Generative AI Developer – Freelance
Equativ (formerly Smart)
contract
Posted on:
Location Type: Hybrid
Location: Paris • 🇫🇷 France
Visit company websiteJob Level
Mid-LevelSenior
Tech Stack
CloudKubernetesPython
About the role
- Design, develop, and deploy goal-oriented AI agents and multimodal or conversational experiences (leveraging frameworks like Langchain, LangGraph, or AutoGen) to automate complex, high-impact workflows within our flagship product
- Own the industrialization and production lifecycle of deployed agents, establishing robust AIOps/AgentOps processes for monitoring performance, ensuring version control of agent blueprints, and guaranteeing production-grade reliability and low-latency response times
- Collaborate closely with Product Managers to translate complex business challenges into concrete, measurable GenAI solutions, focusing on maximizing the return on investment (ROI) of LLM and agent usage
- Develop the specialized backend services and tool-calling APIs necessary for agents to interact securely and effectively with our existing enterprise systems and data sources
- Develop modular, reusable components for the internal Agentic Platform, including dynamic toolkits, sophisticated orchestration layers, and specialized evaluation harnesses for agent performance and safety
- Implement and optimize the entire data infrastructure pipeline critical for GenAI, including managing Vector Databases, designing highly efficient RAG (Retrieval-Augmented Generation) pipelines, and establishing mechanisms for continuous Fine-Tuning
- Champion and implement GenAI-native development standards, integrating best practices for AIOps, CI/CD, and documentation to ensure maximum code reusability and operational quality at scale
- Lead the technical watch on the evolving LLM landscape (e.g., open-source vs. proprietary models) and spearhead the adoption of advanced techniques such as prompt engineering, multi-agent coordination, and complex agentic pattern design
Requirements
- Master's degree in Computer Science, Data Science, or a similar technical field
- 3+ years of significant experience as a Python Developer or ML Engineer, with a recent focus on deploying solutions powered by Large Language Models (LLMs)
- Proven expertise in building production-ready AI agent workflows, orchestration layers, or platforms using Python frameworks (e.g., Langchain, LangGraph, or AutoGen)
- Mastery of Python for enterprise-level development, strong knowledge of core software development principles, and experience integrating AIOps/MLOps best practices (unit tests, CI/CD, Git)
- Practical experience with modern cloud platform technologies (VertexAI, Kubernetes or equivalents) for deploying scalable GenAI services
- Strong versatility and a demonstrated willingness to work across the full stack—from backend agent logic to Vector DB and RAG infrastructure
- Entrepreneurial mindset, high autonomy, and the ability to turn ambiguous, high-level business goals into concrete, efficient GenAI features
- Fluent technical English (written and verbal).
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
PythonAI agentsLarge Language Models (LLMs)AIOpsMLOpsVector DatabasesRetrieval-Augmented Generation (RAG)prompt engineeringmulti-agent coordinationsoftware development principles
Soft skills
entrepreneurial mindsethigh autonomycollaborationproblem-solvingcommunication
Certifications
Master's degree in Computer ScienceMaster's degree in Data Science