Fullstack Software Engineer

Requirements

• I’m looking for someone with solid engineering foundations, curiosity, product sensitivity, and the willingness to learn how to turn ambiguous problems into useful software
• You are a backend or full‑stack engineer
• You have experience building web applications, backend services, APIs, or distributed systems
• You have solid foundations in at least part of our core stack, especially Node.js, Type

  Script, React, or Graph

  QL
• You care about product and business impact, not only technical output
• You are curious and comfortable asking questions when the problem is not fully clear
• You can contribute to turning a loosely defined problem into shipped software
• You enjoy working with Product, Data, Sales, Customer Success, Customer Care, and Operations
• You are curious about AI, automation, agents, CLI tools, and modern engineering workflows
• You care about reliability, maintainability, security, observability, and user trust
• You communicate clearly in English
• Put another way: I’m looking for someone who gets energy from building useful software, learning fast, and helping turn messy growth or operational problems into simple, measurable solutions
• (Desirable) You already use tools like Copilot, Claude, CLI agents, MCP workflows, or custom automations to work differently
• (Desirable) You have worked on B2B SaaS, growth, monetization, onboarding, sales‑assist, or product‑led growth topics
• (Desirable) You have built internal tools, automations, or operational workflows that saved time or reduced costs
• (Desirable) You are comfortable with data pipelines, reverse ETL, analytics engineering, or customer data platforms
• (Desirable) You have experience with PostgreSQL, Elasticsearch, DBT, AWS Glue, Hightouch, Datadog, or Grafana

What the job involves

• At TheFork, we help restaurants grow, manage demand, and connect with millions of diners across Europe
• That sounds simple. In reality, there is a lot of complexity behind it
• Restaurants need to onboard faster
• They need to understand the value of our products
• They need better data to make better decisions
• They need software that reduces friction instead of adding more
• Internally, our Sales, Customer Care, and Moderation teams are looking for modern tools and AI that solve real problems, making sure that actual leverage always comes before the trend
• That’s where this team comes in
• The Growth & GTM engineering team exists to unlock leverage across B2B growth and operational efficiency
• Sometimes that leverage is a product feature
• Sometimes it is an internal tool
• Sometimes it is a data workflow
• Sometimes it is an AI‑powered automation, an MCP workflow, or a CLI‑based prototype
• And sometimes, the best engineering decision is to not build anything until we better understand the problem
• This is not a role where engineers only receive tickets and implement them in isolation
• I’m looking for an engineer who wants to get close to the business problem, understand the product context, contribute to technical decisions, ship reliable software, and learn from production
• Someone who wants to be close to the problem, not just close to the code
• You’ll work on problems that sit at the intersection of product, engineering, data, operations, and AI
• A few examples:
• Helping restaurants activate faster and get more value from TheFork
• Improving monetization, upsell, product discovery, or referral loops
• Exposing useful data and recommendations to restaurants or internal teams
• Automating repetitive workflows for Customer Care, Sales, Moderation, or Operations
• Building internal tools that help teams move faster without adding more process
• Prototyping AI agents, MCP workflows, CLI‑based automations, or internal copilots
• Reducing operational costs by turning fragmented data and manual work into reliable systems
• Some of these projects will be clean product features
• Some will be scrappy prototypes
• Some will require going deep into existing systems
• Some will start with a messy business problem and no obvious solution
• You won’t be expected to solve everything alone. You’ll work with experienced engineers, Product, Data, and business teams to understand the problem, contribute to the solution, and grow your ownership over time
• That’s the job
• How we think about engineering:
• We care about impact, but not in a vague “move metrics” way
• We care about software that changes something real: a restaurant activating faster, a sales team saving time, a support workflow becoming simpler, a moderation process costing less, or an internal team making better decisions because the right data is finally available
• We like engineers who ask questions before building
• We like prototypes when they help us learn faster
• We like clean systems when the problem deserves long‑term investment
• We like boring, reliable software when reliability matters more than cleverness
• We also like AI and automation, but not as decoration
• AI is useful when it removes repetitive work, speeds up decision‑making, improves internal workflows, or helps engineers increase their own leverage
• If you are already using tools like Copilot, Claude, CLI agents, MCP workflows, or custom automations to work differently, you’ll probably enjoy this environment
• The goal is not to put AI everywhere
• The goal is to use modern tools intelligently to solve real problems
• The technical stack used by the team:
• In the Growth & GTM team, we mainly work with:
• Node.js, Type

  Script, React, Graph

  QL
• PostgreSQL, Elasticsearch
• DBT, AWS Glue, Hightouch
• Datadog, Grafana
• GitHub Copilot, Claude, AI CLI tools, MCP workflows
• Across The

  Fork, you may also interact with Kubernetes, AWS, Rabbit

  MQ, and some legacy PHP/Symfony services
• You don’t need to have used every tool already. Solid technical foundations, curiosity, and fast learning matter more than exact stack matching
• Why this is interesting:
• Restaurants are one of the most operationally complex industries in Europe
• A lot of value is still trapped in manual workflows, fragmented data, and software that does not yet do enough of the work
• That creates a lot of room for engineering leverage
• A better onboarding flow can help thousands of restaurants activate faster
• A smarter monetization flow can move revenue
• A good internal automation can save hundreds of hours
• A useful data product can change how teams make decisions
• A pragmatic AI workflow can remove repetitive work and let people focus on higher‑value problems
• You’ll join a Paris‑based team working with colleagues across Europe