ASAniket SalveENGINEERING · ARCHITECTURE · AI
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Stuttgart, Germany / Building since 2016

Hi, I’m
Aniket Salve.

Lead AI Engineer

I architect AI/ML solutions, Industrial IoT applications, and enterprise data platforms for automotive and industrial environments.

Explore my work View résumé
Aniket Salve
Connecting ideas.
Building useful systems.
AI/ML ARCHITECTURECLOUD & MLOPSINDUSTRIAL IOT
01 / About

Complex problems.
Practical solutions.

Technology leader and solution architect delivering AI/ML, Industrial IoT, cloud-native applications, and enterprise data platforms. I define technical roadmaps, translate data science into scalable software, and align engineering delivery with business outcomes.

My work spans AWS, MLOps, CNN-based computer vision, Generative AI, and data integration. I mentor developers and data scientists, establish engineering standards, and coordinate teams and stakeholders across Europe and Asia.

5,000+Users across four business units
~80%Less manual requirements-comparison effort
€400k+Savings over two years

02 / Selected work

From challenge
to working system.

Selected engineering work.
The problem, the approach, and the result.

01Solution architecture

Automated requirements comparison

Comparing requirements and identifying similarities in 3–5 days instead of months.

  • Requirements comparison
  • Automation
  • Solution architecture
Explore the work

The challenge

Manual requirements comparison required months of work and substantial effort.

My approach

Architected an automated solution to compare requirements and identify similarities.

The result

Reduced months of manual comparison work to 3–5 days and cut manual effort by approximately 80%.

02Technical leadership

Enterprise platforms & intelligent automation

Delivering in-house software and driving AI adoption for enterprise engineering.

  • AWS
  • Generative AI
  • Agentic AI
  • Knowledge Graphs
  • MLOps
Explore the work

The challenge

The organization needed a scalable alternative to a third-party solution, aligned with business-unit and organizational KPIs.

My approach

Architected and delivered an in-house solution. Lead AI and enterprise data-platform initiatives, develop LLM-assisted documentation and requirements workflows, and establish cloud-native engineering practices with AWS, GitHub, DevOps, and MLOps.

The result

The in-house solution generated more than €400,000 in savings over two years. The broader AI, data-platform, and digital-transformation initiatives serve 5,000+ users across four business units.

03AI engineering

Docs-as-code & AI-assisted requirements

Using LLM agents for documentation validation and Generative AI for requirements drafting.

  • Docs-as-code
  • LLM agents
  • Generative AI
  • Knowledge Graphs
Explore the work

The challenge

Documentation validation and requirements drafting needed support within engineering workflows.

My approach

Developed a docs-as-code workflow using LLM agents to validate documentation and make changes based on the results. Used Generative AI to draft requirements from information in a knowledge graph.

The result

Enabled AI-assisted documentation validation, changes, and requirements drafting within the workflow.

04End-to-end delivery

Industrial IoT & computer vision

Building production analytics and machine-learning capabilities for industrial operations.

  • Industrial IoT
  • CNNs
  • Computer vision
  • Python
  • MLOps
Explore the work

The challenge

Industrial operations needed reliable device monitoring, automated issue detection, and safety-risk detection.

My approach

Delivered an Industrial IoT and advanced analytics platform from solution design through operational support. Built MLOps workflows and deployed CNN-based computer vision for industrial safety, with Java Spring Boot and Python services and Angular interfaces.

The result

Increased device availability to nearly 90% through improved monitoring, automated issue detection, and reliable production operations.

03 / Expertise

A systems mindset.
A hands-on approach.

01

AI/ML architecture

Production-grade AI/ML solutions, Generative AI, Agentic AI, Knowledge Graphs, and CNN-based computer vision.

02

Cloud & MLOps

AWS cloud architecture, model training and deployment, production monitoring, DevOps, and reliable automation.

03

Data & Industrial IoT

Enterprise data platforms, data integration and migration, analytics, and Industrial IoT applications.

04

Technical leadership

Technical roadmaps, cross-functional delivery, team mentoring, stakeholder management, and executive communication.

Tools behind the work

Cloud & deliveryAWS · Docker · GitHub · DevOps · MLOps

AI/MLMachine Learning · Generative AI · Agentic AI · LangChain · Computer Vision · CNNs

Programming & frameworksPython · Java · Angular · Spring Boot

Data & integrationAnalytics · Data Migration · Data Pipelines · MySQL · REST APIs

Architecture & methodsSolution Architecture · Agile · Scrum

04 / Career

Built on experience.

Jul 2022 — Present

Robert Bosch GmbH

Technical Lead | Solution Architect

Stuttgart, Germany

  • Lead AI, enterprise data-platform, and digital-transformation initiatives serving 5,000+ users across four business units.
  • Define solution architectures and multi-phase roadmaps balancing business goals, maintainability, scalability, governance, and delivery constraints.
  • Architected automated requirements comparison and similarity identification that reduced months of manual work to 3–5 days and cut manual effort by approximately 80%. Delivered an in-house solution generating more than €400,000 in savings over two years.
  • Developed a docs-as-code workflow using LLM agents to validate documentation and make changes based on the results. Used Generative AI to draft requirements from knowledge-graph information. Establish AWS, GitHub, DevOps, and MLOps engineering practices.
  • Coordinated seven data scientists and software engineers across Germany, India, and Vietnam, plus three external vendor companies. Mentor teams, deliver training, and establish engineering standards and user communities.

Sep 2020 — Jul 2022

DEKRA Digital GmbH

Senior Software Developer (Data Scientist)

Stuttgart, Germany

  • Delivered an Industrial IoT and advanced analytics platform end to end, from solution design through production support; increased device availability to nearly 90%.
  • Built MLOps workflows for training, deployment, monitoring, and continuous improvement. Developed and deployed CNN-based computer vision for industrial safety and workplace risk detection.
  • Engineered Java Spring Boot and Python services and Angular interfaces. Worked with the CTO on architecture, stakeholder alignment, executive presentations, customer demonstrations, and pre-sales.

Apr 2020 — Aug 2020

ETAS GmbH

Software Developer Intern

Stuttgart, Germany

  • Developed frontend and backend components and an Electron desktop application; performed data analysis for management dashboards.

Feb 2019 — Mar 2020

DEKRA Digital GmbH

Software Developer Intern

Stuttgart, Germany

  • Developed web applications and contributed to a vision-processing solution focused on improving safety.

Jul 2016 — Jul 2018

HCL Technologies Ltd

Software Developer

Pune, India

  • Contributed to R&D software design and high- and low-level design documentation.
  • Developed REST APIs and Python data services using MongoDB, MySQL, and Elasticsearch. Built Angular interfaces in an Agile development environment.
Download résumé

PDF · Lead AI Engineer résumé.

05 / Education

Foundations
for the work.

2018 — 2020 / Germany

MSc, Data Analytics and Decision Science

RWTH Business School, Aachen

2012 — 2016 / India

BE, Electronics and Telecommunication

Savitribai Phule Pune University

Professional training

iSAQB Trained Software Architect

Scrum Product Owner

Scrum Master

Languages

English · German (B1) · Hindi

06 / Get in touch

Let’s build
something useful.

Have an engineering challenge or a role in mind?
I’d be glad to hear from you.

LinkedIn ↗View résumé ↗