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Software Engr II at Honeywell

, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

03 Sep, 26

Salary

0.0

Posted On

05 Jun, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Go, Rust, C++, Databricks, BigQuery, Azure Data Lake, Kubernetes, MLOps, LangChain, LangGraph, Langsmith, NVIDIA Jetson, Knowledge Graphs, Ontology Engineering, React

Industry

Automation Machinery Manufacturing

Description

As a Full Stack AI Platform Engineer here at Honeywell, you will design, build, and scale AI systems end-to-end — from high-throughput IoT streaming pipelines and knowledge graph infrastructure, through LLM orchestration and RAG services, to the React-based interfaces that surface autonomous insights to plant engineers, facility managers, and OT security analysts. We are seeking a Full Stack AI Platform Engineer to join our Data Engineering, AI & ML Platform team. This role is central to designing, building, and scaling the enterprise AI/ML platform that powers intelligent automation across a global portfolio. You will work at the intersection of data engineering, machine learning operations, and edge AI — building production-grade infrastructure that processes billions of IoT events from building management systems, deploys models to edge devices, and enables AI-driven applications including predictive diagnostics, energy monitoring, and RAG-based knowledge systems. This is a high-impact individual contributor role for someone who thrives in ambiguity, ships production systems, and can operate across the full stack from cloud-native platforms to edge GPU hardware. Honeywell helps organizations solve the world's most complex challenges in automation, the future of aviation and energy transition. As a trusted partner, we provide actionable solutions and innovation through our Aerospace Technologies, Building Automation, Energy and Sustainability Solutions, and Industrial Automation business segments – powered by our Honeywell Forge software – that help make the world smarter, safer and more sustainable.

Responsibilities

Design, build, and scale an enterprise AI/ML platform including IoT streaming pipelines and RAG services. Develop production-grade infrastructure for predictive diagnostics and energy monitoring across cloud and edge GPU hardware.