AI Agent Builder

Mirakl - Labs•Boston, MA

3d•$150,000 - $190,000•Hybrid

About The Position

Mirakl is seeking an AI Agent Builder to design, build, and scale internal AI agents that integrate with company systems, automate workflows, and deliver measurable operational impact. This is a hybrid role requiring 4 days in the Boston office and 1 day remote per week. The role is central to Mirakl's strategy in agentic AI, moving from experimentation to internal agent industrialization to power the company's future. Mirakl is already building AI agents and this role will be at the forefront of this initiative.

Requirements

5 plus 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.

Nice To Haves

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

Responsibilities

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, and rapidly prototype solutions evolving them into production-grade products.
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), and ensure reliable orchestration between APIs, tools, and data sources.
Iterate for Impact: Run pilots with end users and gather qualitative and quantitative feedback, analyze usage, errors, and performance metrics, and continuously improve accuracy, reliability, and user experience.
Ensure Security & Quality: Implement robust guardrails, validation layers, and access controls, ensure compliance with data security and governance standards, and clearly document each agent (scope, capabilities, limitations, KPIs, roadmap).
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, and act as a champion for AI-driven ways of working.
Collaborate with process owners, the Solution architect, and the Data team.