Career
Experience Timeline
4+ years across full-stack software engineering, ML engineering, backend platforms, and agentic systems.
Career summary
This page is optimized for evaluating scope, ownership, and operating range.
The strongest signal across these roles is engineering ownership: turning ambiguous product and platform problems into shipped systems. The work ranges from customer-facing reliability and internal developer tooling to RAG systems, observability, cloud infrastructure, and multimodal ML evaluation.
4+
Years across AI, platform, and full-stack systems
75%
Manual upkeep reduction from developer tooling
25%
MTTR reduction from observability pipeline
14%
Engagement lift from Evidenza ad signals
Full-stack systems
Built React, Node.js, FastAPI, and MongoDB/Postgres-backed tools used by engineering teams and production support workflows.
ML-backed products
Built RAG assistants, VLM/LLM-judge workflows, NLP services, and multimodal scoring systems with measurable outcomes.
Platform reliability
Owned customer-facing platform reliability, observability pipelines, cloud infrastructure, and support systems.
AI Engineer (Intern)
Evidenza · Brooklyn, NY
Top impact
Built LLM-as-judge persona generation and multimodal ad-scoring pipelines, reaching 80% trait coverage and driving a 14% engagement lift in A/B testing.
- Built a self-improving persona generator adapted from Google’s AlphaEvolve pattern, where generation code is automatically rewritten under LLM-as-judge scoring.
- Reached 80% trait coverage on long-tail customer profiles, expanding the range of modeled customers beyond the prior persona-generation pipeline.
- Built a multimodal VLM-as-judge pipeline to catalog and score competitor advertisements for creative intelligence workflows.
- Fed ad-quality signals into a creative recommendation flow that drove a 14% engagement lift in A/B testing.
- Worked across Python, FastAPI, MCP, prompt engineering, LLM-as-judge evaluation, and multi-step agent orchestration.
Sr. Software Development Engineer
CVS Health · New York, NY
Top impact
Built production RAG and VLM-backed systems, deflected 16% of support tickets, cut resolution time by 20%, and reduced platform downtime by 12%.
- Built a transformer-based closed-loop image-caption pipeline that generated captions with a Hugging Face vision-language model and used an LLM judge prompted for CVS brand framing.
- Wrote back only captions that beat the existing text, raising catalog coverage by 18%.
- Built a self-service RAG assistant over ticket history and internal documentation, deflecting 16% of tickets and cutting resolution time by 20%.
- Owned on-call reliability for customer-facing platform systems including Digital Blocks 2.0 and Previews.
- Reduced downtime by 12% across customer-facing core platform systems.
- Worked across RAG, GCP, Terraform, ArgoCD, OpenTelemetry, and GitHub Actions after promotion from Digital Development Engineer III.
Digital Development Engineer III
CVS Health · New York, NY
Top impact
Built Node.js internal developer tooling, adopted by multiple CVS engineering teams, and cut manual upkeep by 75%.
- Built a leadership dashboard surfacing cross-team allocation and throughput metrics, adopted as the primary planning view by 4 teams.
- Built and shipped full-stack internal developer tooling in Node.js used by multiple CVS engineering teams.
- Automated stateful workflow lifecycle logic including state transitions, assignment, and cross-board synchronization, cutting manual upkeep by 75%.
- Built a Grafana observability pipeline backed by Postgres with batched export to GCS.
- Cut incident MTTR by roughly 25% through better observability and incident triage visibility.
- Worked across Hugging Face, Node.js, MongoDB, GCP, and Terraform.
Advanced Software Developer
Aetna Health · New York, NY
Top impact
Built Node.js and MongoDB-backed internal automation systems, migration workflows, and platform health checks.
- Built Node.js and MongoDB-backed internal automation tools for engineering operations.
- Developed automation scripts and service workflows that reduced repetitive manual QA and platform-maintenance work.
- Supported internal tooling, migration workflows, and validation systems used before the CVS Health promotion path.
- Worked across Node.js, MongoDB, automation scripting, API services, and internal platform health checks.
Academic Background
New York University
Courant Institute
M.S. Computer Science (AI)
Trine University
B.S. Software Engineering & Mathematics