Customer-facing engineering · AI · Infrastructure · Integration
Forward-Deployed Engineer
Enterprise Integration · Applied AI · Production Systems
I work where customer requirements, software, infrastructure, APIs, data, and production reality intersect.
I turn ambiguous technical problems into deployed systems — working across discovery, architecture, integration, implementation, troubleshooting, and the path to production.
15+ years from NOC operations and enterprise telecom deployments through global Professional Services, now applied to modern software, infrastructure, data, and AI systems.
How I work
Engineering at the customer boundary.
The hardest technical problems rarely arrive as clean tickets or greenfield projects. They arrive as incomplete requirements, legacy systems, production dependencies, security constraints, third-party integrations, deadlines, and customers who need the system to work.
Discover
Understand the customer's actual environment, constraints, dependencies, workflows, and desired outcome.
Architect
Translate the problem into systems, integrations, data flows, interfaces, failure domains, and an executable plan.
Build
Implement or automate the missing pieces across software, APIs, data, infrastructure, and AI systems.
Integrate
Work with existing environments rather than assuming a greenfield architecture.
Deploy
Test, validate, troubleshoot, coordinate dependencies, support go-live, and own the path into production.
Codify & Scale
Turn successful one-off solutions into reusable architecture, documentation, automation, tooling, and engineering patterns.
Operating thesis
AI looks new until you diagram the traffic.
Telecom taught me to classify the session, select an eligible route, apply policy, observe the path, design failover, and know who owns the incident. Models, agents, APIs, and knowledge systems use different technologies, but many of the operating questions remain.
That operating discipline is the bridge between my telecom career and Forward-Deployed Engineering.
Career arc
Built from the field inward.
Every layer of the stack, learned in the order things actually break.
- 01
Technical Support / NOC
Break/fix, MACD, production monitoring, network troubleshooting, customer-impacting incidents.
- 02
Voice & Data Engineering
Routing, SIP, voice/data services, contact-center systems, endpoints, customer-premise environments, escalation.
- 03
Enterprise Deployment
Discovery, design, provisioning, integrations, QA, UAT, implementation, go-live.
- 04
Professional Services
Complex deployments, escalation ownership, repeatable implementation processes, partner coordination.
- 05
Enterprise Delivery at Scale
Large implementation portfolios, operational systems, capacity, forecasting, Product/Engineering feedback loops.
- 06
Software & AI Systems
APIs, automation, infrastructure, data, local/cloud systems, LLM infrastructure, model routing, agent systems.
- 07
Forward-Deployed Engineering
The full technical range brought together inside real customer environments.
Evidence
Production experience, not just architecture.
15+ Years
Customer-facing technology
Support, network engineering, enterprise deployment, and delivery inside live production environments.
50–80
Concurrent deployments
Carried during hands-on implementation work, weighted toward high-complexity projects.
>99%
SLA compliance
Held across complex multi-site enterprise deployments during major implementation work.
$20M–$30M
Delivery portfolio
Enterprise implementation portfolio under delivery ownership across distributed customer environments.
33%
Reduced delivery timelines
Improved delivery predictability through KPI-driven operations and continuous-improvement frameworks.
30%
Reduced project overruns
Improved delivery predictability through KPI-driven operations and continuous-improvement frameworks.
Now
Current Engineering Focus
Independent engineering and research across Go, Python, and Rust; contract-first APIs and OpenAPI; relational and vector data; Linux and containerized infrastructure; local and cloud inference; model routing; agent coordination; observability; automation; and developer tooling.
Current projects are being developed, tested, documented, and prepared for public release.
Independent Research Engineering Case Study · Ongoing
Luthier
Luthier is an ongoing research engineering project exploring how multiple AI providers, coding agents, local models, repositories, and infrastructure can operate concurrently while remaining observable, controlled, and provider-independent.
Read the research notesContact
Let’s talk.
I’m focused on Forward-Deployed Engineering roles where customer problems require hands-on work across software, integrations, infrastructure, data, networking, or AI.