About CONXAI
CONXAI has built a no-code, agentic AI platform for the Architecture, Engineering and Construction (AEC) and physical industries, focused on knowledge-automation. We automate high-stakes, knowledge-intensive workflows traditionally trapped in siloed data, fragmented tools and tacit (undocumented) human expertise.
Our multi-agent systems perform complex reasoning in the physical world; and transform bespoke, service-heavy processes into scalable Service-as-a-Software automation.
CONXAI is trusted by some of the leading AEC companies in Europe, US, LATAM and Japan.
**Your Role
Automate the lifecycle management of Agentic AI and Large Vision Model**
As the Lead MLOps Engineer, you are the bridge between experimental ML models and scalable, reliable enterprise software. You will be responsible for the "factory line" of our AI - from training automation to the deployment of agentic tools. You’ll ensure our multi-agent systems (LLMs + Computer Vision) remain performant, cost-effective, and accurate.
What You’ll Do
- Agentic Orchestration: Build and optimize the infrastructure for LangChain/LangGraph, enabling complex multi-agent reasoning
- Training Automation: Develop automated pipelines for fine-tuning LLMs and training Computer Vision models specifically for industry use cases
- Model Deployment: Containerize and deploy models using Docker and Terraform, ensuring low-latency inference for high-stakes workflows
- Lifecycle Management: Implement monitoring for AI "silent failures," tracking model drift and performance metrics to ensure consistent customer success
- ML Infrastructure: Manage the compute-heavy environments required for AI, optimizing for both performance and unit economics
Who You Are
- 5+ years in MLOps or ML Engineering, with experience in both NLP (LLMs) and Computer Vision
- Agentic Expert: Deep familiarity with agentic frameworks like LangChain or LangGraph
- Tech Stack: Expert in Terraform, Docker, and GitLab CI/CD pipelines
- Strategic Mindset: You understand that an AI model is only as good as its production reliability and its impact on the user’s ROI
Why CONXAI
- Edge of Innovation: Architect the production backbone for real-time, low-latency agentic AI
- High Autonomy: Drive the end-to-end MLOps strategy, from automated retraining pipelines to sophisticated model monitoring at scale
- Top-Tier Peer Group: Partner with a global team of ML researchers and software engineers to bridge the gap between "experimental" and "mission-critical"
- Equity & Scale: Competitive compensation with significant equity upside