AI Software Engineer

At Commencis, we are seeking an AI Software Engineer to join our team. As part of our AI Lab ecosystem, you will design and build production-grade LLM applications and agentic systems, working on real-world enterprise problems. You will take part in the full lifecycle of AI systems, from data and model development to deployment, evaluation, and optimization. 

If you are curious by nature, adaptive, collaborative, and always one step ahead, then join us and be a Commencer!

Responsibilities

• • Collaborate with product and software teams to integrate AI solutions and forward-deploy production-grade systems into enterprise applications

    
    
  
  

  • Drive proof-of-concept initiatives and publish insights on emerging techniques

    
    
  
  

  • Orchestrate LLM-based agentic systems

    
    
  
  

  • Contribute in full-cycle AI development, from data pipelines and model training to deployment and monitoring

    
    
  
  

  • Design, build, and optimize production-grade machine learning models

    
    
  
  

  • Implement robust MLOps practices using Kubernetes, MLflow, and cloud services (AWS, Azure, GCP)

    
    
  
  

  • Advocate for ethical AI principles, ensuring fairness, transparency, and security

    
    
  
  
  

Qualifications

• • BSc/MSc/PhD in Computer Science or related field

    
    
  
  

  • Proficiency in Python, ML frameworks (PyTorch, TensorFlow), and transformer-based architectures

    
    
  
  

  • Proven experience in fine-tuning generative models (e.g. open-source LLMs, diffusion models)

    
    
  
  

  • Experience deploying AI solutions using containerization (Docker, Kubernetes) and CI/CD pipelines.

    
    
  
  

  • Proficiency in at least one agentic orchestration framework for building LLM-based systems

    
    
  
  

  • Comfortable working in AI-first development environments, leveraging agentic tools (e.g., Claude Code, Codex) to plan, build, and iterate faster.

    
    
  
  
  

Nice to Have

• • Contributions to open-source AI projects

    
    
  
  

  • Expertise in LLM evaluation, and performance-cost optimization

    
    
  
  

  • Experience with advanced AI domains (graph neural networks, reinforcement learning)

    
    
  
  

  • Active engagement in AI communities (Kaggle, Huggingface).

    
    
  
  

  • Experience with agentic orchestration frameworks such as LangGraph, Google ADK, or similar tools