Abbas Kazmi

whoami

Abbas Kazmi

Software Engineer

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👋 Hey, I'm Abbas! I'm a Software Engineer at Adobe, where I get to work across agentic search, backend infrastructure, and full-stack development to help ship AI-powered features people actually rely on. Before this I interned across Adobe's checkout and eCommerce systems, and had a blast serving as Technical Director for HackDavis while studying Computer Science at UC Davis with a focus on deep learning.

Outside of work, you'll usually find me on a soccer field or pickleball court, or catching up on movies. Always happy to chat, so feel free to reach out!

experience
Adobe — Software Engineer
[2024.08 — present]
New York, NY
  • Built an agentic search service and Adobe's first context-aware recommendation app by having agents select search facets from document and parent-app context, driving adoption across 380 customer accounts.
  • Engineered an agent tracing pipeline capturing 100K+ monthly traces via LangFuse, then fine-tuned agent LLMs on the labeled data, boosting task success rate from 25% to 70% and cutting prompt tuning from weeks to hours.
  • Built an agent evaluation system with guardrails against unstructured outputs and silent failures, increasing result relevance by 45% and cutting undetected failures by 75%.
  • Built an automated security alerting system that detects and strips prompt injection and malicious content before it reaches the LLM, cutting triage time 60% and catching 20K+ risks monthly.
  • Architected a reusable agent orchestration harness in CrewAI and LangGraph, standardizing cost tracking and observability across teams and cutting agent setup time from days to minutes.
  • Built AI-enhanced UI features in TypeScript and ReactJS, including recent-search components and suggested-content panels for agentic experiences.
  • Developed internal and public-facing APIs in Java and FastAPI to support AI-powered features and scalable backend services.
  • Deployed cloud-native infrastructure using Azure Functions, Blob Storage, and AWS Bedrock to run production AI workloads.
Adobe — Software Engineer Intern, Machine Learning
[2023.06 — 2023.09]
San Jose, CA
  • Spearheaded development of machine learning models to predict user checkouts by leveraging high-frequency clickstream data.
  • Led end-to-end pipeline development on Databricks using SQL and Python to transform raw data into actionable insights.
  • Achieved ~93% accuracy models through various machine learning methods, integrated via meticulous software engineering.
  • Planned model deployments and microservice integrations to enable real-time predictions on Adobe.com.
Adobe — Software Engineer Intern, eCommerce Experiences
[2022.06 — 2022.09]
San Jose, CA
  • Developed a testing framework for the Adobe Checkout team to validate new, existing, and error scenarios using mock data.
  • Restructured the checkout application's distributed system design by incorporating AWS S3 and EC2 to store and return mock responses.
  • Designed a testing API in TypeScript with Apollo GraphQL that integrates within existing APIs for seamless testing.
  • Implemented Redis caching through an ioredis server for fast retrieval of repeated calls and log analytics.
HackDavis — Technical Director
[2022.09 — 2024.09]
Davis, CA
  • Served as Technical Director for HackDavis, one of the largest collegiate hackathons in California, where over 950 students, creators, and leaders come together to build for social good.
education
University of California, Davis
B.S. Computer Science and Engineering — Concentration in Deep Learning & AI
Deep Learning, Computer Vision, Systems Programming & Operating Systems, Computer Architecture, Algorithm Design & Analysis, Software Engineering
stack
agent / AI frameworks
LangChainLangGraphCrewAI LangFusePyTorchAWS Bedrock Azure OpenAI
languages
PythonJavaTypeScript C++Go
tools / platforms
LinuxDockerSQL MongoDB AtlasGraphQLApache Spark React.jsAWSAzure