Full-Time
Enterprise Account Executive
France
Arango
51-200 employees
Multi-model database with open-source and enterprise
No salary listed
Paris, France
Hybrid
Candidates must be located within France; travel is required as necessary to engage with customers.
 Sales & Account Management (1) |
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- At least 3 years of experience in IT infrastructure and large enterprise selling.
- Experience selling within the defined region and historical understanding of key accounts and customers in France.
- Domain experience with a vendor in the data and artificial intelligence ecosystem, such as Databricks, Neo4j, Snowflake, database vendors, or artificial intelligence vendors.
- Experience owning pipeline-generation responsibilities and prospecting for new business.
- Ability to engage broadly and deeply within large, complex global accounts.
- Deep expertise in the MEDDPIC sales methodology and ability to qualify opportunities, align with customer success metrics, and close high-value deals.
- Experience managing long sales cycles and engaging strategically with enterprise clients.
- Ability to communicate the strategic and financial value of Arango to support long-term customer success.
- Ability to use metrics and insights to guide decisions and keep customer relationship management tools updated.
- Native-level French language proficiency.
- Fluent-level English proficiency.
- Build and expand net new business by generating pipeline meetings through targeted prospecting and insights from existing customer accounts.
- Use the MEDDPIC playbook to qualify opportunities, identify key stakeholders, and align with customer metrics and business outcomes.
- Maintain Salesforce customer relationship management data, including daily activities, interactions, and pipeline information.
- Deliver presentations and high-level demonstrations tailored to customer business objectives.
- Collaborate with Technical Presales, Marketing, and Customer Success teams to articulate Arango’s business benefits and drive adoption across enterprise organizations.
- Conduct weekly pipeline reviews and maintain forecast accuracy using data to inform strategy.
- Travel as necessary to engage with key customers and develop customer relationships and opportunities.
- Perform other duties as assigned to support the business.
- Candidates with 3 years or more of relevant experience who are considered up-and-comers may be considered if they have the right domain experience.
ArangoDB provides a multi-model database that can store documents, graphs, and key-value data all in one system. It uses a single engine and query language to manage different data models, allowing users to run diverse workloads with one database. The product comes in an open-source version (free) and an enterprise version (paid) that adds advanced features, stronger security, and premium support; the company also earns revenue from consulting services and training. Compared with competitors, ArangoDB stands out by integrating multiple data models in one database, enabling flexible data modeling and cross-model queries without needing separate databases. Its goal is to simplify data management for tech startups, large enterprises, and academic institutions by providing a versatile, scalable database solution with dependable support and services.
Company Size
51-200
Company Stage
Series B
Total Funding
$46.9M
Headquarters
San Francisco, California
Founded
2014
Get referred to Arango
See people who can refer or advise you
Simplify's Take
What believers are saying
- ORIX USA invested on August 12, 2025, funding AI-native infrastructure expansion.
- NVIDIA GTC 2026 exposure and booth 3421 position Arango beside enterprise AI builders.
- Customer stories on May 6, 2026 show traction across security, clinical trials, and capital markets.
What critics are saying
- MongoDB, Neo4j, and cloud databases compress ArangoDB's multi-model differentiation inside 2026.
- AI-platform branding masks database commoditization; buyers can stitch open-source components instead of paying Arango.
- If AI agents disappoint, ArangoDB loses its narrative and reverts to a niche database vendor.
What makes Arango unique
- ArangoDB unifies graph, vector, document, key-value, and full-text search in one engine.
- Arango Contextual Data Platform 4.0 ships AutoGraph, AutoRAG, Ada, and AQLizer.
- PSI CRO cut site selection from six weeks to minutes using Arango.
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Benefits
Hybrid Work Options
Remote Work Options
Growth & Insights and Company News
6 month growth
↓ -2%1 year growth
↓ -3%2 year growth
↓ -8%PSI CRO, a global clinical research organisation, has reduced clinical trial site identification from up to six weeks to minutes using SYNETIC, an AI knowledge engine powered by the Arango Contextual Data Platform. The system helps identify higher-performing trial sites and minimise costly non-enrolling institutions, which account for 30-40% of trial sites. Clinical trials can cost over $160 per minute operationally, and activating a trial site costs $30,000 or more. With 15% of sites never enrolling a single patient, failed recruitment can cost millions per study. SYNETIC unifies fragmented clinical research data into a single contextual layer, preserving relationships across investigators, institutions, protocols and historical outcomes. The platform provides explainable AI recommendations, including rationale, supporting evidence and confidence levels, enabling data-driven site selection in minutes rather than weeks.
Nvidia GTC 2026: Arango invites AI leaders and builders to explore the Contextual Data layer powering production AI Agents. Visit Booth 3421 to see how Arango's out-of-the-box contextual data layer enables AI agents to reason, decide, and act using unified, current, and trusted business context at enterprise scale. Arango, announced it is participating in Nvidia GTC 2026, taking place March 16-19 at the San Jose Convention Center.AI leaders and builders attending the event are invited to visit Booth 3421 to meet Arango executives and contextual data experts, explore demonstrations, and see how organizations are using a contextual data layer to power AI agents that reason, decide, and act across enterprise data. The Business Context Gap in Enterprise AI As enterprises race to deploy AI agents that can reason, decide, and act across complex workflows, many are discovering that the biggest barrier isn't the model - it's the lack of business context connecting fragmented enterprise data. At Nvidia GTC 2026, Arango will demonstrate how organizations are closing this gap by building a contextual data layer that enables AI systems to understand what things mean, how they relate, when they were true, and where they came from - creating a foundation where organizations define business context once and reuse it across AI agents, applications, and workflows. Arango is trusted by leading organizations, including Nvidia, HPE, Linx Security, the US Air Force, and Articul8 to power mission-critical workload Why Business Context, Trust and Scale Matter for Enterprise AI Agents Nvidia GTC AI Conference brings together the global AI ecosystem to explore the latest advances in AI. From Jensen Huang's keynote on the future of accelerated computing and AI to technical sessions focused on building intelligent systems that can reason, plan, and act, the conference highlights the technologies shaping the next wave of enterprise AI. As organizations move from experimentation to deploying AI agents in production, many encounter a critical gap in the AI stack: the absence of a unified business context layer that connects fragmented enterprise data. Industry analysts increasingly highlight the importance of unified multimodel data platforms that combine graph, vector, document, and other data types to support advanced AI workloads and reasoning systems. For example, The Forrester Multimodel Data Platforms Landscape, Q4 2025 highlights the growing role of multimodel data architectures in helping organizations manage complex, interconnected data required for AI systems that enterprises can trust to reason, decide, and act. Real-World Applications for Context-Driven AI Organizations are increasingly recognizing the need for a contextual data layer to power AI agents across complex enterprise workflows. Examples include: * AI support agents for engineers diagnosing issues across products, systems, and documentation * Engineering and semiconductor design intelligence where AI agents trace chip designs and product changes across development, testing, and production systems * Customer service co-pilots guiding frontline staff with real-time operational context * Cybersecurity investigations where AI agents analyze relationships between alerts, systems, and vulnerabilities to identify root causes and remediation steps * Clinical trial intelligence where AI agents identify high-performing trial sites by reasoning across investigators, institutions, protocols, and outcomes * Supply chain intelligence and digital twins where agents reason across suppliers, logistics networks, and operational systems * Video intelligence and incident response where AI agents reason over live video streams and enterprise data to deliver instant, explainable insights Many organizations attempt to assemble this contextual layer themselves - starting with vector search for retrieval, then adding graph technologies for relationships, document stores for content, and pipelines to connect everything together. The result is a complex, fragile, and fragmented stack that becomes difficult to maintain as AI initiatives scale. Arango delivers this contextual data layer out of the box, allowing teams to power AI systems with unified business context without stitching together multiple databases and pipelines. See Context-Driven AI in Action at Booth 3421 At Booth 3421, Arango, a member of the Nvidia Inception Program, will showcase live demonstrations of the Arango Contextual Data Platform, illustrating how organizations empower AI agents with unified, current, and trusted business context at scale through a simplified, agentic-AI-ready data architecture delivered out of the box. Live Demonstrations * Integrated Circuit Design Knowledge Graph Trace chip designs from development through production support. AI agents reason across engineering data, documentation, and system records to accelerate troubleshooting and design decisions * Infrastructure Security: Root Cause and Remediation Identify failures, configuration changes, root causes, and remediation steps by connecting alerts, logs, and documentation into a unified operational context * Nvidia Video Search and Summarization + Arango GraphRAG Turn hours of video into actionable insights by connecting video evidence with enterprise data, enabling AI agents or humans to detect events, identify patterns, and accelerate operational decisions. Nvidia will also be featuring version 3.0 of this blueprint at their booth * Arango Contextual Data Platform 4.0 New Features Arango will unveil the Arango Contextual Data Platform 4.0 and highlight key feature demos on March 17, 2026 during Nvidia GTC "Enterprises are deploying AI agents that must reason, decide, and act across complex business environments - but without the right business context across enterprise data, they cannot succeed," said Shekhar Iyer, CEO, Arango. "At Nvidia GTC, we're excited to meet with AI leaders and builders and demonstrate how a contextual data layer helps make AI systems reliable and production-ready."
Arango has launched Contextual Data Platform 4.0 at NVIDIA GTC, designed to help organisations build enterprise AI agents and applications more reliably. The platform introduces a Contextual Data Layer that transforms fragmented enterprise data into unified business context for AI systems. The release includes the Agentic AI Suite with over 20 built-in AI services, AutoGraph for automated context graph generation, AutoRAG for optimising retrieval, and Ada, an AI digital assistant. The platform supports deployment across cloud, on-premises and hybrid environments. Early adopters report 30–50% reduction in integration complexity and 2–4× faster AI development cycles. Customers include PSI CRO, Matpriskollen, Transient.AI and Linx Security. The platform also supports Bring Your Own Code/Container deployment, allowing organisations to integrate preferred models whilst maintaining security and compliance control.
Transient.AI, an AI platform for capital markets, has selected Arango's AI Data Platform as its data infrastructure to deliver explainable, real-time intelligence for hedge funds, asset managers and investment banks. The partnership enables Transient.AI to model complex financial relationships whilst maintaining transparency in AI-driven outcomes. The New York-based company, founded in 2024, required a unified system capable of combining graph, vector and document data whilst supporting real-time analysis of interconnected entities including strategies, instruments and risk factors. Arango's multi-model platform eliminates data fragmentation across AI workflows, enabling explainable decisions at institutional scale. The infrastructure supports front-office workflows including institutional sales, trading and research by delivering AI-driven recommendations on counterparty engagement and market opportunities. Financial institutions face mounting regulatory pressure to ensure AI decisions are both accurate and auditable.
Arango launches AI Data Platform at NVIDIA GTC introducing Contextual AI: Enterprise AI powered by business context. Arango AI Data Platform gives you a trusted data foundation for Contextual AI - transforming enterprise data into a System of Context that truly represents the business, so LLMs can deliver better outcomes with unlimited scale and cost efficiency. WASHINGTON-(BUSINESS WIRE)-Arango unveiled the Arango AI Data Platform, a trusted data foundation for Contextual AI - transforming enterprise data into a System of Context that truly represents the business, so LLMs can deliver better outcomes with unlimited scale and cost efficiency. Operating at the data infrastructure layer, Arango fills the missing layer in the AI stack - because traditional data architectures weren't built to support AI workloads or the data complexity they require. Arango launches AI Data Platform at NVIDIA GTC introducing Contextual AI: Enterprise AI powered by business context. Share. We're entering an era where context is the new currency of enterprise AI. Competitive advantage no longer comes from raw compute power - it comes from understanding business context. The leaders are building Systems of Context that connect every type of data - structured, semi-structured, and unstructured, from databases and logs to text, images, and video - so AI can recognize relationships, understand meaning, and deliver insights that make sense to the business. Without context, AI sees fragments instead of the full picture - delivering generic answers instead of answers or outcomes based on true business understanding. With it, enterprises move from disconnected data to accurate, explainable, and actionable intelligence that drives measurable ROI. Overcoming the Barriers to Enterprise AI Success Most AI applications can generate answers, but they can't understand the business because they're disconnected from enterprise data. They're built on fragmented stacks - separate databases, brittle pipelines, and missing relationships between data and meaning. When organizations try to scale copilots, chatbots, or agentic applications, those fragile architectures break under real-world scale, leading to inaccurate answers, stalled performance, and rising infrastructure costs. The Arango Advantage "Every enterprise building AI today is fighting the same battle: fragmented data, brittle pipelines, and runaway costs," said Ravi Marwaha, Chief Product & Technology Officer at Arango. "The problem isn't the models; it's the missing business context. Contextual AI shifts the focus from data integration to business understanding. With the Arango AI Data Platform, we're giving AI the business context it needs to deliver accurate, explainable, and actionable insights at scale and provide the repeatable ROI enterprises can measure." Arango solves this with a System of Context, a unified data foundation that connects relationships, meaning, and business context across all types of enterprise data. Within a single integrated environment, Arango unifies multimodal and multi-model data, including graphs, vectors, documents, key-value data, and full-text search, enabling AI to reason, retrieve, and respond with business understanding rather than isolated information. It understands relationships through graphs, meaning through vectors, and multimodal signals across text, structured data, and media, giving AI the ability to connect facts to context and deliver results enterprises can trust. By combining advanced capabilities such as Hybrid/GraphRAG, AIOps, MLOps, Graph Analytics, and GPU acceleration, Arango enables enterprises to: * Accelerate development: Eliminate data silos and fragile integrations. * Scale confidently: Handle billions of relationships with real-time performance. * Reduce cost and complexity: Consolidate tools, simplify maintenance, and achieve repeatable ROI. With Arango, enterprises gain context-aware AI applications that understand their business reality and solve specific problems with accuracy and scale. "Most enterprises have valuable data scattered across disconnected systems such as CRMs, ERPs, emails, product logs, and documents," said Marwaha. "The challenge isn't that they lack data; it's that the data lacks context. The System of Context changes that by unifying every source and mapping how things relate across all data so AI understands the business context. When AI sees the full picture, its answers, decisions, and actions become accurate, explainable, and trustworthy - making AI truly useful for business." Build Enterprise AI Faster with a System of Context With built-in ingestion pipelines, BYO LLM integrations, and context-aware RAG frameworks for GraphRAG, HybridRAG, and enterprise context management, Arango accelerates the path from prototype to production, ensuring every model response is grounded in enterprise knowledge. Teams can use natural-language querying to ask questions in plain English and instantly generate optimized Arango Query Language (AQL) commands, turning business questions into contextual outcomes in seconds while reducing developer workload. Just as Waymo's self-driving system fuses inputs from cameras, radar, and LiDAR into situational awareness, Arango fuses enterprise data into business context, enabling AI to perceive, interpret, and decide with accuracy and scale. This is the foundation of Contextual AI, giving models the ability to reason like humans but at machine speed and enterprise scale. Enterprise-Grade Results * Builds Trust: Connects relationships and meaning across all data types for accurate, explainable AI that understands business context. * Scales Without Limits: Handles billions of relationships with SmartGraph clustering and natural-language querying. * Cuts Costs: Consolidates multiple systems with GraphRAG, HybridRAG, and BYO LLM support, reducing total cost of ownership by up to 70%. With Arango, enterprises gain a dynamic System of Context that evolves with their data, models, and needs - enabling them to scale AI confidently, maintain trust, and turn insight into action. Building the Future of Enterprise AI The Arango AI Data Platform simplifies every stage of AI development, reducing time to delivery, eliminating integration headaches, and empowering teams to build faster. A new role is emerging: the Context Engineer - builders who design relationships, curate multimodal data, and connect it to reasoning. Arango equips them to architect understanding, not just pipelines. "Success in enterprise AI won't be defined by who has the biggest model but by who can connect their data into business understanding," added Marwaha. "With Arango, enterprises turn disconnected data into Contextual AI, delivering business results with context, confidence, and scale." New Product: The Arango AI Data Platform unifies graph, vector, document, and key-value data with full-text and multimodal search in a single System of Context. It connects relationships between all types of data to give AI business understanding and enables AI-powered applications with accurate, explainable insights, unlimited scale, and repeatable ROI. Product Launch: Official debut at NVIDIA GTC AI Conference, Washington, D.C., October 28, 2025. AI Ecosystem Fit: Arango serves as the AI data foundation that turns enterprise data into a System of Context - the layer that connects meaning, relationships, and reasoning across the business. With context-aware RAG (Hybrid/GraphRAG), Arango enables AI to retrieve, reason, and respond using the full spectrum of enterprise data, delivering accurate, explainable, and actionable insights that reflect business context across every AI-powered application. AI Suite: The Arango AI Suite delivers built-in capabilities for context-aware RAG, Hybrid/GraphRAG, AIOps, MLOps, Graph Analytics, and GPU acceleration within the same integrated environment. It allows teams to build, test, and deploy AI-powered applications faster, improve accuracy and scalability, and achieve repeatable ROI by operationalizing context-aware AI without managing multiple tools. Performance: Scales to billions of relationships with SmartGraph clustering, horizontal elasticity, and near-real-time performance under production workloads. Customers: Trusted by thousands of developers at more than 200 organizations - including NVIDIA, HPE, the London Stock Exchange, the U.S. Air Force, the National Institutes of Health (NIH), the French Ministry of Defense, Synopsys, and Articul8 - who rely on Arango to enable mission-critical applications at global scale. Learn More: See the Arango AI Data Platform in action at Booth I-2 during NVIDIA GTC Washington, D.C. Visit arango.ai or book a private preview. About Arango Arango gives you a trusted data foundation for Contextual AI - transforming enterprise data into a System of Context that truly represents the business, so LLMs can deliver better outcomes with unlimited scale and cost efficiency. The Arango AI Data Platform gives developers a single, integrated environment to build and scale AI-powered applications without the complexity of stitching together multiple databases and tools. At its core is a massively scalable multi-model database that unifies graph, vector, document, and key-value data with full-text, geospatial, and vector search, creating the System of Context - the bridge between enterprise data and AI-powered applications. The Arango AI Suite includes automated data pipelines, multimodal data ingestion, AIOps and MLOps, LLM integrations, Graph Analytics, agentic frameworks for context-aware Hybrid/GraphRAG, GraphML, natural-language support, and GPU acceleration, enabling repeatable ROI and faster innovation. Trusted by NVIDIA, HPE, the London Stock Exchange, the U.S. Air Force, NIH, and Articul8, Arango powers enterprise AI with context, confidence, and scale. Learn more at arango.ai, LinkedIn, YouTube, and G2.