Leadership & Executive VP, Director, C-Suite, General Manager

What excites this persona

  • Category-defining opportunity: Not optimising an existing market — creating a new one
  • Market timing: $2T+ AI spend, 95% pilot failure rate — the problem is urgent and massive
  • Proven traction: Gartner Leader (2x), Forrester Leader, Fortune 500 customers
  • Founder quality: Prukalpa Sankar & Varun Banka — thoughtful, mission-driven leadership
  • Strategic influence: Shape the direction of a company at an inflection point

How to explain Atlan

"Companies are spending trillions on AI that doesn't work because it doesn't understand the business. Atlan builds the infrastructure layer — the context layer — that gives AI that understanding. We're defining a new category, like Snowflake did for data warehousing."

Objection handling

  • "Never heard of this category" → That's the point — Gartner and Forrester are validating it now. Early category = outsized impact.
  • "How big can this get?" → Every company deploying AI needs a context layer. This is the AI-era equivalent of the data warehouse.
Product Management PM, Group PM, Director of Product, CPO

What excites this persona

  • Zero-to-one product thinking: No playbook exists for this category — you write it
  • Complex user landscape: Data engineers, business analysts, AI architects, domain experts — wildly different needs
  • AI-native product: AI isn't a feature; it's the core architecture (context bootstrapping, auto-classification)
  • Platform play: 80+ integrations, APIs, SDKs — platform thinking required
  • Real enterprise scale: Workday catalogued 6M+ assets; Nasdaq depends on this daily

How to explain Atlan

"AI fails in production because it doesn't understand business context — definitions, rules, exceptions. We build the product that captures that context and makes it available to every AI tool. Think of it as the operating system for enterprise AI's understanding of the business."

Objection handling

  • "Is this just a data catalog?" → Data catalogs were chapter one. The context layer is chapter two — it serves AI at inference time, not just humans browsing metadata.
  • "Sounds niche" → Every enterprise deploying AI needs this. $2T market. Gartner calls it foundational infrastructure.
Backend Engineering Backend SWE, Staff Engineer, Principal Engineer

What excites this persona

  • Knowledge graph infrastructure: Enterprise-scale graph databases, real-time traversal, context retrieval APIs
  • 80+ integration connectors: Snowflake, dbt, Databricks, BI tools, Slack — deep system integration
  • AI pipelines: Context extraction, bootstrapping, semantic classification at scale
  • Real-time serving: Millions of context retrievals per day for AI agents
  • Hard problems, not CRUD: Distributed systems, graph algorithms, policy engines

How to explain Atlan

"We build the graph infrastructure that captures how a company's data, rules, and relationships connect — then serve that context to AI agents in real-time. Think knowledge graphs + real-time APIs + 80 system integrations at enterprise scale."

Objection handling

  • "Is this just ETL?" → No — we don't move data. We build the meaning layer on top. Graph infrastructure, not pipelines.
  • "What's the scale?" → Workday: 6M+ assets. Millions of context retrievals/day. Fortune 500 SLAs.
Frontend Engineering Frontend SWE, UI Engineer, Design Engineer

What excites this persona

  • Enterprise UX that matters: Making millions of data relationships navigable & intuitive
  • Interactive graph visualisation: Knowledge graphs, lineage views, relationship explorers
  • Collaborative workflows: Multi-user annotation, review, and certification flows
  • Performance at scale: Rendering complex graphs and data structures smoothly
  • Craft valued: Rare B2B company where frontend quality is a competitive advantage

How to explain Atlan

"We make the most complex data relationships in the world feel simple. Our product visualises how an entire company's data connects — and lets domain experts annotate, approve, and manage that knowledge. Enterprise infra where frontend craft genuinely matters."

Objection handling

  • "Enterprise UX is boring" → Not when you're building interactive graph explorers, real-time collaboration, and designing patterns that don't exist yet.
Full-Stack Engineering Full-Stack SWE, Senior SWE

What excites this persona

  • End-to-end ownership: From graph APIs to interactive UIs — own the full experience
  • Breadth of challenges: Backend graph infra + frontend data viz + AI integration in one product
  • Small team, big impact: Your code powers AI for Nasdaq, Mastercard, General Motors
  • New design patterns: No established playbook — invent how context layers should work

How to explain Atlan

"You'd own features end-to-end: from the knowledge graph APIs that serve context to AI agents, to the collaborative interfaces where domain experts certify business definitions. Full-stack in the truest sense, on infrastructure that matters."

Infrastructure / Platform Engineering Platform SWE, SRE, DevOps, Cloud Engineer

What excites this persona

  • Enterprise-grade reliability: Fortune 500 SLAs, ISO 27001/27701, GDPR/HIPAA compliance
  • Scale challenges: Millions of metadata assets, real-time serving, multi-tenant architecture
  • Cloud-native infra: Distributed systems, graph databases, vector stores at scale
  • Developer platform: APIs, SDKs, MCP server — building for external developers too

How to explain Atlan

"We build the platform that runs the context layer — multi-tenant, enterprise-grade, serving millions of context queries daily with Fortune 500 reliability requirements. Graph databases, vector stores, real-time APIs, all at scale."

Data / AI / ML Engineering Data Engineer, ML Engineer, AI Engineer, Data Scientist

What excites this persona

  • Context engineering > prompt engineering: Gartner declared the shift in 2025 — this is the frontier
  • AI bootstrapping: Using LLMs to auto-generate business definitions from existing data/docs
  • GraphRAG & knowledge graphs: Next-gen retrieval architectures, not just vector search
  • Context at inference time: Serving the right context to AI agents when they reason
  • Solve the real AI bottleneck: Models are commoditising; context is the new differentiator

How to explain Atlan

"We're building the infrastructure that makes AI actually work in enterprises. Context engineering — extracting, storing, and serving business meaning to AI at inference time. This is the layer between the data stack and AI agents. Models are commoditising; context is the differentiator."

Objection handling

  • "I want to work on models, not infrastructure" → Models without context are useless (95% fail rate). Context engineering is where the impact is. Gartner agrees.
Design Product Designer, UX Researcher, Design Lead, Head of Design

What excites this persona

  • Greenfield design space: No established patterns for human-AI context collaboration
  • Complexity → simplicity: Making 6M+ data assets navigable for non-technical users
  • Enterprise + craft: Rare B2B company with genuine design investment
  • Strategic influence: Small team — shape how enterprises interact with AI
  • Research-rich domain: Deep user research needed across data engineers, analysts, executives

How to explain Atlan

"We're designing the interfaces for a new category of software — one where humans and AI collaborate on understanding an organisation's data. It's complex, novel, and the patterns don't exist yet. You'd help define them."

Sales AE, Sales Leader, Solutions Engineer, SDR/BDR

What excites this persona

  • Category creation: Not selling into an existing market — creating one
  • Gartner Leader x2: Massive enterprise credibility already built
  • $2T tailwind: Every enterprise needs context for AI; the market is pulling
  • Teach, don't pitch: Evangelism-led sales — educate the market on a new concept
  • Fortune 500 deals: Nasdaq, Mastercard, GM, Unilever — land and expand at the top

How to explain Atlan

"You'd be selling the fix for why enterprise AI doesn't work. Every company deploying AI is hitting the same wall — the AI doesn't understand the business. We're the solution, with Gartner validation and Fortune 500 logos already."

Objection handling

  • "Hard to sell a new category" → Gartner and Forrester are doing the evangelism for us. The market is actively looking for this.
  • "What's the deal size?" → Enterprise contracts with Fortune 500. Land and expand model.
Customer Success CSM, Customer Success Lead, Director of CX

What excites this persona

  • Strategic partnerships: Deep, consultative relationships — not ticket queues
  • Fortune 500 customers: Help Nasdaq, Mastercard, GM transform their AI programs
  • High-impact advisory: Help data leaders map business context and design governance
  • Category education: Be the expert who helps customers understand a new paradigm
  • Measurable ROI: Directly tied to whether their AI programs succeed or fail

How to explain Atlan

"Customer Success at Atlan is deeply strategic. You'd help Fortune 500 companies map their business context, design governance workflows, and ensure their AI investments actually deliver ROI. This is consulting-level work, not reactive support."

Technical Support Support Engineer, Technical Support Specialist

What excites this persona

  • Technical depth: Supporting integrations with Snowflake, dbt, Databricks, and 80+ systems
  • Enterprise calibre: Working with sophisticated data teams at global companies
  • Learning opportunity: Deep exposure to the cutting edge of AI infrastructure
  • Path to engineering/CS: Natural stepping stone to deeper technical roles

How to explain Atlan

"You'd be the technical expert helping enterprise data teams integrate and use the context layer. This means deep knowledge of data stacks, real debugging, and working with some of the most sophisticated data teams in the world."

Marketing Content, Product Marketing, Demand Gen, Brand, Developer Marketing

What excites this persona

  • Category creation storytelling: Write the narrative for a brand-new market
  • Thought leadership platform: Gartner Leader status gives a massive stage
  • Technical + creative: Explain complex infrastructure to CxOs and data engineers
  • Content-led growth: 44+ guides already; content is a core growth engine
  • Multiple audiences: CDOs, data engineers, AI architects, procurement — rich segmentation

How to explain Atlan

"This is marketing at its most strategic — you're not promoting features, you're teaching the market a new way to think about AI. Category creation with a strong existing foundation (Gartner Leader, Fortune 500 customers, 44+ content pieces already)."

Finance FP&A, Controller, Finance Manager, CFO

What excites this persona

  • Strategic finance seat: Shape strategy at a category-defining company, not just track it
  • Enterprise SaaS model: Fortune 500 customers, land-and-expand, predictable revenue
  • Growth-stage dynamics: Fast-scaling company with real traction — finance is critical
  • Category economics: Help define pricing, packaging, and market sizing for a new category

How to explain Atlan

"Atlan is a Gartner Leader building the infrastructure layer for enterprise AI. Finance here means shaping the economics of a new category — pricing, unit economics, and strategic planning during a critical growth phase."

HR & People HR Business Partner, People Ops, Total Rewards, L&D, Head of People

What excites this persona

  • Culture at scale: Maintaining five strong values as the company grows fast
  • Distributed team challenges: Building connection and culture across geographies
  • Category-defining employer brand: Shape how the world sees Atlan as a place to work
  • Mission-driven culture: Values aren't just words — Bias for Action, Be Straightforward, etc.
  • Technical talent market: Competing for AI/data talent in the hottest market ever

How to explain Atlan

"We're building the people function for a company that's defining a new AI infrastructure category. That means hiring world-class talent into a category most people haven't heard of yet, building culture at scale, and creating programs that retain top performers in the hottest talent market ever."

Talent Acquisition Recruiter, TA Lead, Sourcer, Head of TA

What excites this persona

  • Sell a mission, not just a job: "Making AI actually work" is a compelling pitch
  • Category-defining company: Unique employer brand story — not "another SaaS startup"
  • Technical recruiting: Hire top AI/data talent in the most competitive market
  • Growth-stage impact: Every hire shapes the company's trajectory
  • Strong proof points: Gartner Leader, Fortune 500 customers — easy credibility

How to explain Atlan

"TA at Atlan means selling a genuine mission to top-tier talent. You have Gartner validation, Fortune 500 logos, and a problem (making AI work) that everyone in tech cares about. The pitch practically writes itself — but the execution is where great recruiters shine."

Operations BizOps, RevOps, Strategy & Ops

What excites this persona

  • Build the operating model: Define how a category-creating company scales operationally
  • Cross-functional impact: Touch engineering, sales, CX, finance — see the whole picture
  • Data-rich environment: Ironic perk: an infra company that practises what it preaches on data
  • Growth-stage complexity: Enterprise customers + fast scaling = meaty ops challenges

How to explain Atlan

"Operations at a growth-stage, category-defining company means building the operating model from the ground up — sales ops, go-to-market operations, cross-functional processes — while the company scales with Fortune 500 customers."

Hiring Manager Intake Prep Questions to ask before you start sourcing

Questions for the hiring manager

  • What's the "one-liner" for this role that a candidate would repeat to a friend?
  • What's the hardest problem this person will solve in their first 90 days?
  • How does this role connect to the context layer mission?
  • What would make a "passive but interested" candidate say yes?
  • What's the team's biggest technical/strategic challenge right now?
  • Which companies should we source from? Which should we avoid?
  • What's the non-negotiable vs. nice-to-have in the candidate profile?

Context to bring to intake

  • Share the Explainer page — ensure alignment on how to describe the company
  • Align on which campaign hooks to use for this role
  • Review the relevant persona section above for talking points
  • Agree on the candidate experience: how many rounds, who interviews, what's the sell