AI Engineer

SMX•Aiea, HI

11d•$140,000 - $173,000•Onsite

About The Position

SMX is seeking an AI Engineer to support a government client at Camp Smith. The AI Engineer designs, develops, tests, and improves AI-enabled systems that support client operations, business processes, and organizational Knowledge Management. This role transforms business and operational processes into tools that can be integrated into AI harnesses, workflows, and agentic systems. The ideal candidate has a balanced technical background and military operational experience. This combination allows the AI Engineer to understand real operational processes and convert them into practical AI-integrated systems. The AI Engineer should be able to work with Maven Smart System as the primary platform while also understanding cloud environments, AI tools, data systems, and modern AI development patterns. This role supports the creation of AI capabilities that may include AI-integrated tools, retrieval workflows, organizational data models, internal LLM development, prompt systems, AI agents, and systems that use organizational data to improve decision support. This position requires a current DoD Top Secret SCI security clearance which requires US citizenship for work on DoD contracts. This position is full-time onsite in Aiea, Hawaii.

Requirements

Bachelor’s degree in computer science, AI, Data Science, Software Engineering, Information Systems, Cybersecurity, Engineering, or related field.
5–8 years of relevant technical experience; additional experience may substitute for degree.
Experience developing AI-enabled systems, tools, workflows, automation, or data integrations.
Strong understanding of cloud environments, AI tools, APIs, databases, and system integration.
Experience with RAG, LLMs, AI agents, embeddings, vector search, prompt engineering, and AI evaluation.
Ability to transform business and operational processes into AI-integrated tools.
Ability to test and evaluate AI outputs.
Understanding of human-in-the-loop review and responsible AI use.
Must meet applicable DoD 8140 / DCWF requirements.

Nice To Haves

Military operational experience is strongly preferred.
Experience with Maven Smart System as the primary AI/operational platform preferred.
Experience supporting in-house LLMs or domain-adapted AI systems using organizational data preferred.
IAT Level II or IAM Level I equivalent certification preferred; IAT Level III, IAM Level II, or IASAE-equivalent preferred for elevated technical roles.
Military operational experience or strong understanding of military workflows.
Experience with Palantir or Maven Smart System.
Experience developing AI tools in cloud environments.
Experience supporting operational, intelligence, or defense organizations.
Experience with Python, APIs, data pipelines, or AI development frameworks.
Experience creating RAG systems, AI agents, or prompt libraries.
Experience with internal LLM development, fine-tuning, or domain adaptation.
Experience building AI systems around organizational data.

Responsibilities

Builds the AI-enabled technical capability that transforms client processes into integrated tools, workflows, and AI systems.
Design, build, and support AI-integrated systems that improve client workflows and decision-making.
Transform operational and business processes into tools that can be integrated into AI-enabled environments.
Support Maven Smart System as the primary AI and operational integration platform.
Develop AI-enabled workflows that connect organizational knowledge, data, tools, and decision processes.
Support the design and development of in-house LLM capabilities trained or tuned on approved organizational data, where authorized.
Develop retrieval-augmented generation workflows using trusted organizational data sources.
Support AI agent workflows that retrieve information, summarize content, call tools, generate draft products, and support human decision-making.
Design prompt templates, prompt chains, structured outputs, and reusable AI patterns.
Integrate AI systems with cloud environments, APIs, databases, knowledge repositories, dashboards, and workflow tools.
Support embedding models, vector search, knowledge retrieval, data ingestion, and AI search capabilities.
Develop methods to test and evaluate AI system performance, accuracy, relevance, and usefulness.
Work with the AI Integrator and Knowledge Systems Integrator to ensure AI tools are operationally useful, adopted by users, and connected to real client workflows.
Support AI governance, human-in-the-loop review, data protection, and auditability.