Patent-backed AI Product Leader

AI safety, edge inference, and deterministic governance for 40M–70M+ devices.

I design and ship safety-first AI systems on top of large broadband and Wi-Fi fleets—defining how we gate releases, score risk, and turn telemetry into decisions that leaders can trust.

40M–70M+ devices governed8 USPTO non-provisional patentsEdge AI · Safety · Governance
40M–70M+
Devices governed across broadband & Wi-Fi platforms
8
USPTO-filed non-provisional patents as sole inventor
Edge AI · Safety · Privacy
Core focus
12+
Years building reliability, safety, and rollout governance

About

I build deterministic, safety-first AI systems at scale. At Comcast, I've led AI safety, rollout governance, and reliability for broadband and Wi-Fi platforms serving 40M–70M+ devices—where every regression becomes real customer impact and multimillion-dollar SLA risk.

My work focuses on defining product strategy and technical architecture for edge inference, alignment guardrails, and telemetry-driven risk scoring. I own the end-to-end governance stack: safety bars, rollout gates, anomaly thresholds, compliance checks, and privacy-preserving logging across distributed telemetry pipelines.

I've unified 50+ engineers across Product, ML/DS, SRE, QA, Field Ops, Security, and vendors under a standardized evaluation model— reducing regression recurrence by 28%, improving triage and recovery by 35%, and giving leaders a clear view of safety vs. velocity on every high-stakes release.

I'm also pursuing a Doctor of Engineering (DEng) at Penn State to deepen my work at the intersection of AI safety, product strategy, and innovation management, while building a patent-backed portfolio across Edge AI, alignment, and deterministic governance.

What I build

Edge AI & Offline Intelligence

LLM systems that run fully offline on edge devices, respect data boundaries, and keep working when the network doesn’t—combining model compression, on-device alignment debugging, and self-forgetting memory.

Deterministic Safety & Governance

Rule-based risk engines for hallucination, bias, latency, and policy violations. Deterministic where it matters, ML where it’s safe—always with an audit trail.

Product Strategy & Execution

Turning patents and research into roadmaps, prototypes, and launch-ready AI features—grounded in reliability, compliance, and real production constraints.

Skills & Stack

AI Safety, Governance & Privacy

  • AI safety & alignment
  • deterministic rule engines
  • risk triage and scoring
  • privacy-preserving logging
  • offline inference
  • RAG, embeddings, ONNX, quantization
  • explainability (XAI)

Product & Strategy

  • vision & strategy
  • multi-year roadmaps
  • PRDs and requirements
  • KPIs / SLIs / SLOs
  • rollout governance & go/no-go
  • experimentation & A/B testing
  • VP/SVP stakeholder management

Platforms & Systems

  • RDK-B, broadband, Wi-Fi / 6 GHz
  • DHCP, DSCP & traffic prioritization
  • CI/CD and observability
  • SLA/SLO design
  • high-availability distributed systems

Engineering, Leadership & Execution

  • Python, FastAPI, Docker, Splunk, ElasticSearch, Next.js, Git, ONNX Runtime
  • cross-functional alignment (Product, ML/DS, SRE, QA, Field Ops, Security)
  • multi-quarter OKR planning
  • incident triage & postmortems
  • executive communication & decision briefs