Senior AI System Architect (Outcome-Based AI in PALM BAY, Florida at Dynatech International LLC
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Job Description
Job Title: Senior AI System Architect (Outcome-Based AI Operations)
Department: Information Technology
Reports to: Vice President of Information Technology
Location: Palm Bay, FL
Company Overview
Company Overview: Established in 1973, Dynatech International is a Commercial and Defense supply chain company providing long term, complex procurement, engine overhaul, rotable and repair management services, manufacturing, and kitting solutions across land, air, sea, and space programs. Dynatech’s proprietary database, the Defense Logistics Management System (DLMS®), empowers us to mitigate supply chain risk, and provide quality supply chain solutions in a cost-effective manner that enhances operational readiness for over 2,000 weapons systems and platforms.
We're actively deploying AI-driven operational systems to modernize sourcing, procurement, proposal development, workflow automation, executive operations, and enterprise decision support.
This is not a traditional "AI chatbot" position.
We're building production-grade AI operational infrastructure designed to create measurable business outcomes, improve operational velocity, enhance executive decision-making, and support scalable autonomous workflows across the enterprise.
We're looking for an AI Systems Architect to help design, implement, and mature the next generation of AI-enabled operational systems at Dynatech.
Position Summary
The Senior AI Systems Architect will lead the design and implementation of enterprise-grade AI operational systems integrating:
- large language models (LLMs) · autonomous agents
- workflow orchestration · retrieval systems
- Microsoft ecosystems · operational data sources
- human-in-the-loop governance
This role takes more than API integration and prompt engineering. The architect needs to design durable AI systems that produce measurable operational outcomes while maintaining security, auditability, governance, scalability, and operational resilience.
The right candidate is equally at home discussing:
- AI orchestration frameworks · workflow engineering
- executive operations · systems integration
- long-term production architecture
Core Responsibilities
AI Systems Architecture
- Architect scalable AI operational systems supporting enterprise workflows
- Design modular, maintainable AI infrastructure
- Build autonomous and semi-autonomous AI agent ecosystems
- Develop long-term memory and retrieval architectures
- Implement human-in-the-loop escalation frameworks
- Design secure production-grade AI pipelines
Workflow Automation
- Automate operational and executive workflows
- Integrate AI into procurement, sourcing, proposal generation, and operational processes
- Develop measurable KPI-driven automation systems
- Create AI-assisted decision support systems
- Design orchestration layers across multiple AI services and tools
Microsoft Ecosystem Integration
- Integrate with Microsoft 365, Azure AI, Microsoft Graph, Teams, Outlook, and SharePoint
- Support AI-driven email, scheduling, task management, and operational workflows
- Implement secure permission and identity management practices
AI Engineering and Orchestration
- Implement multi-agent orchestration frameworks
- Develop RAG (Retrieval-Augmented Generation) systems
- Build vector database architectures
- Implement tool-use and function-calling frameworks
- Develop monitoring, logging, and audit systems
- Design AI safety and governance controls
Operational Governance
- Develop production-grade testing methodologies
- Implement AI guardrails and escalation logic
- Ensure operational transparency and auditability
- Support data governance and compliance requirements
- Build systems resilient to hallucination and workflow failure
Required Qualifications
Compliance and Eligibility (non-negotiable)
- U.S. Person as defined in 22 CFR § 120.62 (U.S. citizen, lawful permanent resident, or protected individual)
- Familiarity with CMMC Level 2, NIST SP 800-171, and DFARS 252.204-7012 requirements, and with handling Controlled Unclassified Information (CUI)
- Comfortable operating in an ITAR-aware environment
- Production system access will not be granted until our standard vendor risk review has been completed
Technical Expertise
- Deep experience with OpenAI APIs and LLM architectures
- Strong understanding of AI orchestration frameworks
- Experience with one or more of:
- Microsoft Foundry
- LangChain
- LangGraph
- CrewAI
- AutoGen
- Semantic Kernel
- Microsoft Copilot Studio
- or similar frameworks
- Experience with vector databases and retrieval systems
- Strong API integration experience
- Strong Python development capabilities
- Experience with Azure AI and Microsoft Graph
- Experience with workflow orchestration platforms
Legacy System Integration
- Experience integrating modern AI services with legacy enterprise applications
- Strong SQL Server background (T-SQL, performance diagnostics, schema discovery)
- Comfort with ASP.NET Web Forms and ERP-class applications as integration targets
- Comfort working across Windows Server, macOS AI compute, and Tailscale-managed networks
Systems and Operations
- Track record designing durable operational systems
- Experience implementing production AI systems
- Strong understanding of workflow engineering
- Experience with logging, monitoring, and observability
- Strong understanding of security and governance
- Experience with scalable enterprise architecture
Business and Strategic Thinking
- Ability to align AI systems with measurable business outcomes
- Strong operational reasoning skills
- Ability to translate executive objectives into technical architectures
- Strong written and verbal communication skills
- Ability to operate independently in a fast-moving environment
Preferred Qualifications
- Experience supporting defense or regulated industries
- Experience with procurement or supply chain systems
- Experience with autonomous operational workflows
- Experience with voice AI systems
- Experience with avatar or conversational AI systems
- Experience integrating AI into ERP or CRM environments
- Experience with executive assistant AI systems
What Success Looks Like
Success in this role means building AI systems that:
- Reduce operational friction
- Improve decision speed
- Enhance sourcing and proposal operations
- Automate repetitive workflows
- Improve executive leverage
- Maintain governance and security
- Scale reliably across the organization
What This Role Is NOT
This role is NOT:
- Basic prompt engineering
- Simple chatbot development
- Front-end-only AI work
- Experimental hobby AI projects
We're looking for a systems architect capable of building operational AI infrastructure with real-world business impact.
Ideal Candidate Traits
The ideal candidate:
- Thinks in systems
- Understands operational workflows
- Values measurable outcomes
- Embraces rapid innovation
- Balances speed with governance
- Operates at both strategic and technical level
Application Requirements
Applicants should provide:
- Resume or CV
- Relevant GitHub or portfolio links
- Examples of production AI systems built
- Architecture examples or diagrams (if available)
- Description of prior AI operational workflows implemented
- Preferred AI stack and orchestration frameworks
- Availability and engagement model
Compensation is competitive and aligned to experience, capability, and demonstrated expertise. Both contract and long-term engagement structures will be considered
We offer a comprehensive benefits package which includes health, dental, vision, & life insurance, and 401k Retirement plan.
Equal Opportunity Employer - Vet/Disability - Drug-Free Workplace