus on integration with enterprise systems and adherence to Responsible AI standards.

Highest-signal resume keywords

Large Language Models (LLMs)Google Cloud Platform (GCP)Python ProgrammingAI Workflow DevelopmentEnterprise Integration

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI Application DevelopmentPrompt EngineeringAPI IntegrationSoftware Development Lifecycle (SDLC)Agile MethodologiesRetrieval-Augmented Generation (RAG)Data Sensitivity ManagementAutomation Opportunities IdentificationMulti-Step AI Workflow OrchestrationProduction-Ready AI Applications

Soft Skills

Strong Communication SkillsAnalytical Problem-SolvingOrganizational SkillsCollaboration SkillsCustomer-Focused Mindset

Tools & Technologies

ADKLangChainVertex AICloud RunBigQueryContainerized DeploymentsDocument Management SolutionsHRIS SystemsCRM SystemsERP Systems

Certifications & Qualifications

Cloud CertificationsAI CertificationsSoftware Engineering CertificationsSolution Architecture Certifications

Industry Keywords

Responsible AIAI Compliance FrameworksEnterprise ArchitectureSecurity StandardsGovernance Standards

Tech Stack

Tools & technologies

BigQueryCloudERPGoogle Cloud PlatformPythonSDLC

About the role

Key responsibilities & impact

Design, build, configure, and enhance AI-powered applications, workflows, and automations using LLMs, orchestration frameworks such as ADK or LangChain, and Google Cloud Platform services
Translate business processes into scalable AI solutions by integrating LLMs, APIs, and enterprise systems
Develop, test, troubleshoot, and deploy AI solutions from prototype through production readiness
Integrate AI applications with HRIS, CRM, ERP, finance systems, and document management solutions
Implement human-in-the-loop workflows, validation checkpoints, and escalation paths for responsible and auditable AI usage
Collaborate with Product, Deployment, PMO, Architecture, Security, Data, and AI Platform teams
Identify and mitigate AI risks including hallucinations, data sensitivity, bias, and inappropriate automation
Create reusable implementation patterns, documentation, and engineering standards
Support testing, deployment, integration, and continuous improvement of enterprise AI solutions
Ensure solutions align with enterprise architecture, security, governance, and Responsible AI standards

Requirements

What you’ll need

Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or a related field, or equivalent practical experience
Experience designing, building, configuring, or integrating enterprise technology solutions in complex environments
Experience working with large language models (LLMs) or generative AI technologies, including prompt engineering and AI workflow development
Experience building AI-driven workflows or agentic systems using orchestration frameworks such as ADK, LangChain, or similar technologies
Strong programming experience with Python
Hands-on experience with Google Cloud Platform (GCP), including Vertex AI, Cloud Run, BigQuery, and related cloud-native technologies
Experience integrating APIs and enterprise platforms such as HRIS, CRM, ERP, finance, or document management systems
Understanding of software development lifecycle (SDLC), Agile methodologies, and cross-functional delivery practices
Experience implementing secure, scalable, and production-ready AI applications
Strong written and verbal communication skills with the ability to collaborate across technical and business teams
Ability to work independently while managing multiple priorities in a fast-paced environment
Experience with Retrieval-Augmented Generation (RAG) architectures
Experience handling unstructured data and multi-step AI workflow orchestration
Cloud, AI, software engineering, or solution architecture certifications
Experience implementing Responsible AI, governance, or AI compliance frameworks
Experience working with enterprise architecture and security standards
Familiarity with containerized deployments and enterprise integration patterns
Strong analytical and problem-solving skills
Ability to identify opportunities for automation, process optimization, and AI innovation
Excellent organizational and project management skills
Strong collaboration and interpersonal skills with a customer-focused mindset
Ability to provide technical guidance, mentorship, and knowledge sharing across engineering teams
High attention to detail with a commitment to delivering secure, reliable, and scalable AI solutions
Self-motivated with a strong sense of ownership and accountability
May be required to pass a pre-employment drug test after receiving a conditional offer

Benefits

Comp & perks

Full health insurance (medical, dental, and vision)
401(k)
Life insurance
Disability coverage
Equal Opportunity employer including Disabled/Veterans