Solution Engineer

Matter and Energy, LLC is a tech solutions company specializing in data infrastructure, artificial intelligence, and intelligent IT spending management for government and mission-driven organizations. We operate at the intersection of cloud, data, AI, and automation. We combine deep technical understanding with strategic thinking to help leaders modernize IT, improve cost transparency, and build more secure and resilient digital ecosystems.

About the Role

Matter + Energy is seeking an experienced, hands-on Solution Engineer to design and implement AI-powered solutions that address complex business challenges and deliver measurable value for enterprise clients.

In this role, you will take ownership of end-to-end technical implementations, from discovery and solution architecture through development, integration, testing, and deployment. You will work directly with clients to identify AI use cases, evaluate technical feasibility, and translate business requirements into practical, scalable solutions.

The ideal candidate combines strong software engineering skills with hands-on experience in generative AI, large language models (LLMs), and enterprise system integration. You should be comfortable independently leading technical implementations, navigating complex client environments, and turning emerging AI capabilities into reliable, production-ready solutions.

Key Responsibilities

AI Solution Design and Implementation

• Independently lead end-to-end AI solution implementations, from technical discovery and solution design through development, testing, deployment, and optimization.
• Collaborate with clients to understand business challenges, identify AI opportunities, and translate requirements into technical solutions.
• Design and develop AI-powered applications, intelligent workflows, and automation solutions using LLMs, generative AI, and related technologies.
• Build and integrate AI agents, retrieval-augmented generation (RAG) systems, and knowledge-based applications.
• Evaluate AI models, frameworks, and technology platforms based on performance, cost, scalability, security, and business requirements.
• Develop proof-of-concept solutions and transition validated prototypes into production-ready implementations.

Technical Development and Integration

• Develop backend services, APIs, and application components to support AI-powered solutions.
• Integrate AI capabilities with enterprise applications, databases, document repositories, and existing business workflows.
• Design and implement data ingestion, preprocessing, transformation, and retrieval pipelines.
• Develop and optimize prompt engineering strategies, tool integrations, and AI orchestration workflows.
• Implement testing and evaluation processes to assess model outputs, accuracy, reliability, and overall solution performance.
• Troubleshoot complex technical issues, optimize system performance, and ensure solution maintainability.
• Apply appropriate security, access control, data privacy, and responsible AI practices throughout the implementation lifecycle.

Client Engagement and Technical Leadership

• Lead technical discovery sessions and solution design discussions with client stakeholders.
• Assess client technology environments, data readiness, integration requirements, and implementation constraints.
• Translate business requirements into solution architectures, technical specifications, and implementation plans.
• Serve as the primary technical point of contact throughout the implementation lifecycle.
• Communicate technical concepts, architectural decisions, risks, and recommendations to both technical and nontechnical audiences.
• Independently manage technical deliverables, proactively identify risks, and resolve implementation challenges.
• Collaborate with project managers, consultants, and client teams to ensure successful delivery.

Solution Quality and Continuous Improvement

• Establish and apply best practices for AI solution development, testing, deployment, and monitoring.
• Evaluate AI solution quality, including accuracy, reliability, latency, cost, and security.
• Monitor and improve deployed AI applications based on performance metrics and user feedback.
• Develop reusable technical components, implementation templates, and engineering best practices.
• Stay current with emerging AI technologies, frameworks, and industry developments.
• Contribute technical expertise to solution demonstrations, proof-of-concept engagements, and presales activities.

Required Qualifications

• Bachelor's degree in Computer Science,…