AI Operations Engineer Intern (M/F/X)

About Crossbeam

The highest-performing go-to-market teams have figured out how to turn their partner ecosystem into a revenue engine, and Crossbeam is the platform that makes that possible. Companies use Crossbeam to securely compare CRM data with partners, revealing shared customers, overlapping prospects, and warm paths into deals.

That second-party data becomes Ecosystem Intelligence - a layer of unique signals and recommendations that helps revenue teams uncover new opportunities, target the right accounts, and win faster. We pioneered the category of ecosystem-led growth, and now we're defining what comes next: go-to-market powered by AI-native ecosystem intelligence.

The Role

AI is only as good as the context you give it. Companies often plug an LLM into their CRM and get generic answers. At Crossbeam, we're building our own GTM context layer: our revenue data, definitions, playbooks and skills, versioned like code and served to every AI tool our teams use. It's what lets a rep ask Claude about an account and get an answer grounded in our real data and our way of selling.

As our AI Operations Engineer Intern, you'll join the Operations team to build and run that layer with the AI Operations Manager. Think of it as being a platform engineer whose users are Sales, Customer Success, Partnerships and Finance.

📅 Start date: March, 2027 - 6 months internship.

📍 Paris: 37 av Trudaine 75009, Paris

Your missions

• Build the context layer: turn data from Salesforce, Gong, HubSpot, billing and product systems into clean, documented datasets using Snowflake, dbt, Fivetran.

• Make knowledge searchable: Make unstructured business knowledge searchable through vector stores and combine semantic search with structured data so agents can retrieve relevant deal insights.

• Maintain context as code, grounded in how teams work: Work with relevant teams across Sales, Business Development, Customer Success, Partnerships and Demand Generation to document roles, workflows and success criteria. Version definitions, skills, team-specific plugins and playbooks in GitHub, and publish human-readable documentation.

• Build and connect AI agents: Develop agents for deal intelligence, sales outreach, meeting preparation and follow-up, or signal monitoring. Contribute to MCP connectors and integrations, including Claude in Slack, so AI tools can access internal systems safely.

• Keep context and workflows reliable: Help build feedback loops and n8n routines to keep context up to date as data and processes change. Bring workflows into GitHub and contribute to their testing, review and deployment.

• Measure quality and support adoption: Build evaluations to check answer accuracy, track usage and iterate on errors with users. Help teams use AI workflows and agents effectively and share best practices.

How the internship works: you’ll spend your first month getting hands-on across the stack (context layer, agents) and sitting with the teams. By the end of that month, we’ll pick one project together, based on what the business needs most and where you want to grow, and you’ll own it end to end, from design to production.

What you'll learn

• Context engineering: structure business knowledge so AI systems can provide reliable, company-specific answers.

• Modern data engineering: SQL, dbt, Snowflake, data modeling and documentation.

• Software practices: Git, pull requests, code review, testing and versioning applied to AI systems.

• LLM systems in production: MCP, agents, retrieval (vector search and hybrid search over structured data), orchestration, evaluation, cost and access governance.

• GTM operations: understand how commercial teams work and translate their needs into useful AI workflows.

This experience is relevant to paths such as AI Engineer, Forward Deployed Engineer or GTM Engineer.

Our stack

• AI: Claude (including Claude Code, skills and plugins and all related features), ChatGPT

• Data and context: Snowflake, dbt, GitHub, Fivetran

• Orchestration: n8n

• Source systems: Salesforce, Gong, HubSpot, Maxio, raw product data

You might be a fit if

• You're studying engineering, computer science, data or a similar field, or you've taught yourself and can show it.

• You write SQL and at least one language (Python, JavaScript), and you're comfortable in a terminal and with Git.

• You've built something with LLMs: an agent, a RAG project, an MCP server, a side project. Show us.

• You care about making systems reliable and documented, not just making demos.

• You enjoy talking to people: you can interview a sales rep about their day and turn it into clear documentation.

• You're curious about the business side and enjoy having internal users.

• You speak French and English fluently.

• 6-month final-year internship or second half of a gap year.

Hiring process

• Intro call with our HR Generalist (30 min)

• Technical case: given a sample of GTM data and a business question, design the context (models, definitions, a skill) that lets an AI answer it reliably. Any AI tools allowed; walk us through your choices.

• Meeting with the AI Operations Manager (1 hour)

• Culture fit with the AI Operations Manager, our Revenue Operations Lead and the team at the office

Our core values

Values are a social contract that we have with our team, our users, and our communities. They are guiding lights as well as argument-enders, and we expect results delivered in a way that is consistent with these values.

Trust is our Foundation

We create value by building trust in our company, our team, and our technology. That goes in all directions, not just between us and our customers but also amongst ourselves. We approach conflict with empathy and curiosity, and ascribe best intentions to all of our collaborators.

Work Hard and Smart

This is a startup, and we will act like one. We prioritize impact, take personal ownership of outcomes, act decisively, and get our hands dirty in the process. We communicate clearly, avoid over-engineering, and take risks. This allows us to be creative, innovative, and solution-oriented.

Default to Transparency

We will not succeed in information silos. We share the good, bad, and ugly about what is happening in our company, which requires us to pay attention, always measure what matters, and hold each other accountable.

Belonging

In our workplaces, communities, and ecosystems, we shape environments where people feel a sense of belonging. To do this, we work to ensure that stakeholders of all backgrounds are treated equitably and experience psychological and physical safety. This is key to their relationship with our company, their access to opportunities, and their ability to thrive.

Treasure the Fun

We are incredibly lucky to be here: let's make memories. We will all spend that extra bit of time and energy to energize each other with fun and inspiring experiences. This applies internally and externally, from the smallest interactions to the largest events.

Equity sits at the heart of our hiring process, and we're proud to be building a culture where differences are valued. Applicants from diverse and non-traditional backgrounds are strongly encouraged to apply.

Curious to meet the team and learn more about our culture? Check out our profile on Welcome to the Jungle!