Manager, AI/ML Ops Engineering (Hybrid in Bangalore)

Smartsheet
Bangalore, INDIAPosted 23 March 2026

Job Description

For over 20 years, Smartsheet has helped people and teams achieve–well, anything. From seamless work management to smart, scalable solutions, we’ve always worked with flow. We’re building tools that empower teams to automate the manual, uncover insights, and scale smarter. But more than that, we’re creating space– space to think big, take action, and unlock the kind of work that truly matters. Because when challenge meets purpose, and passion turns into progress, that’s magic at work, and it’s what we show up for everyday. For over 20 years, Smartsheet has helped people and teams achieve–well, anything. As the Intelligent Work Management Platform, we are redefining the velocity of work by uniting people, data, and AI to move businesses forward. We don’t just automate tasks; we eliminate execution silos and turn strategic vision into measurable enterprise impact. We’re creating a space to think big and take action, because when challenge meets purpose and AI-powered execution meets human ingenuity, that’s magic at work. It’s what we show up for every day, helping organizations not just keep up with change, but thrive because of it. Our India Global Capability Center isn't just supporting global operations—we’re leading global innovation. After scaling rapidly into a best-in-class hub, we deliver the product innovation and enterprise capabilities that accelerate our global growth, profitability, and scale. As we expand Smartsheet India, we’re searching for Manager AI/ML Ops Engineering, who crave variety and ownership. You’ll have the opportunity to work across multiple teams and disciplines, building a versatile skillset while solving the complex challenges of a global platform. You Will: Focus on team members and coaching them to play to their strengths, grow and deliver peak performance Lead and mentor a team of AI/ML Ops engineers and operations specialists. Define and govern solutions for AI/ML operations, ensuring scalability, cost-efficiency, and reliability Develop and maintain standardized AI/MLOps workflows, including CI/CD/CT (Continuous Integration/Continuous Delivery/Continuous Training) pipelines Delegate and harness the aggregate strength of your team. Focuses on individual and team needs to foster a positive culture consistent with Smartsheet values. Actively helps individuals and the overall team to set priorities and focus on delivery of commitments Review team's designs and provide feedback on deployment safety, resilience, scale, performance, and security Lead and facilitate cross-team interactions, communication, and dependencies Ensure all changes are fully tested before being deployed Ensure deployment plans are well-considered and include appropriate scalability and load tests Work with stakeholders to align AI projects with business strategies. Ensure all AI/ML Ops solutions adhere to regulatory compliance, security, and ethical guidelines Drive Engineering and Operational excellence initiatives Perform other duties as assigned You Have: Enterprise SaaS software solutions with high availability and scalability Experience building teams through recruiting and retention Experience in Leading and Mentoring a team of ML engineers and operations specialists. Experience in building and maintaining AI/ML Ops platform systems ensuring scalability, reliability, efficiency and security AI/MLOps workflows on Databricks , MLFlow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, Knowledge Graph Knowledge of AI/ML frameworks like LangChain, LangGraph for AI/ML Ops pipeline integration Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable Programming languages like Python and SQL Modern software engineering practices like Kubernetes, CI/CD, IAC tools (Preferably Terraform), Observability, monitoring and alerting Solution Cost Optimisations and design to cost Legally eligible to work i ... (truncated, view full listing at source)
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