About the job

Design, build, and scale internal AI agents that integrate with company systems, automate workflows, and deliver measurable operational impact.

This is a permanent position (Freelance) based in Paris or Bordeaux, with 4 days on-site per week.

Why Now, Why Mirakl

The rise of agentic AI has fundamentally changed what's possible in our team automation. For the first time, AI agents can handle complex, multi-step workflows with minimal human intervention.

Mirakl is uniquely positioned to lead this shift. As an Operating system for intelligent commerce, technology is in our DNA. We've already deployed some AI agents using Dust, n8n, Claude Code and Langchain, and the early results are compelling. Now we need someone to take this from experimentation to internal agent industrialization — designing the system that will power the company of tomorrow.

You won't be joining a company that's thinking about AI. You'll be joining one that's already building it — and you'll be at the center of what comes next.

Who are we looking for?

Backend Engineer with AI exposure – solid on APIs, reliability, and scalable integrations, with growing experience in LLMs
Data / Analytics Engineer – strong on data structuring and business use cases, relevant for analytics-driven agents
ML / Applied AI Engineer – good understanding of LLMs, RAG, and evaluation, with potential to grow on productization

What You’ll Do

1. Design & Build AI Agents

• Create workflow-driven AI agents (e.g., BDR, Contract, Accounting agents)
• Architect multi-step agent systems including prompts, tools, memory, and guardrails
• Rapidly prototype solutions and evolve them into production-grade products

2. Integrate Across the Stack

• Connect agents to internal systems (CRM, data platforms, Drive, Jira, etc.)
• Enable agents to perform real actions (e.g., update CRM, generate reports, create tickets)
• Ensure reliable orchestration between APIs, tools, and data sources

3. Iterate for Impact

• Run pilots with end users and gather qualitative and quantitative feedback
• Analyze usage, errors, and performance metrics
• Continuously improve accuracy, reliability, and user experience

4. Ensure Security & Quality

• Implement robust guardrails, validation layers, and access controls
• Ensure compliance with data security and governance standards
• Clearly document each agent (scope, capabilities, limitations, KPIs, roadmap)

5. Drive Adoption & Enablement

• Build a clean, scalable agent ecosystem for internal users
• Support and educate teams on adopting agents in their workflows
• Contribute to internal best practices and agent-building standards
• Act as a champion for AI-driven ways of working

Collaborative: you work hand-in-hand with our process owners, the Solution architect and the Data team.     

Our stack and tools:

• GenAI APIs: OpenAI, Anthropic, Mistral, Gemini
• Agent & Automation Tools: n8n, Dust, Claude
• Cloud: AWS or GCP
• (Optional): LangChain, LlamaIndex
  
  

What Makes You Successful

• Strong product mindset: able to identify friction and design practical solutions
• Ability to turn ambiguous problems into structured, automated workflows
• Focus on measurable impact, not just technical output

Success Metrics

• Adoption: number of agents actively used and delivering value
• Automation rate: % of tasks completed without human intervention
• Performance: accuracy, reliability, and user satisfaction
• Business impact: time saved, quality improvements, operational efficiency

You'll Love This Job If you have 

• 3 to 5 years of experience as a Data Scientist, ML Engineer, or Software Engineer, with a background in backend/full-stack development, data, or automation workflows
• Proven experience building AI agents using LLMs, RAG, MCP and related technologies, including architectural design of multi-step agentic workflows
• Proficient in Python and data fundamentals (SQL, JSON, data modeling)
• Production deployment expertise, you've shipped AI solutions in production
• Experience with API integrations, MCP, webhooks, and connectors
• Experience with low-code/no-code automation platforms (n8n, Make, Zapier or equivalent)
• Curiosity and continuous learning, you stay current with AI/ML trends and love exploring new technologies
• Strong communication skills in both English and French

Feel free to add a link to your GitHub in your CV so we can understand what you have worked on!

Want to join us? Here is our process 

• A 40-minute phone conversation with one of our Tech recruiters. This will be an opportunity to discuss your background, expectations, and discover what Mirakl can offer you in return.
• An initial 1 hour technical discussion with a member of the Data Science team and Engineering Team, which will allow you to delve into the more specific aspects of your expertise and discover how your skills can be integrated into our projects.
• 2 x 45-minute "STAR" interviews with future Mirakl colleagues to discuss our values and company culture.

About the job

Design, build, and scale internal AI agents that integrate with company systems, automate workflows, and deliver measurable operational impact.

This is a permanent position (CDI) based in Paris or Bordeaux, with 4 days on-site per week.

Why Now, Why Mirakl

The rise of agentic AI has fundamentally changed what's possible in our team automation. For the first time, AI agents can handle complex, multi-step workflows with minimal human intervention.

Mirakl is uniquely positioned to lead this shift. As an Operating system for intelligent commerce, technology is in our DNA. We've already deployed some AI agents using Dust, n8n, Claude Code and Langchain, and the early results are compelling. Now we need someone to take this from experimentation to internal agent industrialization — designing the system that will power the company of tomorrow.

You won't be joining a company that's thinking about AI. You'll be joining one that's already building it — and you'll be at the center of what comes next.

Who are we looking for?

Backend Engineer with AI exposure – solid on APIs, reliability, and scalable integrations, with growing experience in LLMs

Data / Analytics Engineer – strong on data structuring and business use cases, relevant for analytics-driven agents

ML / Applied AI Engineer – good understanding of LLMs, RAG, and evaluation, with potential to grow on productization

What You’ll Do

1. Design & Build AI Agents

• Create workflow-driven AI agents (e.g., BDR, Contract, Accounting agents)
• Architect multi-step agent systems including prompts, tools, memory, and guardrails
• Rapidly prototype solutions and evolve them into production-grade products

2. Integrate Across the Stack

• Connect agents to internal systems (CRM, data platforms, Drive, Jira, etc.)
• Enable agents to perform real actions (e.g., update CRM, generate reports, create tickets)
• Ensure reliable orchestration between APIs, tools, and data sources

3. Iterate for Impact

• Run pilots with end users and gather qualitative and quantitative feedback
• Analyze usage, errors, and performance metrics
• Continuously improve accuracy, reliability, and user experience

4. Ensure Security & Quality

• Implement robust guardrails, validation layers, and access controls
• Ensure compliance with data security and governance standards
• Clearly document each agent (scope, capabilities, limitations, KPIs, roadmap)

5. Drive Adoption & Enablement

• Build a clean, scalable agent ecosystem for internal users
• Support and educate teams on adopting agents in their workflows
• Contribute to internal best practices and agent-building standards
• Act as a champion for AI-driven ways of working

Collaborative: you work hand-in-hand with our process owners, the Solution architect and the Data team.     

Our stack and tools:

• GenAI APIs: OpenAI, Anthropic, Mistral, Gemini
• Agent & Automation Tools: n8n, Dust, Claude
• Cloud: AWS or GCP

What Makes You Successful

• Strong product mindset: able to identify friction and design practical solutions
• Ability to turn ambiguous problems into structured, automated workflows
• Focus on measurable impact, not just technical output
  
  

Success Metrics

• Adoption: number of agents actively used and delivering value
• Automation rate: % of tasks completed without human intervention
• Performance: accuracy, reliability, and user satisfaction
• Business impact: time saved, quality improvements, operational efficiency

You'll Love This Job If you have 

• 3 to 5 years of experience as a Data Scientist, ML Engineer, or Software Engineer, with a background in backend/full-stack development, data, or automation workflows
• Proven experience building AI agents using LLMs, RAG, MCP and related technologies, including architectural design of multi-step agentic workflows
• Proficient in Python and data fundamentals (SQL, JSON, data modeling)
• Production deployment expertise, you've shipped AI solutions in production
• Experience with API integrations, MCP, webhooks, and connectors
• Experience with low-code/no-code automation platforms (n8n, Make, Zapier or equivalent)
• Curiosity and continuous learning, you stay current with AI/ML trends and love exploring new technologies
• Strong communication skills in both English and French

Feel free to add a link to your GitHub in your CV so we can understand what you have worked on!

Want to join us? Here is our process 

• A 40-minute phone conversation with one of our Tech recruiters. This will be an opportunity to discuss your background, expectations, and discover what Mirakl can offer you in return.
• An initial 1 hour technical discussion with a member of the Data Science team and Engineering Team, which will allow you to delve into the more specific aspects of your expertise and discover how your skills can be integrated into our projects.
• 2 x 45-minute "STAR" interviews with future Mirakl colleagues to discuss our values and company culture.