AI Engineer specializing in agentic AI, RAG pipelines, and LLM systems in production. I turn machine learning into reliable infrastructure at enterprise scale — cutting incident response from hours to minutes and saving millions through automation.
Skills
Languages Python, TypeScript, JavaScript, Bash, SQL
AI / ML LLMs, RAG, Agentic AI, Prompt Engineering, MCP, PyTorch, scikit-learn, TensorFlow, pandas
Frameworks & Tools FastAPI, React.js, PostgreSQL, Prometheus
Cloud & Infra AWS, Azure, GCP, Kubernetes, Docker, Jenkins
Security OWASP Top 10, Penetration Testing, Vulnerability Assessment
Experience
Lead Software Engineer, Walmart Global Tech 2022 — Present
- Deployed a distributed agentic monitoring system across DC server infrastructure; agents continuously track memory, CPU, and storage utilization, autonomously detect anomalies, log diagnostic notes, and page SRE teams with pre-analyzed findings — eliminating idle discovery time entirely.
- Reduced MTTR from ~4 hours to under 30 minutes by ensuring SREs are alerted at anomaly onset and arrive with full context, replacing the legacy discover → escalate → troubleshoot chain.
- Engineered RAG pipelines integrating ServiceNow and internal APIs as LLM knowledge sources, supplying agents with real-time operational context and historical incident signal to inform diagnostics.
- Led the enterprise agentic AI initiative across global logistics operations, reporting architecture and outcomes to director-level stakeholders.
- Eliminated a sequential API bottleneck in a legacy messaging platform by re-architecting recipient resolution as concurrent FastAPI calls; adopted across all North American distribution centers and supporting teams.
- Saved the division $1M+/year by automating technician workflows, increasing team throughput by 40%.
- Enforced OWASP Top 10 compliance across all customer-facing services; eliminated SQL injection vulnerabilities.
- Mentored a network engineer from L1 to L3 through a structured Python and backend curriculum.
Founding Technical Lead, Stealth Startup 2018 — 2022
- Trained a language pattern-recognition model as the core of an AI-led PTSD symptom analysis pipeline.
- Built end-to-end data collection, cleaning, and training-set preparation pipelines from raw sources.
- Architected full-stack applications from requirements through deployment, owning the technical roadmap.
- Documented model architecture and pipeline decisions, enabling reproducibility and onboarding of junior contributors.
Software Engineer, simuwatt 2018
- Acquired and cleaned building energy datasets from web and manual sources, preparing training data for a PyTorch-based energy-auditing model designed to benchmark buildings and recommend cost-reduction improvements.
- Expanded the training database by 30% through web-scraping pipelines; doubled viable in-house data by surfacing overlooked sets through Python parsing programs.
- Automated QA and internal user workflows via Selenium, cutting manual testing overhead and freeing engineering bandwidth for model development.
- Contributed to model fitting in collaboration with the Data Science lead, raising end-of-year user retention by 20%.
Computer Science Tutor, Volunteer 2016 — Present
- Taught C++ through Python OOP via pair programming, a structured syllabus, and project-based milestones.
Education
Full Sail University — B.S. in Computer Science · Salutatorian Florida · 2018