BASED IN NEW YORK


applying AI
at scale.

Currently at Fiserv, designing and building agentic AI analytics tooling end-to-end.

See my work Get in touch
40.7128° N 74.0060° W
01 About

A back-end engineer with an AI focus.

Michael Walter
Specs Michael Walter
Based
New York, NY
Role
Applied AI Developer
Company
Fiserv
Education
UT Austin, '23

I work across the full stack of a modern AI product: semantic data layers, multi-agent orchestration, text-to-SQL pipelines, and the frontends that people want to use. Before that, I modernized legacy Java systems and led security compliance work across a portfolio of enterprise apps. I care about shipping things that hold up in production, well-architected, well-tested, and built with security as a first-class concern.

02 Experience

Where I've worked.

Fiserv Berkeley Heights, NJ Apr 2026 — Present

Applied AI Developer · Senior Professional I

  • Lead technical strategy as the sole developer on a small cross-functional team, identifying client onboarding pain points and architecting a tailored internal AI analytics platform as the solution.
  • Built a unified data layer consolidating 20+ data points across 3 databases, powering a Cortex Agents application that automates data summarizations and generates visualizations via a text-to-SQL pipeline using Cortex Analyst.
  • Built and own all layers of a Streamlit on Snowflake application spanning semantic layer architecture, data transformations, and frontend design, iteratively shipping features toward production release.
Fiserv Berkeley Heights, NJ Jul 2025 — Mar 2026

Applied AI Developer · Technology Analyst II

  • Enhanced a client-facing Snowflake Cortex multi-agent framework orchestrating specialized agents across querying, summarization, and visualization, built on top of a FastAPI app with a React frontend.
  • Researched and advised on integrating Playwright E2E testing into the GitHub Actions CI/CD pipeline.
  • Participated in red teaming LLM-driven applications company-wide to identify and mitigate security risks.
Fiserv Berkeley Heights, NJ Jan 2024 — Jul 2025

Java Backend Engineer · Technology Analyst I

  • Built a recurring process to migrate and transform millions of account records from legacy to modern platform.
  • Modernized legacy Java apps migrating from Struts to Spring, SVN to Azure DevOps, and configuring Maven.
  • Regularly led vulnerability scans and maintained CI/CD pipelines for 10+ apps to achieve security compliance.
Wonderful Los Angeles, CA May 2022 — Aug 2022

Software Intern

  • Partnered with project managers and clients to align requirements and prioritize features for business objectives.
  • Performed QA and pre-launch testing on iOS applications and websites, then reported findings.
  • Organized workflows by creating Asana boards while assisting front-end developers with debugging.
03 Selected projects

Things I've built.

AI · Personal Project

AI Task Manager

An AI task manager that transforms vague objectives into prioritized, time-aware to-do lists, simulating a personal project manager using prompt chaining and structured outputs.

Python Claude API Prompt Chaining
04 Skills

What I work with.

Backend & AI/01

  • Python
  • Java / Spring
  • FastAPI
  • Django
  • Apache Struts
  • Swift
  • Agentic AI
  • LLM Security
  • n8n

Data & DevOps/02

  • SQL
  • Snowflake / Cortex
  • Azure DevOps
  • AWS
  • GitHub Actions
  • Maven
  • JBoss

Frontend & Mobile/03

  • React
  • JavaScript
  • HTML / CSS
  • Streamlit
05 Education

Where I studied.

May 2023

The University of Texas at Austin

B.A. Human Dimensions of Organizations · Ampla Cum Laude

Interdisciplinary major blending liberal arts with technical and analytical coursework. Dean's Honors List.

Spring 2020 — Dec 2022

The University of Texas at Austin

Minor in Elements of Computing · Computer Science

Intensive programming and computation program covering scientific computing, graphics & visualization, networking, databases, and software engineering. Built standalone applications in multiple languages.

Spring 2023

DeepLearning.AI · Stanford Online

Supervised Machine Learning: Regression and Classification

Built regression and classification models in Python using regularization, feature scaling, vectorization, and model evaluation techniques.

06 Contact

Let's build something worth building.

If you'd like to talk about applied AI, back-end systems, or anything in between, I'd love to hear from you.