Forward Deployed Engineer (FDE) / Principal Architect
AI can compress the distance from idea to working software. The hard part begins when that software has to integrate with real systems, handle real failures and operate under real business constraints.
I work directly with founders and engineering teams to scope, architect, build, integrate and productionize difficult systems—and stay with the problem until it works in production.
For teams facing an expensive technical uncertainty.
When to bring me in
Choose the moment that sounds most like your system.
The demo works and customers may be arriving, but failure handling, permissions, evaluation, observability, deployment or cost controls have not caught up.
AI Production Readiness ReviewIncidents increase. Delivery slows. Cloud spend grows. You are debating a rewrite without enough evidence about what is actually broken.
Architecture Risk ReviewMemory growth, latency spikes, capacity limits, cascading failures or unexplained instability need containment and evidence before an elegant redesign.
Technical RescueCommon entry points
The work can start with readiness, architecture risk or technical rescue, and continue into hands-on implementation and productionization when the problem requires it.
AI applications or agent systems moving from prototype or early customer usage toward production.
What can break when real users, real data and real failure conditions arrive?
Failure modes, data handling and fallback paths; model and tool boundaries; permissions, evaluation, observability, deployment, scaling and cost.
Prioritized production blockers, a risk map, architecture findings and a remediation plan; critical hardening changes can be implemented where the engagement calls for it.
Systems becoming fragile, expensive, slow to change, unreliable or difficult to scale.
What is actually causing risk, and what is expensive to leave unfixed?
Failure domains and scalability; service and data boundaries; technical debt, deployment risk, observability, cloud cost and modernization priorities.
An architecture risk map, prioritized findings, justified target-state recommendations and a remediation sequence—plus hands-on modernization when needed.
Teams dealing with a production problem that is affecting delivery, reliability, customers, operations or engineering velocity.
How do we control the impact, establish evidence and identify the real failure mode?
Containment and operating behavior across application code, infrastructure, networking, clients, deployment, data and team boundaries.
Contain impact, establish evidence, diagnose across boundaries, implement remediation, observe the result and improve recurrence controls.
How I work
Forward-deployed work starts with the business problem and stays close to the technical outcome.
Sometimes the right answer is a focused architecture review. Sometimes the problem requires writing code, working inside the existing stack, integrating systems, debugging production behavior or staying through rollout.
The responsibility is the same: own the technical problem until there is a production outcome the team can stand behind.
Production-scale proof
These cases show the depth behind forward-deployed work: architecture decisions, cross-boundary diagnosis and production controls where stability, recovery and customer impact were not theoretical.
Featured production case
Former senior architect · Business-critical real-time order delivery
I was responsible for the stability of a business-critical long-connection platform supporting approximately 10 million concurrent client connections. Couriers depended on it for real-time order delivery.
During peak traffic, an abnormal disconnect path left TCP connections incompletely cleaned up and caused progressive memory growth.
Containment came first: controlled rolling restarts let connections migrate across nodes instead of the cluster failing together. I then coordinated backend, Android, iOS, DevOps, architecture and data teams to trace client keepalive behavior, TCP/network behavior and server implementation.
The connection-lifecycle defect was fixed, monitoring and stability controls improved, and the platform continued supporting approximately 10 million concurrent long-lived connections with push delivery around 98%. It remained in use after Ele.me was acquired by Alibaba.
Contain first. Diagnose across boundaries. Fix the system, not just the symptom.
Selected architecture cases
The production rescue case sits within a broader record of architecture decisions made under real scale, reliability and observability constraints.
Physical capacity at the Beijing site was effectively exhausted, while one data center remained a large failure domain.
As Ele.me evolved toward geographic active-active, my work at the mobile / persistent-connection boundary covered zone-aware access, routing and failover considerations, intelligent DNS and server-initiated push location. The company-level architecture was broader; I did not own Ele.me's DRC database-replication platform.
Scale requires explicit locality and failure boundaries—not simple duplication.
Server-side monitoring started too late to explain mobile crashes, interaction failures, networking problems and performance degradation on the phone.
I led mobile architecture and infrastructure work including APM, instrumentation and the client-side monitoring foundation, extending visibility from the app edge through telemetry transport into real-time and forensic paths.
If failure can happen outside the server boundary, observability has to start outside it too.
Sample deliverable
A review should not maximize architectural purity or become a generic recommendation deck. It should make a small number of consequential decisions clearer—and can be the starting point for implementation or productionization when the problem needs it.
Illustrative sample — not based on a specific client engagement.
View a Sample Architecture Risk Review ↗Engineering proof
Tools such as Cursor, Claude and Codex compress the distance from idea to code. They do not remove architecture, failure modes, security boundaries, cost or ownership. Forward-deployed production engineering is what turns the resulting system into something the team can operate. Current work stays tied to evidence, tests, traces, evaluations and explicit limitations.
An evidence-grounded AI workflow that turns meeting transcripts into structured minutes with traceable source spans.
Exact evidence validation, conservative unknown handling, bounded repair and unresolved isolation show how AI output can be inspected rather than blindly trusted.
Current boundaryLocal technical preview; not a production meeting platform or hosted service.
An open-source Kubernetes/K3s control plane for hosting and operating user-owned AI agent runtimes across isolated environments.
Runtime lifecycle, persistent state, tenant and environment isolation, Helm/customer-site packaging and observability address the gap between a laptop demo and an operating system.
Current boundaryPreview and customer-site validation; enterprise SSO and production HA remain roadmap work.
More engineering work: Memory Policy Lablimitations
When the work needs staying power
Sometimes a focused review or rescue is enough. Sometimes the problem needs forward-deployed execution through remediation and rollout; that is where I stay involved as a Fractional Principal Architect.
I work directly with the engineering team, join architecture decisions, write or review critical-path code, integrate systems, sequence remediation, support rollout, observe production behavior and adapt the solution after real-world feedback.
Discuss a continuationI typically work with AI/SaaS founders, engineering leaders, software agencies and China-based technology teams expanding internationally.
Specialized engagement
I also work with Chinese technology companies adapting existing software for international operating environments.
Deployment topology, region/cloud decisions, availability, identity/access, data flows, observability, third-party infrastructure and AI/model deployment.
Earlier international technical/business work covered eight Eastern European markets and was connected to approximately EUR 4M in cumulative sales.
This is technical architecture work, not legal or regulatory consulting.
Discuss International ExpansionThe working identity
I work as a Forward Deployed Engineer (FDE) / Principal Architect: close to the customer, the engineering team, the codebase and the production environment.
I can move from founder or CTO discovery into technical scoping, architecture, implementation, integration and production rollout without handing the difficult parts off at the boundary between “strategy” and “engineering.”
What differentiates this profile from a typical FDE is what happens after the demo. My background includes about 15 years across large-scale production systems, distributed architecture, high concurrency, reliability, incidents, architecture evolution and engineering leadership—alongside current hands-on AI systems work.
Common questions
A few practical answers about how I work with an existing engineering team.
Both labels miss part of the work. I operate forward-deployed: I can work with leadership on discovery, scope and architecture, then stay close enough to the engineering work to build, integrate, debug and productionize the solution.
As hands-on as the problem requires. That can mean architecture and review, but it can also mean writing critical-path code, integrating systems, debugging production behavior, working with infrastructure or helping the existing team ship the solution.
No. I work with the existing team, adding senior technical judgment where the risk is consequential—not providing generic staff augmentation.
When useful, yes—on critical paths and high-risk fixes, not as a replacement for day-to-day product development.
Yes. The question is not who generated the code; it is whether the system has understandable boundaries, failure behavior, operational visibility and maintainable architecture.
Only when evidence shows that a rewrite will reduce an important risk. Usually we isolate the highest-risk paths and improve visibility first.
Not necessarily. We scope the review around the relevant decisions, failure modes and operating evidence.
Yes. When deeper remediation is useful, I can stay involved as an external or Fractional Principal Architect.
Bring me the problem
Tell me what you are trying to ship, what is getting in the way, and what happens if it fails. I can help determine whether the next step is architecture work, hands-on implementation, production hardening, technical rescue—or something simpler. If the problem fits, I stay close to the work through the production outcome.
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