Full-Time
Enterprise Account Executive
Revefi
11-50 employees
Automated data operations and observability platform
No salary listed
Remote in USA
Remote
 Sales & Account Management (1) |
|---|
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- Six to eight or more years of experience in Business-to-Business Software as a Service sales.
- At least three years of experience selling into data, cloud, or engineering personas.
- Proven track record of exceeding quota and closing complex deals.
- Strong understanding of the modern data stack, cloud infrastructure, or observability space.
- Experience managing technical sales cycles with multiple stakeholders and long sales timelines.
- Experience working in early-stage environments and building Go-To-Market motions from the ground up.
- Own and manage the full sales cycle from discovery to close across mid-market and enterprise accounts.
- Drive pipeline growth in the United States region through outbound prospecting, inbound leads, and field events.
- Educate technical stakeholders, including Data Engineers, Cloud Architects, and Financial Operations teams, on the value of the Artificial Intelligence driven observability and spend optimization platform.
- Collaborate with Sales Development Representatives and Marketing to run regional campaigns and Go-To-Market plays.
- Develop and execute territory plans and strategic account mapping.
- Accurately forecast sales activity and revenue using tools such as Salesforce, Gong, and HubSpot.
- Provide customer feedback to product and leadership teams to influence the product roadmap and positioning.
- Experience selling to Data Engineers, Cloud/DevOps leaders, or Financial Operations teams.
- Familiarity with Generative Artificial Intelligence, data observability, or Artificial Intelligence and Machine Learning driven infrastructure tools.
- Background in early- to mid-stage startups (Seed to Series B), with hands-on experience adapting to fast-changing priorities and scaling Go-To-Market functions.
Revefi provides a data operations and observability platform for cloud enterprises, helping manage data quality, spending, performance, and usage with minimal manual work. It integrates with Snowflake, BigQuery, and Redshift and connects to BI tools like Tableau and ThoughtSpot, plus collaboration platforms like Slack and Teams, to monitor data in real time and offer automated recommendations. It differentiates itself with zero-touch onboarding and end-to-end data lifecycle management across cloud data platforms, aiming for measurable outcomes such as cost savings and increased data usage. Its goal is to help enterprises access the right data at the right time and cost while continuously improving quality and reducing cloud data spend through automation.
Company Size
11-50
Company Stage
Series A
Total Funding
$30.5M
Headquarters
Redmond, Washington
Founded
2021
Get referred to Revefi
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Simplify's Take
What believers are saying
- June 2026 Databricks GA extended Revefi into a larger, active enterprise install base.
- November 2025 Snowflake Marketplace listing and March 2026 update broadened distribution inside Snowflake.
- June 2026 Token Economics caught a $76,000 AI overspend within minutes, proving ROI urgency.
What critics are saying
- Databricks and Snowflake can bundle native optimization, collapsing Revefi into a feature by 2027.
- Reliance on autonomous spend actions creates security and procurement scrutiny at enterprise customers.
- Monte Carlo, Datadog, and hyperscaler FinOps tools crowd data observability deals, slowing expansion.
What makes Revefi unique
- RADEN spans Databricks, Snowflake, BigQuery, and OpenAI, unlike single-vendor observability tools.
- Revefiās AI DBA executes fixes through Slack and Jira, not just dashboards.
- Zero-touch, read-only setup plus organizational memory reduce adoption friction and repeat incident toil.
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Growth & Insights and Company News
6 month growth
ā 11%1 year growth
ā 5%2 year growth
ā 11%Revefi has extended its AI database administrator to Databricks, enabling autonomous cost and performance optimisation across the platform. The company announced the expansion at Databricks Data + AI Summit 2026 in San Francisco. The Revefi AI DBA handles performance tuning, cost management, operations and governance autonomously. It optimises Spark jobs, manages DBU consumption, right-sizes clusters and resolves production incidents. The system operates through Slack, Jira or directly within Revefi's product, executing tasks whilst maintaining transparency and requesting approval when needed. The AI DBA is powered by RADEN, Revefi's underlying agent, and works across multiple data platforms including Snowflake and Google BigQuery. The service is generally available today at no additional cost for Revefi enterprise customers. Founded in 2021, Revefi counts AMD, Verisk and Docker amongst its clients.
Revefi extends its AI DBA to autonomously optimize Databricks ecosystem. June 16, 2026 San Francisco, CA, June 16, 2026. Revefi today extended its AI DBA to Databricks, bringing the agentic teammate that autonomously manages, optimizes, and operates cloud data platforms to the Databricks ecosystem. The announcement coincides with Databricks Data + AI Summit 2026 in San Francisco, June 16 to 18, where Revefi will be exhibiting at Booth 113 and demonstrating the AI DBA live. As Databricks deployments scale across jobs, pipelines, all-purpose clusters, and SQL warehouses, the operational burden on data teams scales with them. Engineers and platform owners spend most of their time on repetitive, high-toil work: tuning Spark jobs, chasing runaway DBU consumption, right-sizing and consolidating clusters, fixing out-of-memory failures and skewed joins, and resolving production incidents. Hiring a skilled Databricks administrator is expensive and slow. Existing tools can surface cost dashboards but rarely act on them, while the platform itself keeps getting more complex to operate. The Revefi AI DBA closes that gap by combining detection, investigation, and autonomous action in a single agentic teammate. "The best AI embodies the human, not the other way around," said Sanjay Agrawal, Co-Founder and CEO of Revefi. "The Revefi AI DBA is built to work the way a great Databricks administrator works: task-oriented, transparent, and accountable. It runs controlled experiments before it changes anything, asks for approval when needed, assigns tasks to teammates, and keeps improving the platform around the clock. Customers can hire it the way they would hire a person, and it gives their team back the hours they spend on reactive operational work." What the Revefi AI DBA for Databricks Does The Revefi AI DBA gives a human element to agentic AI: an expert Databricks administrator working autonomously around the clock across the Databricks ecosystem, within enterprise process guidelines. Customers assign it work from Slack, Jira, or directly in the Revefi product. It executes, raises pull requests, opens tickets, tracks attribution, reports progress, and loops the team in when needed. The AI DBA handles: * Performance. Job and Spark optimization through controlled experiments, slow-run investigation, and root-cause analysis of failures, skewed joins, high shuffle volume, and out-of-memory errors. * Cost and FinOps. Continuous DBU and spend monitoring with autonomous savings actions. Cluster right-sizing, autoscaling tuning, idle and over-provisioned cluster reclamation, and tradeoffs across job clusters, all-purpose clusters, and serverless. Cost is attributed by job, cluster, user, and Databricks product category (SQL, jobs, all-purpose clusters, and predictive optimization) for chargebacks and showbacks. * Operations. Cluster and configuration management, job consolidation, removal of redundant jobs, and continuous tuning across workspaces. * Governance. User and role management, access reviews, and table-level usage auditing that attributes compute cost to individual users. * Agentic workflow. Finds and creates work for itself to keep improving the platform. Asks for approval from team members as needed. Assigns work to others. Accepts work from others via Slack, Jira, or in-product chat. * Organizational memory. Remembers every action taken across the customer's organization, what worked and what did not, and personalizes recommendations. The AI DBA is powered by RADEN, Revefi's underlying agent. Unlike platform-native agents, Revefi is aligned with the customer's goal of reducing cloud data spend; it carries persistent organizational memory across actions; and it operates across multiple data platforms, viz., Databricks, Snowflake, Google BigQuery, and more rather than inside a single vendor's walled garden. Availability The Revefi AI DBA for Databricks is generally available today and is included in the Revefi enterprise package at no additional cost. Customers can get started in five minutes with a zero-touch, read-only integration. To request access or a live demo, visit revefi.com/databricks. Databricks Data + AI Summit attendees can meet Revefi at Booth 113, June 16 to 18 at Moscone Center, for live demos of the AI DBA and conversations with the founding team. Trusted by Leading Enterprises Revefi is trusted by F500 and other leading enterprises such as AMD, Verisk, Stanley Black & Decker, Docker, Ingersoll Rand, Help At Home and Cribl. About Revefi Revefi is the creator of RADEN, an AI agent designed to help enterprises optimize cost, data operations, data observability, AI observability, and database administration across cloud data platforms and LLMs. Founded in 2021 by data experts and ThoughtSpot co-founders Sanjay Agrawal and Shashank Gupta, Revefi's AI and ML-powered platform automates complex data and AI use cases, delivering up to 60 percent reduction in data spend, 10x improvement in operational efficiency, and results in as few as five minutes. Revefi is a 2025 Gartner Cool Vendor in Data Management. Revefi is recognized as one of "The Companies That Matter Most in Data" in the DBTA 100 2026 list. Media Contact Adopt the AI Agent for Data Cost Optimization
Revefi has launched FinOps, Observability and Token Economics for AI to govern cost, quality and reliability across data, AI and agents. The announcement was made at FinOps X 2026 in San Diego. The platform provides real-time attribution and control of AI spending across providers including OpenAI, Anthropic, Google Gemini and Vertex AI. Revefi caught one Fortune 500 enterprise user incurring $76,000 in unexpected token spend within minutes. The company reports token economics through four lenses: by outcome, by department, wasted and optimised. Founded in 2021 by ThoughtSpot co-founders Sanjay Agrawal and Shashank Gupta, Revefi already helps customers cut cloud data and Snowflake warehouse costs by 30-60%. The company is a 2025 Gartner Cool Vendor and FinOps Foundation member.
Revefi launches FinOps, Observability and Token Economics for AI. SAN DIEGO, June 8, 2026 Revefi today announced general availability of FinOps, Observability and Token Economics for AI to govern cost, quality, and reliability across Data, AI, and Agents. The announcement coincides with FinOps X 2026, in San Diego, June 8 to 10, where Revefi will be exhibiting. On the AI layer, a single user in a Fortune 500 enterprise incurred a $76,000 unexpected token spend for a single AI use case. Revefi caught the above spend for this customer within minutes, and they immediately stopped the unplanned dollar burn. "Today as enterprises are pushing everyone to use AI across the board, we see AI Agents burning billions of tokens within minutes, real risk of running out of annual budget within weeks or even days. Your AI just lit both your AI and your data budget on fire," said Sanjay Agrawal, CEO and co-founder of Revefi. "The model was the easy part, knowing what it cost, whether it worked, and if it was even worth it, is the hard part. That's Token Economics: every token, seen, attributed, and under your control. Because you can't adopt AI safely at scale if you can't measure continuously & can't attribute ROI." Revefi's Token Economics gives enterprises a single, unified layer to see, attribute, and control the true cost of AI. As organizations push LLMs and AI agents into production, the spend sprawl across providers, models, agents, and users is increasing at an unprecedented rate with no way to trace what happened, where it went wrong, or what it cost. Revefi closes that gap: full user-to-agent-to-model attribution, real-time observability, prompt optimization, and automated ROI on every AI action, across OpenAI, Anthropic, Google Gemini, and Vertex AI. The result is safe AI adoption built on the three things that matter most - spend, trust, and control with value in as little as five minutes and zero-touch, read-only setup. Revefi reports Token Economics through four lenses that tie spend to value and ROI instead of raw consumption: By Outcome, By Department, Wasted and Optimized. Revefi attributes spend across the full path a request travels. It starts with the user who issues the request, through per-user cost attribution, outlier detection, prompt analysis and tracing, automatically alerts if it goes in the wrong direction, and triggers workflows for model selection, prompt analysis to balance performance and spend. Proven at the data layer, now governing the full chain Revefi customers have already cut cloud data and Snowflake warehouse costs between 30-70%. Today the platform is running tens of millions of automated monitors for data freshness, quality, spend increases, schema changes, and query performance for enterprise customers. This is the data-layer foundation that trusted Token Economics depends on. About Revefi Revefi is the creator of RADEN, an AI agent designed to help enterprises optimize cost, data operations, data observability, AI observability, and database administration across cloud data platforms, LLMs and Agents. Founded in 2021 by data experts and ThoughtSpot co-founders Sanjay Agrawal and Shashank Gupta, Revefi's AI and ML-powered platform automates complex data and AI use cases, delivering up to 60 percent reduction in data spend, 10x improvement in operational efficiency, and results in as few as five minutes. Media contact: Adopt the AI Agent for Data Cost Optimization
Revefi launches AI DBA to manage, optimize, and operate cloud data platforms. A F500 Enterprise used the Revefi AI DBA to autonomously manage more than 700 Snowflake warehouses, reducing spend by 50% in less than 48 hours. Revefi today announced the launch of the Revefi AI DBA, an agentic teammate that works alongside data teams to manage, optimize, and operate their cloud data platform. The announcement coincides with Snowflake Summit 2026 in San Francisco, June 1 to 4, where Revefi will be exhibiting at Booth 1410 and demonstrating the AI DBA live. The best AI embodies the human, not the other way around," said Sanjay Agrawal, Co-Founder and CEO of Revefi. "The Revefi AI DBA is built to work the way a great database administrator works" - Sanjay Agrawal As cloud data platforms scale, the operational burden on data teams has scaled with them. Database administrators and platform owners spend most of their time on repetitive, high-toil work: tuning warehouses, chasing slow queries, reviewing access, converting older warehouse generations, and resolving production incidents. Hiring a competent DBA to solve the problem is expensive and slow. Existing tools can detect simple issues but rarely fix them and the underlying data platforms continue to get more complex and difficult to manage. The Revefi AI DBA closes that gap by combining detection, investigation, and autonomous action in a single agentic teammate. Jun 2, 2026 Prev Next 1 of 42,448 "The best AI embodies the human, not the other way around," said Sanjay Agrawal, Co-Founder and CEO of Revefi. "The Revefi AI DBA is built to work the way a great database administrator works: task-oriented, transparent, and accountable. It handles all aspects of a day in the life of a database administrator. It keeps improving the platform without any triggers, asks for approval when needed, assigns tasks to teammates, and accepts work from them. Customers can hire it the way they would hire a person, and it gives their team back the hours they spend on reactive operational work. It operates continuously, allowing teams to improve performance, control costs, and resolve issues around the clock." What the Revefi AI DBA Does The Revefi AI DBA gives a human element to agentic AI: an expert database administrator working around the clock across cloud data platforms, within enterprise process guidelines. Customers assign it work from Slack, Jira, or directly in the Revefi product. It executes, raises pull requests, opens tickets, tracks attribution, reports progress, and loops the team in when needed. The AI DBA handles: - Performance. Query optimization, query rewrites, slow-query investigation, and root-cause analysis. - Cost and FinOps. Continuous spend monitoring with autonomous savings actions. Right-sizing, right scale-out, and right-generation of warehouses. It can make tradeoffs involving Gen 1 to Gen 2 conversions, configuration optimization and adaptive warehouses. - Operations. Warehouse management, configuration changes, provisioning with permissions, continuous cluster tuning, and idle resource reclamation. - Governance. User and role management, access reviews, schema and table changes. Stops in-flight bad actors autonomously. - Agentic workflow. Finds and creates work for itself to keep improving the platform. Asks for approval from team members as needed. Assigns work to others. Accepts work from others via Slack, Jira, or in-product chat. - Organizational memory. Remembers every action taken across the customer's organization, what worked and what did not, and personalizes recommendations over time. "The most powerful thing about an AI DBA is not what it automates, it is what it frees the team to own," said Shashank Gupta, Co-Founder and CTO of Revefi. "When the 3am pages, ticket queues, and performance fires are handled, data teams get to focus on what only humans can do: strategy, trust, architecture, and the judgment calls that move the business." The AI DBA is powered by RADEN, Revefi's underlying agent, which is available on the Snowflake Marketplace. Unlike platform-native agents, Revefi is aligned with the customer's goal of reducing cloud data spend; it carries persistent organizational memory across actions; and it operates across multiple data platforms rather than inside a single vendor's walled garden. [To share your insights with Aithority, please write to [email protected]]