Lead AI Architect, Strategist

LTS

Lead AI Architect/Strategist at LTS driving enterprise AI transformation through scalable AI platforms and advanced analytics solutions. Collaborating with diverse teams to establish AI roadmaps and standards.

Posted 7/29/2026full-timeRemote • 🇺🇸 United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in AI architecture strategies, including the design and implementation of scalable AI platforms and solutions utilizing Generative AI, LLMs, and RAG. Proven ability to lead technical evaluations, establish AI governance practices, and communicate complex AI concepts effectively to diverse audiences.

Highest-signal resume keywords

AI Architecture StrategiesGenerative AI SolutionsLarge Language Models (LLMs)Retrieval-Augmented Generation (RAG)Cloud AI Platforms

ATS Keywords

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Hard Skills

AI/ML Solution DesignEnterprise ArchitectureData ArchitectureModel OrchestrationPython ProgrammingAPIs DevelopmentData PipelinesMLOps PracticesPrompt EngineeringDistributed Systems

Soft Skills

Technical LeadershipMentorshipEffective Communication

Tools & Technologies

Azure OpenAI ServicesAWS BedrockGoogle Vertex AILang ChainLang GraphLlama IndexSemantic KernelOpenAI Frameworks

Industry Keywords

AI GovernanceAutomation SolutionsKnowledge Retrieval SystemsData-Driven Decision SupportAI Transformation Strategies

Tech Stack

Tools & technologies

AWSAzureCloudDistributed SystemsPython

About the role

Key responsibilities & impact

Define and execute AI architecture strategies, technical roadmaps, and modernization approaches aligned with organizational goals.
Design scalable AI platforms and solutions leveraging Generative AI, LLMs, RAG, AI agents, machine learning, and automation capabilities.
Architect intelligent AI systems that integrate models, data platforms, enterprise applications, and APIs.
Develop architecture patterns and best practices for: LLM-based applications, Agentic AI workflows, AI copilots and automation solutions, knowledge retrieval systems, data-driven decision support.
Design and evaluate RAG architectures, including data ingestion, embeddings, vector search, retrieval strategies, and model orchestration.
Lead technical evaluations of emerging AI technologies, frameworks, and platforms.
Guide teams in implementing AI solutions from proof-of-concept through production deployment.
Establish AI governance practices supporting security, compliance, responsible AI, scalability, and operational excellence.
Collaborate with software engineers, data scientists, product teams, and enterprise architects to deliver AI-enabled solutions.
Provide technical leadership, mentorship, and guidance on AI architecture patterns and engineering best practices.
Communicate complex AI concepts and recommendations to technical teams, business stakeholders, and executive leadership.
Support innovation initiatives through prototypes, technical demonstrations, and AI transformation strategies.

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Information Technology, Engineering, Data Science, or related technical field.
10+ years of experience in software engineering, enterprise architecture, solution architecture, data architecture, or technology transformation.
5+ years of experience designing and implementing AI/ML solutions, AI platforms, or intelligent automation solutions.
Strong experience architecting enterprise-scale technology solutions and distributed systems.
Proven experience with Generative AI, Large Language Models (LLMs), and AI application architectures.
Hands-on experience with AI concepts and technologies including Retrieval-Augmented Generation (RAG), AI Agents / Agentic AI, prompt engineering, vector databases and embeddings, model orchestration, AI governance and lifecycle management.
Experience with cloud AI platforms such as: Azure OpenAI / Azure AI Services, AWS Bedrock, Google Vertex AI.
Experience with modern AI frameworks and tools such as: Lang Chain, Lang Graph, Llama Index, Semantic Kernel, OpenAI frameworks.
Strong programming experience with Python or other modern programming languages.
Experience with data architecture, APIs, data pipelines, and enterprise system integration.
Understanding of MLOps/LLMOps practices, including monitoring, evaluation, deployment, and governance.
Ability to communicate complex technical concepts effectively with both technical and non-technical audiences.

Benefits

Comp & perks

The Opportunity to support high-visibility federal missions
A culture that values innovation, growth, and collaboration
Access to cutting-edge tools and technologies
Comprehensive benefits for you and your family
A career path that rewards ambition and performance