Pranay Modukuru

Senior AI Engineer — Nuremberg

Agentic AI,
built to ship.

I'm Pranay, I design agent systems, orchestration, and the platforms that carry them from prototype into production. After hours, I shoot cinematic travel film and play sports.

Pranay Modukuru cheek to cheek with a caramel-coloured alpaca

01

6+

Years shipping production AI

02

3

Patents in industrial AI

03

1st

AI hackathon, Fraunhofer IOSB-INA

04

2+ yrs

Mentoring DS & ML, TechLabs

6+ years building production AI,
end-to-end.

From novel research to enterprise platforms.
Wherever models meet reality.

At DB Systel I build agentic-RAG for Deutsche Bahn's GenAI platform. Before that, at Tvarit GmbH I co-authored 3 patents in industrial AI that shipped into real manufacturing plants.

Lifelong Learner.

Experience

Building production AI, end-to-end.

DB Systel GmbH Nürnberg, Germany
Senior AI Engineer Sep 2025 – Present

Architecture lead for Deutsche Bahn's enterprise RAG platform, owning product strategy, agentic-RAG delivery, and cross-team technical alignment.

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  • Shipped production agentic-RAG pipeline (LangGraph, FastMCP) with query planning, parallel retrieval, reranking, stable citations, and configurable reasoning effort, with multi-provider LLM support.
  • Authored foundational ADRs on multi-tenant access control, billing, and enterprise MCP integration, drove adopted architecture decisions across three consuming platforms without formal mandate.
  • Own product strategy and roadmap for the platform, initiated the Agentic AI product direction and the Data Access Layer vision, aligning engineering and business stakeholders across teams.
  • Built enterprise MCP tools for chat, knowledge-base configuration, and retrieval, supporting machine-to-machine and on-behalf-of auth flows.
  • Built LLM-model provider-neutral API contract to enable flexible integration with multiple LLM providers.
AI Engineer Mar 2025 – Aug 2025

Built DB's API-first RAG-as-a-Service platform on Azure with retrieval, multi-tenant capability, and the API gateway layer.

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  • Built an API-first RAG-as-a-Service platform (Azure AI Search hybrid + semantic retrieval, Document Intelligence) adopted across multiple Deutsche Bahn business units.
  • Engineered a multi-provider LLM abstraction layer via a dynamic factory pattern, enabling model swaps without changing downstream pipeline stages.
  • Designed the multi-tenant security architecture with auth-claim validation, session guardrails, and multi-layer deletion protection, guaranteeing complete data isolation across tenants.
  • Authored OpenAPI specifications and maintained Azure APIM gateway policies across dev, integration, and production.
Machine Learning Engineer Sep 2022 – Feb 2025

Owned the MLOps backbone including CI/CD, Kubernetes, and ML pipelines.

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  • Automated versioning and multi-environment deployments with GitLab CI, FluxCD, and Helm, eliminating manual release overhead.
  • Provisioned scalable AWS EKS clusters and storage with AWS CDK, delivering identical, production-ready environments.
  • Orchestrated automated ML training and evaluation pipelines with Prefect and MLflow, improving experiment tracking and collaboration.
  • Standardized Docker images and DevSpace templates, reducing developer onboarding from days to hours.
  • Designed and ran technical training workshops to upskill the team on newly adopted infrastructure and workflows.
Tvarit GmbH Frankfurt am Main, Germany
Senior AI Researcher Jan 2022 – Aug 2022

Invented a patented time-series domain-adaptation algorithm, supervised a team of three junior researchers.

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  • Developed a novel time-series domain adaptation algorithm to scale predictive models across machines, securing US Patent No. US12032929B2.
  • Designed automated root-cause and prescriptive-analysis AI features with product teams and domain experts.
  • Supervised three AI researchers and an intern building scalable data processing algorithms for plant-wide AI rollouts across two manufacturing facilities.

US Patent · US12032929B2 · Granted Jul. 2024

System and Method for Cross Domain Generalization for Industrial Artificial Intelligence Applications

Adversarial encoder-decoder architecture enabling predictive models to transfer across machines at a fraction of the data and compute cost. Enables quality prediction on new machines without retraining from scratch.

EP Patent · EP4254087B1 · Granted Mar. 2026

System and Method for Recommending a Recipe in a Manufacturing Process

Physics-AI hybrid system: physics-based simulation generates synthetic training data; ML model optimizes manufacturing recipes under real environmental and machine-state variability.

EP Patent · EP4300229A2 · Application Pending

System and Method for Determining Defect Regions of Products in a Manufacturing Process

Geometry-aware ML: integrates 3D CAD mesh features with process sensor data to predict spatial defect locations in manufactured parts.

AI Researcher Sep 2020 – Dec 2021

Shipped predictive models into live manufacturing plants — 50% scrap reduction for a wheel manufacturer.

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  • Deployed a predictive model prescribing optimal casting parameters for a wheel manufacturer, reducing scrap by 50% and saving €144k annually.
  • Developed an automated time-series framework standardizing data integration and feature engineering, cutting deployment timelines from 50 to 30 days.
  • Built proofs-of-concept for 5+ predictive maintenance and quality-optimization use cases, driving AI adoption for manufacturing clients.
Fachhochschule Südwestfalen Soest, Germany
Research Assistant — Machine Learning Feb 2019 – Aug 2020

Deep learning research on multivariate sensor data, novel regularization against catastrophic forgetting.

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  • Developed deep learning algorithms and feature pipelines for multivariate sensor data, optimizing computer vision and predictive maintenance systems.
  • Developed a novel regularization technique and multi-headed neural network, reducing catastrophic forgetting from 6.5% to 1.0% on sequential classification tasks.

Projects

Projects Showcase

Personal Project · Sports Tech

Cricket S&C Dashboard
snc-dashboard

Workload & readiness tracking for a T20 cricket squad with ACWR, bowling load, and RPE, with Telegram check-in reminders.

  • ACWR + player readiness tracking
  • Telegram bot check-ins
  • One-stop dashboard for an S&C coach
PythonFastAPIStreamlitSQLiteTelegram BotRailway

Personal Project · Open Source

School Timetable Auto-Scheduler
GVP-MLBT-Scheduler

A browser-based constraint-aware school timetable generator.

  • Easy configuration
  • Constraint-based scheduling
  • 3 timetable views
JavaScriptES6 ModulesHTMLCSS

Personal Project · Open Source

Agentic PersonalFinance Pipeline
pf-ops

An LLM-based extraction and classification pipeline for transactions straight from raw bank PDFs/CSVs feeding a dashboard.

  • 3 banks, zero parsers
  • SHA256 idempotency
  • Browser-only dashboard
PythonLLMReactTypeScript

Education

First principles, first.

Education

M.Sc.

Apr 2018 – Jun 2020

Grade: 1.6

Systems Engineering and Engineering Management

Fachhochschule Südwestfalen · Soest, Germany

Machine Learning · Deep Learning · Signal Processing · Advanced Control Systems

B.Tech.

Sep 2013 – Apr 2017

Grade: 1.6

Electrical and Electronics Engineering

Jawaharlal Nehru Technological University · Hyderabad, India

Volunteer Experience

  • Winner, Anomaly Detection Hackathon, AI Challenge Days 2020, Fraunhofer IOSB-INA
  • Mentor, Data Science & ML, TechLabs Düsseldorf (May 2021 – Apr 2023)

Skills & Stack

How I actually build things.

01Agentic & GenAI

  • LangGraph
  • FastMCP
  • LangChain
  • Multi-Agent Systems
  • RAG & Agentic-RAG
  • Eval & Monitoring
  • OpenAI API
  • Claude / Anthropic SDK
  • Azure AI Foundry
  • Azure AI Search
  • Azure Doc Intelligence

02Languages & Frameworks

  • Python
  • TypeScript
  • SQL
  • Shell
  • C
  • FastAPI
  • PyTorch
  • TensorFlow
  • Keras
  • scikit-learn
  • Ray
  • Pandas
  • NumPy

03Cloud & Infra

  • Azure (Cosmos DB, Functions)
  • AWS (EKS, S3, SageMaker)
  • Docker
  • Kubernetes
  • DevSpace
  • GitLab CI
  • FluxCD
  • AWS CDK
  • Helm
  • Bicep

04MLOps & Data

  • MLflow
  • DVC
  • Prefect
  • PySpark

05Domains

Large Language Models · Time-Series Forecasting · Computer Vision · Deep Learning · Domain Adaptation

After Hours

Frames, Courts, & Creases.

Same obsessive eye for craft but different medium. I shoot travel film at 24fps, chasing the blue hour from Nuremberg to wherever the light is interesting.

@pranay.studios on Instagram

Cricket

All-rounder

Playing club cricket in Germany. Batting middle order, keeping wickets, bowling medium pace. The sport that followed me across continents.

Badminton

Singles & doubles

Weekly court sessions chasing drop shots and smashes. Fast-twitch reflexes, strategic patience. What I started to play for my wife.

Contact

Let's build something
worth shipping.

Open to senior AI engineering roles, consulting, and interesting collaborations. Drop me a line, I get back within a day.