Applied AI · Software engineering

Joseph Haenel

I build and operate
enterprise AI systems.

From stakeholder discovery and architecture to deployment and ongoing operation. My work spans AI applications, agent workflows, retrieval systems and machine learning.

1,000+employees have used DotChat
since January 2025
200+data pipelines covered
by monitoring I added
End to endapplication ownership
from design to operation

01 / Selected work

Systems built for everyday use.

Selected work at Dot Foods. I owned the applications and ML workflows end to end, working with infrastructure teams on Azure provisioning, DNS and networking.

Enterprise AI platform

DotChat

Production

An enterprise AI platform used by more than 1,000 employees since January 2025.

I built durable chat execution with queued jobs, idempotent requests and reconnect recovery. Permission-aware SharePoint retrieval uses delegated Microsoft Graph access, resumable indexing and atomic activation of completed indexes.

Release workflows include database migration checks, controlled traffic promotion and rollback. I added OpenTelemetry instrumentation for model and tool execution, including a Monte Carlo evaluation, to support debugging and cost visibility.

I also built assistant feedback analytics: clustering unanswered questions, tracking review status and providing location-filtered dashboards to help business teams identify gaps in assistant responses.

477 active employeesMeasured August 29–September 27, 2026.

A self-service assistant-builder pilot enabled 10 employees to create 15 custom assistants, with approval, version history and sharing controls.

Azure AI · Python · PostgreSQL / pgvector · Redis · Microsoft Graph · OpenTelemetry

Knowledge capture

DotLore

Deployed pilot

A knowledge-capture platform with evidence and human review built into the workflow.

I built and deployed the application using FastAPI, React and hybrid retrieval. Evidence-linked extraction, human approval and durable background jobs support the capture process, with Okta authentication for access.

FastAPI · React · Hybrid retrieval · Durable jobs · Okta OIDC

Machine learning operations

Warehouse forecasting

Planning workflows

Forecasting workflows designed to be evaluated, reproduced and operated reliably.

I own warehouse forecasting in Python and Snowflake. The work includes reproducible backtests, shadow evaluations, incomplete-data checks and baseline fallbacks for planning feeds.

Python · Snowflake · Backtesting · Model evaluation · Data quality

Employee development

AI Career Coach

Recommendation application

An internal career-matching application refined through employee testing.

I built job-data ingestion and embedding-based matching, then adjusted the weighting of education and work experience in response to tester feedback. The application work included session management, backend and interface integration, and PDF career plans.

Later work brought Career Coach into DotChat and added a dashboard, with a redesign that keeps submitted career information local to the request.

Python · Embeddings · Recommendation systems · Application integration

Governed agent workflows

Intake Studio

Working prototype

AI-assisted project intake with human review before work enters Jira.

I built an authenticated application for refining stakeholder requests and preparing structured handoffs. Reviewers approve Jira Epic and Story creation, with context for downstream coding agents included in the handoff.

Next.js · PostgreSQL · Okta OIDC · Jira integration · Human approval

Earlier applied work

Driver fuel optimization

Constrained-path optimization with Azure Functions and Snowflake, including fuel-data ingestion, cleaning, geocoding, validation and failure notifications.

Business case: $1M+ estimated annual savings.

Customer-service agent

Retrieval and OCR with DB2 and Azure/Snowflake MCP integrations, authenticated data access and business-specific tool selection.

Business case: $200K estimated annual cost avoidance.

Warehouse retention

A deployed LightGBM model for warehouse employees, in operational use for over a year.

Business case: $1.5M+ estimated annual savings.

Financial figures are estimates from business calculations, not measured or realized savings.

02 / Experience

From analysis to applied AI.

May 2026 — Present

Associate AI Engineer

Dot Foods

Own enterprise AI applications and ML systems, including DotChat, DotLore and warehouse forecasting. Build retrieval and agent workflows, feedback analytics, release processes and operational tooling. Create solution designs in LeanIX, use Alation for data governance, and investigate Dagster Cloud pipeline failures during on-call support.

Aug 2024 — May 2026

Data Analyst

Dot Foods

Built customer-service and fuel-optimization applications, including Azure and Snowflake MCP integrations. Added xMatters monitoring across 200+ data pipelines, job-status tracking, failure notifications and GitHub Actions workflows. Built Career Coach matching and PDF career plans, refining recommendations from tester feedback.

May — Aug 2024

Data Analytics & Machine Learning Intern

Dot Foods

Developed and deployed a LightGBM retention model for warehouse employees.

Jul 2023 — Dec 2024

Undergraduate Research Assistant

Southern Illinois University Edwardsville

Implemented CNN models in Keras and TensorFlow for leaf-disease detection and investigated genomic associations with autism comorbidities.

View research poster

03 / Technical skills

The tools behind the work.

Languages

Python, SQL, TypeScript, JavaScript

AI & machine learning

Azure AI Foundry, Azure OpenAI, Responses API, RAG, MCP, embeddings, LightGBM, scikit-learn, PyTorch

Backend & data

FastAPI, Flask, PostgreSQL / pgvector, Redis, Snowflake, Docker, Azure Container Apps, CI/CD, Microsoft Graph, Okta OIDC

Operations & observability

OpenTelemetry instrumentation, xMatters monitoring, Dagster Cloud on-call troubleshooting, Monte Carlo evaluation

Solution design & governance

LeanIX for solution designs; Alation for data governance

Additional exposure

WorkIQ integration research; limited familiarity with ThoughtSpot and Sigma BI tools

04 / Education

A foundation in computer science.

In progress · Expected May 2028

Master of Computer Science

University of Illinois Urbana-Champaign

GPA: 4.0 · Studying alongside full-time engineering work.

Completed December 2024

B.S. Computer Science

Southern Illinois University Edwardsville

Magna Cum Laude · Honors · Provost Scholar

05 / Contact

Let’s talk about
what you’re building.

Interested in AI engineering opportunities in Germany.
Seeking relocation to the Rhein-Main or Rhein-Neckar region.