Hi! We're Forerunner. We believe that climate adaptation is a necessity, not a luxury, and communities deserve access to powerful software that helps them plan for the future. The challenge of climate change is complex – it implicates how municipalities plan, manage capital, and communicate to both residents and higher levels of government. Forerunner helps local communities do these things better by empowering them to access, understand, and mobilize local-level flood risk data at scale. About the role As a Deployment Specialist, you will own the end-to-end deployment experience for our customers — from discovery to go-live — ensuring the outcome aligns with business impact. You’ll act at the intersection of strategy, project management, and operational delivery, collaborating with customers, internal teams, and technical resources to make deployments high-quality, repeatable, and outcome-driven. What you'll do Customer Discovery & Planning Lead structured workshops with customers to uncover business objectives, operational constraints, and success metrics. Translate findings into a clear deployment roadmap and set of deliverables. Define project scope, milestones, dependencies, and governance. Project Leadership Serve as the primary point of contact for the customer during deployment. Coordinate across cross-functional teams (Implementation Specialist, Forward Deployed Engineer, Customer Success Manager, internal stakeholders) to ensure alignment and momentum. Proactively identify risks, manage dependencies, and escalate when necessary. Provide regular status updates to both the customer and internal leadership. Solution Design & Oversight Partner with the Implementation Specialist to ensure system configurations align with business goals. Work with the Forward Deployed Engineer to scope integrations and customizations. Ensure that deployment deliverables map back to the business requirements and success criteria.

CSQ426R189 The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. This role can be remote. The impact you will have: Develop cutting-edge GenAI solutions, incorporating the latest techniques from our Mosaic AI Research to solve customer problems Own production rollouts of consumer and internally facing GenAI applications Serve as a trusted technical advisor to customers across a variety of domains Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap What we look for: Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy Expertise in deploying production-grade GenAI applications, including evaluation and optimizations Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools (i.e., pandas, scikit-learn, PyTorch, etc.) Experience building production-grade machine learning deployments on AWS, Azure, or GCP Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike Passion for collaboration, life-long learning, and driving business value through AI [Preferred] Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed datasets Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles.  Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipated utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here. Zone 1 Pay Range $180,656 — $248,360 USD Zone 2 Pay Range $180,656 — $248,360 USD Zone 3 Pay Range $180,656 — $248,360 USD Zone 4 Pay Range $180,656 — $248,360 USD About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visit https://www.mybenefitsnow.com/databricks. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description The Director of Engineering, Applied Intelligence & Data Platforms will be responsible for overseeing the vision, execution, and development of AI solutions for our products. We are looking for a leader who balances deep expertise in machine learning with the ability to build and orchestrate distributed systems at scale. - Oversee multiple existing teams and help bootstrap new teams based on our planned roadmap and customer opportunities. - Work closely with existing product and senior leadership to align AI initiatives with LVT business goals. - Ensure the successful implementation of AI technologies that deliver significant value. Role Responsibilities - Strategic AI Leadership: Work with senior leadership to develop a technical AI strategy that aligns with LVT business goals and strengthens our competitive advantage. - Scalable Architecture: Design and build multi-region distributed services capable of handling massive data throughput from globally deployed IoT sensors and cameras. - Team Management: Mentor and lead a collaborative team of machine learning engineers, MLOps engineers, and data scientists. - Agentic AI & MCP: Lead the architecture and implementation of agentic AI frameworks and define the strategy for LVT's Model Context Protocol (MCP). - Edge-to-Cloud Integration: Oversee the development of robust data pipelines and infrastructure that span from cloud orchestration engines to edge devices like NVIDIA Jetson. - Model Lifecycle: Establish benchmarks for model performance, monitoring outputs and adjusting for accuracy and product effectiveness. - Data Governance & Ethics: Ensure all AI development adheres to strict data security, privacy, and ethical guidelines within our SaaS environment. - Research and Innovation: Stay current with the latest developments in AI research and methodologies. Encourage and support the exploration of new techniques and technologies to enhance the company's AI capabilities. - Data Strategy and Governance: Ensure the use of high-quality, reliable data to train AI models. Implement AI data governance best practices to maintain the integrity, privacy, and data security. - Compliance and Ethics: Ensure that AI model development adheres to industry standards, ethical guidelines, and regulatory requirements. - Cross-functional & Stakeholder partnership: Collaborate and communicate AI strategy, progress, and outcomes to stakeholders, including the executive team, board of directors, and investors. Qualifications - 10+ years of engineering experience, including 5+ years of applied AI/ML leadership. - Deep understanding of modern cloud technologies and orchestration engines for high-availability, multi-region services. - Proven track record in the IoT space, specifically building infrastructure for cameras and sensors in production environments. - Expert knowledge of computer vision models, Large Language Models (LLMs), and Large Vision Models (LVMs) and Agentic AI frameworks. - Proficiency in Python, C++, or Java, and experience with frameworks such as PyTorch, TensorFlow, or scikit-learn. - Practical experience deploying and optimizing models for edge hardware (e.g., NVIDIA Jetson). - Deep understanding of machine learning algorithms, data preprocessing, model evaluation, and deployment. - Demonstrated ability to think strategically and make data-driven decisions. - Degree in Computer Science, Data Science, Engineering, or a related field. Compensation The beginning annual salary range for this role is $243,000.00 - $324,000.00 USD and is determined by location, job-related experience, and education/training. Your total earning potential is amplified by a bonus structure tied to meeting goals, and you will become an owner from day one through our employee equity program. Benefits - Comprehensive health, family, and financial support. - Benefits package designed to support you inside and outside the office. Equal Opportunity Employment LVT is proud to be an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.

• Optimize the sales tech stack with a primary focus on Salesforce CRM and MariaDB data integration. • Manage system configurations, troubleshoot complex data workflows, and promote the adoption of advanced technologies. • Bridge the gap between traditional CRM management and modern AI automation. • Leverage AI, machine learning, and automated workflows to enhance CRM performance, drive predictive data insights, and streamline commercial execution. • Manage Salesforce processes including Pages, Objects, Fields, Validation Rules, Territory/Role Hierarchies, and User Setup. • Support data flow and integrity between MariaDB databases and the Salesforce environment; assist in SQL querying for advanced data extraction. • Serve as the primary contact for CRM support channels, resolving technical issues and managing system upgrades. • Lead onboarding and ongoing training for sales teams, maintaining updated user documentation and video tutorials. • Generate and analyze reports using Power BI or similar tools to track KPIs, territory optimization, and sales forecasting. • Knowledge of AI-driven tools for predictive analytics and machine learning models to enhance user behavior analysis. • Utilize low-code/no-code automation tools (e.g., Flow, Zapier, or Make.com) to streamline CRM workflows and reduce manual data entry. • Translate complex datasets into actionable business insights, ensuring technology programs stay at the forefront of industry standards. • Partner with global support teams to maintain data integrity and accuracy across all platforms. • Develop technical guides and maintain a library of standard operating procedures (SOPs).