Solutions/Agentic AI Architect

Position Overview:

Arch Systems is seeking an experienced Solutions / Agentic AI Architect to lead the design and development of innovative AI-enabled solutions for Federal Government customers.

This role combines deep technical expertise in Agentic AI, Generative AI, cloud, data, application modernization, and enterprise architecture with strong customer-facing, solutioning, and business development capabilities.

The Solutions / Agentic AI Architect will work closely with Federal customers, technical teams, program leadership, capture teams, and strategic partners to understand mission challenges and translate them into secure, scalable, and practical technology solutions. The ideal candidate should be comfortable moving from executive-level discussions and whiteboarding sessions to detailed architecture, prototyping, demonstrations, and proposal development.

A key focus of the role will be designing AI agents and multi-agent systems that can reason, plan, retrieve information, interact with tools and enterprise systems, execute multi-step workflows, and operate with appropriate security, governance, and human oversight.

Key Responsibilities:

Agentic AI & Generative AI Architecture

• Design and architect Agentic AI, Generative AI, and intelligent automation solutions for complex Federal mission and business use cases.
• Develop single-agent and multi-agent architectures that support:
• Reasoning and planning
• Task decomposition
• Tool and function calling
• API interaction
• Workflow execution
• Memory and context management
• Agent-to-agent coordination
• Human-in-the-loop approvals
• Exception handling and escalation
• Design AI agents capable of securely interacting with enterprise systems, databases, document repositories, APIs, workflow platforms, and business applications.
• Develop architectures leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), embeddings, vector databases, knowledge graphs, and enterprise search .
• Evaluate commercial, open-source, and government-approved AI models and platforms based on mission requirements, security, scalability, performance, and cost.
• Develop strategies for prompt engineering, context engineering, model selection, model routing, grounding, model evaluation, and AI guardrails.
• Establish approaches to reduce hallucinations, unauthorized actions, data leakage, and other risks associated with autonomous and semi-autonomous AI systems.

Solution Architecture

• Lead the development of end-to-end technical solutions addressing complex Federal mission, business, and operational challenges.
• Translate customer requirements and problem statements into:
• Solution architectures
• Technical roadmaps
• CONOPS
• Architecture diagrams
• Implementation strategies
• Technical demonstrations
• Proofs of concept
• Design integrated solutions spanning:
• Agentic AI
• Generative AI
• Machine Learning
• Data and Analytics
• Cloud Computing
• Enterprise Architecture
• Application Modernization
• DevSecOps
• APIs and Systems Integration
• Intelligent Automation
• Cybersecurity
• Develop conceptual, logical, and physical architectures that clearly communicate how technologies, applications, data, and users interact.
• Evaluate technical alternatives and make recommendations based on security, scalability, interoperability, cost, performance, maintainability, and implementation risk.
• Establish reusable architecture patterns and technical standards that can be applied across multiple customer environments and Federal opportunities.

Data & Knowledge Architecture

• Design modern data architectures that support AI, analytics, enterprise search, knowledge management, and mission applications.
• Architect solutions utilizing:
• Data lakes
• Data warehouses
• Lakehouses
• Vector databases
• Graph databases
• Knowledge graphs
• APIs
• ETL/ELT pipelines
• Enterprise search
• Develop architectures that allow AI agents to securely retrieve, reason over, and take action based on structured and unstructured enterprise data.
• Support data governance, quality, lineage, metadata management, access control, and information lifecycle management.
• Design AI-powered knowledge management, document intelligence, decision-support, and enterprise search solutions.
• Identify opportunities to improve data usability and accessibility across legacy and modern environments.

Cloud & Modern Application Architecture

• Architec…