CSQ427R87 Note: This role is remote within the United States, with a strong preference for candidates based in the Eastern or Central time zones. Candidates should expect to travel at least once a month. The Forward Deployed AI Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services (PS) engagements to help our customers build and productionize first-of-its-kind AI applications with a focus on GenAI. We work cross-functionally to shape long-term strategic priorities and initiatives alongside AI/ML Product, Research, and Engineering. We are looking for a world-class leader to lead and grow our AI FDE team. In this role, you will lead customers on their AI/ML transformation with Databricks, push the boundaries of our product, recruit and develop top data scientists/machine learning engineers, and manage a portfolio of key accounts. The impact you will have: - Lead and scale a world-class AI/ML professional services team, including hiring, mentoring, and building a team structure to support long-term growth and execution at scale. - Develop and expand executive relationships with key customers and partners (including VP+, CIO/CDO-level stakeholders), acting as a trusted advisor during complex technical engagements and AI transformations. - Align with Field Engineering and Sales Leaders to define joint strategies for strategic accounts and ensure strong delivery coordination across functions. - Lead strategic AI PS initiatives, practice development, and standardized delivery processes; design scalable engagement models and reusable solutions for repeatability across the global team. - Shape cross-functional collaboration by influencing Product, R&D, and GTM—ensuring voice-of-customer insights and delivery learnings help inform the product roadmap and GTM strategy. - Own OKRs for AI-services led accounts, revenue, utilization, and public references. - Represent Databricks as a thought leader in AI/ML. What we look for: - Extensive experience managing, hiring, and building a team of high-performing data scientists/ML engineers and leaders, with a track record of scaling organizations through developing scalable processes and cultivating leaders. - Ability to scope, guide, and sell technical engagements, manage escalations, and ensure successful delivery in enterprise environments. - Deep technical expertise in ML, GenAI, and data science, and curiosity to continue to stay up-to-date in this ever-changing field. - Experience leading teams building cutting-edge production ML solutions in cloud environments (AWS, Azure, or GCP). - Proven success in developing strategy with senior executive stakeholders to define program-level goals, align technical vision, and build trust throughout complex enterprise engagements. - Develop and drive a strategic vision for AI transformations across our customers, including product management for applied AI projects, organizational change management for the adoption of AI, and mapping and aligning with key stakeholders. - Demonstrated experience in cross-functional leadership roles, collaborating with Sales, Product, and GTM teams to drive business impact through AI/ML. - “Company-first” mindset. - [Preferred] Experience in a customer-facing consulting or professional services leadership role. - [Preferred] Experience working with Databricks. 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 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 anticipates 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. Local Pay Range $211,800—$291,300 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 click here. 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.

ARIEL is our unique and specialist adjusting arm of Crawford & Company, providing Agricultural, Rural Industries and Estates' Losses claims management expertise to complement our global portfolio of specialty and traditional claims management services. Our opportunity is a first notification of loss (FNOL) coordinator to support our busy network of claims technicians and adjusters

• Serves as the technical lead for the cross-functional team supporting SunStrong’s consumer apps, which is comprised of engineering, QA and product • Leads a team of software engineers, providing mentorship, guidance and support to facilitate their progressional growth and development. • Contributes to overall team velocity as a hands-on leader by delivering some code. • Provides code reviews and mentorship to improve overall application health and team skills. • Provides architectural planning and insights for application development. • Facilitates Agile sprint ceremonies including daily standups, sprint planning and retrospectives. • Identifies, implements and promotes opportunities to improve team delivery through the use of AI tooling and methodologies. • Champions best practices, coding standards and software development methodologies to maintain high-quality codebase. • Manages and allocates resources effectively to meet project deadlines and organizational objectives. • Promotes a positive and inclusive team culture that encourages creativity, teamwork and continuous improvement.

• Month 1: Become a strong IC. Get into the codebase, ship a meaningful feature, and prove to yourself and the team that you can build at the level we need. You don't need to be the best senior engineer on day one, but you should be onboarded and delivering high-quality work fast enough that you can credibly help others improve. Expect to spend 70–80% of your time writing code. • Month 2: Own hiring. Beyond continued IC contributions, take over engineering interviews and build a better technical interview process. The current setup depends too many people. You'll design technical challenges, run screens, and make hiring more consistent and repeatable. This matters — we're planning to double the team in the next 12 months. • Month 3: Start leading. Help design a pragmatic way to evaluate team performance — simple, measurable, not bureaucratic. Start doing more regular 1:1s with each team member, focused on three things: output x impact, quality, and AI efficiency. Identify who's behind and help them improve. Remove obstacles from top performers. • Over time, the balance shifts. Coding goes from 70% to 10–20%. Hiring becomes the plurality of your work, we’ll grow the team from 5 engineers to 9 in the next months (50–70% during active hiring, 20–30% after). Mentorship and process improvement grow as the team grows. But you never fully stop building — you stay in the code enough to have credible technical judgment.