Manoj Issrani

About Manoj Issrani

I am a technology and architecture leader with 20 years of experience building and scaling embedded, connected, and intelligent systems across agricultural, automotive, and industrial domains.In my current role, I lead end-to-end system engineering for complex embedded machine platforms, spanning embedded software, middleware, and Qt/QML-based in-cab user interfaces. I have driven multiple platform-level innovations, including modern ECU communication architectures, multidrop 10BASE-T1S Ethernet adoption, and delivery of interoperable, third-party-compliant control solutions, enabling scalable, reusable, and high-performance system designs. I also lead high-definition data communication platforms and in-cab display systems across multi-controller environments.Beyond product delivery, I actively drive organization-level architecture and engineering transformation. During 2023–24, I conceptualized and led an architecture-themed, organization-wide hackathon, helping institutionalize an architecture-first and design-first engineering culture across a large, multi-disciplinary department.After completing my Master’s in AI & Machine Learning, I am currently leading AI-driven engineering productivity and transformation initiatives focused on improving engineering efficiency and SDLC effectiveness. I drove the development and rollout of an AI-assisted engineering platform leveraging LLM- and SLM-based approaches for requirement generation, design artifacts, and test case creation. This platform was adopted by 150+ engineers through a governance-driven rollout, well ahead of the availability of mainstream AI developer tools.On the product side, I contribute to applied AI initiatives for embedded and in-cab systems, collaborating with cross-functional teams to explore practical and feasible AI deployment options under real-world constraints. This includes exposure to on-device ML for control and optimization, cloud-based predictive analytics, and high-performance compute workloads involving vision- and audio-based algorithms, with a strong focus on latency, data security, reliability, and hardware limitations across cloud, edge, and embedded environments.I am passionate about bridging deep embedded engineering with applied AI, building scalable platforms, mentoring engineers, and enabling teams to deliver high-quality systems with speed, rigor, and architectural discipline.

Experience

1. Assistant General Manager Technology & Architecture

   John Deere

   Apr 2022 — Present · Pune, IN

   Lead a team of Software Architects and System Engineers, defining and delivering architecture-first solutions across complex embedded machine platforms and in-cab systems- Own technology and architecture direction for multiple embedded control and display platforms, balancing innovation, scalability, interoperability, and long-term maintainability- Drive adoption of modern ECU communication architectures, including multidrop Ethernet (10BASE-T1S), enabling high-performance, multi-controller connectivity- Lead development of high-definition data communication platforms and Qt/QML-based in-cab display systems for complex machine operations- Conceptualized and led organization-wide architecture initiatives, including an architecture-themed hackathon, to institutionalize a design-first and architecture-first engineering culture- Mentor architects strengthening system thinkingAI Adoption & Engineering Productivity- Leadin AI adoption initiatives for the embedded department, focused on improving engineering productivity and SDLC efficiency- Contributed to and drove rollout of AI-assisted engineering capabilities, including requirements generation, test case creation, and automated test script generation- Driving additional AI-enabled SDLC automation initiatives in progress, such as unit test generation and developer workflow acceleration.Applied AI in Embedded & In-Cab Products- Contribute to applied AI initiative, shaping architectural foundations for on-vehicle intelligence- Support early-stage use cases including machine anomaly detection and intelligent in-cab assistance etc- AI deployment options across cloud, edge, and embedded environmentsKey Impact- Established architecture-driven delivery practices across product lines- Led GenAI adoption at department scale, with measurable improvements in engineering efficiency and consistency- Strengthened engineering culture through architecture and AI-led transformation initiatives.

Education

• Birla Institute of Technology and Science, Pilani

  Master of Technology - MTech, Artificial Intelligence and Machine Learning

• Indian Institute of International Business

  Post Graduation Diploma in Import and Export, International Business (Import and Export)

  2009 — 2009

• Gujarat University

  Bachelor of Engineering (BE), Electronics and Communication Engineering

  2002 — 2006

Skills

• Tortoise Svn
• Instrumentation
• Embedded Linux
• Qt
• Mvc Architecture
• Debugging
• Test Automation Framework
• Device Drivers
• C++
• Ibm Doors
• Embedded Software
• Socket Programming
• Software Project Management
• Linux
• Security System Design
• Qtp
• Hardware Architecture
• Gnu Debugger
• Gnu Make
• Rational Team Concert
• Gnu Tools
• Telecom Technologies
• Qml
• Valgrind
• Ipc
• Atmel Avr
• Design Patterns
• Arm
• Microchip Pic
• Enterprise Architecture
• Telecommunications
• Embedded Systems
• Unix Shell Scripting
• Ibm Rational Rhapsody
• Python
• Git
• Embedded C
• Ti Dsps
• Oop
• Voip