flagship case studies documented in detail
Engineering Portfolio
I design AI products with systems-level rigor and production discipline.
My work spans end-to-end AI pipelines, LLM-powered applications, OCR and vision systems, eBPF-based telemetry, real-time voice bots, forecasting platforms, cloud infrastructure, and deployment tooling. I usually own the full path: architecture, training, evaluation, backend APIs, infra, rollout, and operational hardening.
additional projects across AI, infra, security, voice, and product engineering
core engineering tracks delivered end to end
Delivery style
Architecture to operations
I optimize for durable systems, not one-off demos.
Preferred scope
Multi-component products
APIs, workers, models, storage, observability, and rollout plans.
Operating principle
Pragmatic + measurable
Trade-offs are explicit, metrics are visible, and failure modes are handled.
Flagship Work
Selected projects that define how I build
These case studies show the kind of work I usually handle: multi-component architectures, production pipelines, model experimentation, traffic control, deployment, and real operational constraints.
Haier AI Platform
Built multiple use cases under one program: retail store compliance, invoice extraction, legal document extraction, async processing, model routing, dashboarding, traffic shaping, Bedrock/Gemini integration, Redis-backed control plane, PostgreSQL persistence, and production monitoring.
- Designed and hardened inference pipelines and supporting infrastructure.
- Worked on model strategy, evaluation, invalid-image gates, and backend failover logic.
- Built admin and reporting capabilities for cost, throughput, usage, and operational visibility.
eBPF Data Flow Agent, Nucleus & Backend
Designed a host-based outbound data-flow visibility platform to inspect server-side requests, classify traffic, study runtime-specific interception paths, move kernel events to user space efficiently, and relay captured data from agent to nucleus through Redis so the host-side agent stayed lightweight and decoupled from heavier processing.
- Explored ring-buffer and other kernel-to-user-space transport approaches.
- Worked on Python, Node.js, Java, and .NET interception directions for pre-encryption visibility.
- Used Redis as the practical transport layer between agent and nucleus for buffering, decoupling, and operational simplicity.
Air India Voice Bot Workflow
Built a voice workflow around FreeSWITCH, mod_audio_fork, ESL, separate playback control, NLU,
Air India API orchestration, and response-audio generation. The system streamed live call audio out, processed
intent externally, then played generated bot responses back into the call.
- Separated media outflow, bot intelligence, and ESL-driven playback return path.
- Implemented intent operations and workflow execution through API-backed voice automation.
- Created a practical call-control architecture rather than a simple demo bot loop.
Core Expertise
Where I usually contribute the most
AI systems & LLM workflows
I build production pipelines around LLMs, vision models, OCR systems, asynchronous job flows, validation layers, evaluation loops, prompt design, routing logic, and enterprise backend integration.
Vision, OCR & model operations
I work on image quality gates, wrong-category detection, OCR extraction, model training pipelines, YOLO-based detection paths, PaddleOCR workflows, evaluation design, and structured output mapping for downstream systems.
Kernel, security & observability engineering
I explore eBPF-based capture, runtime interception, SSL/TLS boundary visibility, agent architecture, event transport, container-aware deployment, and backend intelligence around outbound data-flow analysis.
Voice automation & conversational systems
I design telephony-to-bot workflows, audio streaming chains, speech handling, NLU orchestration, retry logic, TTS playback paths, and backend integration for real operational call flows.
Cloud infra, APIs & platform hardening
I usually handle production runtime setup too: Nginx, workers, Redis queues, Postgres schemas, API auth, multi-worker tuning, S3 flows, Docker images, Kubernetes deployment, and admin/monitoring planes.
Data platforms & forecasting systems
I also work on forecasting and analytical data products, building data contracts, feature layers, baseline models, causal features, and business-oriented forecasting workflows for real enterprise use cases.
How I Work
My usual engineering pattern
Map the real problem
I usually start by narrowing the actual bottleneck: model accuracy, throughput, infra, latency, data quality, or runtime constraints.
Explore multiple approaches
I compare practical routes instead of forcing one tool. That may mean trying LLM-only flows, classical gates, runtime interception, or distributed queue designs.
Build the full pipeline
I usually own APIs, worker orchestration, model integration, storage, dashboards, load behavior, and deployment scripting together.
Harden for production
I care about failure modes, fallback logic, caching, rate limiting, monitoring, and making the system usable in real environments, not just in a demo.
Project Library
Broader work across AI, systems, platform engineering, and automation
Use the filters to focus on a track. The library combines flagship and additional projects so the website feels like a full profile, not just a small case-study list.
Downloads
Attached case studies
Retail compliance, OCR workflows, legal extraction, infra, control plane, failover, monitoring.
eBPF Data Flow Agent & Nucleus PDF case studyKernel tracing, Redis transport to nucleus, deployment portability, container-aware observability, backend platform.
Air India Voice Bot Workflow PDF case studyFreeSWITCH, mod_audio_fork, ESL playback, NLU, API orchestration, generated response audio.