AI Engineer · Knowledge System
Query Bryan's AI Representative directly for validated, retrieval-grounded answers on experience, projects, architecture, and delivery outcomes.
20+ hrs/wk
Time reclaimed through workflow automation
75%
Reduction in manual operational tasks
$168K
Annual efficiency savings delivered
Profile
I specialize in applied AI engineering, designing retrieval pipelines, observability layers, and governed multi-agent systems that behave predictably in production. My core doctrine: Agents should reason freely, but execute through controls.
My background spans federal consulting and private delivery, with deep roots in process optimization and operational governance before moving into AI systems engineering. That background shapes how I build: business-first, measurable, and observable by design.
Experience
Founder | Agentic Systems & AI Engineering
PowerLogic Solutions, LLC · 2025 – Present · Remote
Senior Consultant
ABS Consulting Inc. · 2020 – 2025 · Washington, DC
Team Lead / Lead Analyst
UniSpec Enterprises Inc. (U.S. DOT Contract) · 2008 – 2020 · Washington, DC
Under the hood
This AI Representative is built on a retrieval-based architecture designed for accuracy, control, and transparency.
Instead of generating answers from model memory, it retrieves verified information from a structured knowledge base, applies validation layers, and returns grounded responses with clear context.
This diagram shows the end-to-end pipeline behind the AI Representative.
Each request passes through input validation, retrieval, ranking, and controlled response generation, with multiple layers of security and cost controls applied throughout the system.
Before your question reaches the system, the request is checked to confirm it comes from a real person in an authorized session. Requests that arrive from unrecognized sources, or that exceed normal usage patterns, are turned away before any processing begins.
This system is actively monitored through LogicFlow OS™, an operational intelligence platform being developed through PowerLogic Solutions. Response quality, usage patterns, and reliability are reviewed on an ongoing basis — and the knowledge base is updated as gaps are identified.
Simplified system view (full technical breakdown available)
This interactive view represents how the knowledge base is organized by meaning — not keywords. Unlike traditional databases that retrieve information by matching exact words, this system stores each piece of content by what it's about, so responses stay relevant even when your question is phrased differently than the source material.
Each point is an illustrative marker showing how knowledge clusters by theme across public profile data, professional context, and approved talking points. It is a conceptual map of the retrieval space, not a literal one-to-one rendering of live chunks.
Model: OpenAI text-embedding-3-small · illustrative semantic map
Together, these layers ensure responses are not only relevant, but explainable, controlled, and tied to real underlying data.
Observability
Every query this system handles is instrumented. LogicFlow OS™ — a purpose-built AI observability platform developed through PowerLogic Solutions — monitors the AI Representative across five operational dimensions: reliability, latency, retrieval quality, security pressure, and cost.
Unknown questions feed a structured knowledge-gap backlog. Benchmark evaluation runs on a separate lane from live telemetry so quality regressions are caught before they're mistaken for normal variance. The result is a system that isn't just deployed — it's observable, governable, and improving over time.
Operational Monitoring
Eight live KPIs — success rate, p95 latency, KB hit rate, refusal rate, average citations, cost per query, and security pressure — alongside advisory cards that surface regressions and executive-level operating summaries on a rolling window.
Benchmark Evaluation
Retrieval quality (MRR, nDCG@5) and answer quality (accuracy, completeness, relevance, faithfulness) measured against a versioned golden dataset — on a separate evaluation lane from live telemetry so quality changes are deliberate, not accidental.
LogicFlow OS™ — AI observability platform · PowerLogic Solutions, LLC
Contact
I'm open to discussing full-time AI engineering roles or contract engagements where delivery quality and business impact both matter. Remote, U.S.-based.