Senior AI & Data Governance Engineer-II (Hybrid in Bangalore )

<div class="content-intro"><p>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.</p></div><p>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 <strong>Senior AI Data Governance Engineers</strong> 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.<br><br></p> <p><strong>You Will:</strong></p> <ul> <li>Develop and enforce AIData governance frameworks, including bias detection, explainability, and model lifecycle management</li> <li>Ensure adherence to data privacy laws and security regulations, managing risks in AI and data pipelines</li> <li>Implement data lineage, metadata, data management, and quality frameworks</li> <li>Implementing tools to track data from its source to the final AI output. If a model breaks, you need to know exactly which data point caused the drift</li> <li>Define roles for data custodians, users, and AI developers, promoting transparency and fairness.</li> <li>Partner with Legal, Data Engineering, and Security teams to embed security and privacy into AI workflows and data products</li> <li>Implement governance tools (e.g., Collibra, Informatica) and automate audit procedure</li> <li>Oversee data stewardship to ensure data accuracy, integrity, and privacy throughout its lifecycle</li> <li>Designing and enforcing the rules for how data is collected, stored, and used—specifically focusing on data privacy (GDPR, CCPA) and AI regulations (like the EU AI Act).</li> <li>AI Ethics Bias Mitigation: Establishing "Responsible AI" standards. This involves auditing models for algorithmic bias, ensuring transparency (Explainable AI), and managing the ethical implications of automated decision-making</li> <li>Risk Management through Identification of Shadow AI (unauthorized use of AI tools) and managing the risks associated with third-party LLM providers<br><br></li> </ul> <p><strong>You Have:</strong></p> <ul> <li>Experience in AI Governance across foundational pillars like AI Organization, Legal, Regulatory Compliance, Ethics, Transparency, Interoperability, Data/AIOps Infrastructure, AI protection and Security</li> <li>AI Risk Assessment Management, Auditability Transparency, AI Policy Development</li> <li>Databricks AI Governance Framework (DAGF), Databricks Security Framework (DASF), MLFlow, Unity Catalog, RAG Governance</li> <li>Programming languages like Python and SQL</li> <li>Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable</li> <li>In-depth understanding of AI, GenAI, LLMs, data quality assessment, and metadata management.</li> <li>Regulatory Knowledge in GDPR, EU AI Act, and industry-specific regulations (e.g., HIPAA, Financial Services)</li> <li>Lineage Tracking with automatic capture of end-to-end data flow (from ETL to BI/AI) to understand dependencies.</li> <li>Auditability with centralized logs to allow compliance teams to monitor access and usage of data and AI models</li> <li>Knowledge of tools for Model Auditing towards Bias detection,, monitoring, and mitigating bias</li> <li>Understanding of data masking, encryp ... (truncated, view full listing at source)