The Artificial Intelligence Engineering Manager will be responsible for leading, mentoring, and providing support to a team of talented AI engineers as you work on cutting edge AI based projects. You will oversee the end-to-end development lifecycle, including project planning, resource allocation, and timeline management. You will drive the integration of AI solutions into existing systems and processes as well as building out best practices and coding standards within the AI engineering team.
You will report directly to our Manager and you’ll work out of our Bengaluru,Karnataka location on a Hybrid work schedule.
We are seeking an AI Engineering Manager with strong foundations in software engineering, machine learning systems, and modern MLOps practices. This role leads cross-functional engineering teams to build scalable, reliable, production-grade AI systems.
As the Artificial Intelligence Engineer Manager at Honeywell, you will play a pivotal role in driving the development and implementation of cutting-edge AI solutions. Working within the dynamic AI team, you will oversee and manage a group of talented engineers to address complex business challenges and contribute to the organization's success. Your technical expertise, leadership skills, and strategic mindset will be essential in shaping the future of AI initiatives at Honeywell. Let’s shape the future together!
At Honeywell, our people leaders play a critical role in developing and supporting our employees to help them perform at their best and drive change across the company. Help to build a strong, diverse team by recruiting talent, identifying and developing successors, driving retention and engagement, and fostering an inclusive culture.
Key Responsibilities
- Engineering Leadership
Lead, mentor, and grow AI/ML and software engineering teams.
Promote engineering excellence through code quality, testing, and design reviews.
Establish and evolve system design and operational best practices.
- AI/ML System Design & Architecture
Architect end-to-end AI systems: data pipelines, training pipelines, deployments, monitoring.
Drive cloud-native scalable AI service design (microservices, APIs, containers).
Ensure responsible AI practices and model governance.
- MLOps & Platform Ownership
Define and evolve MLOps standards and reusable workflows.
Oversee production deployment, CI/CD for ML, automated testing, monitoring.
Champion automation and infrastructure-as-code.
- Technical Execution
Support engineers through hands-on design, prototyping, and troubleshooting.
Collaborate cross-functionally to ship production-ready AI systems.
Required Qualifications
Bachelor’s or Master’s in CS or related.
7+ years in software or ML engineering, 2+ years leading teams.
Strong software engineering fundamentals and Python expertise.
Experience productionizing ML systems and using CI/CD, containers, cloud platforms.
Deep understanding of ML lifecycle operations.
Preferred Qualifications
Experience designing scalable AI platforms.
Experience with responsible AI, model governance.
Familiarity with LLMs, agent-based systems.
Experience leading multi-disciplinary teams.
What We Offer
Opportunities to build modern AI engineering platforms.
A collaborative, highly technical environment.
Strong career growth potential.