Senior AI Software Engineer

At Commencis, we are seeking a Senior AI Software Engineer to join our AI Lab ecosystem. In this role, you will design, build, and scale production-grade LLM applications and AI-powered systems that solve real-world enterprise problems.

You will take technical ownership across the full lifecycle of AI systems, from architecture and data pipelines to deployment, evaluation, monitoring, and continuous optimization. Working closely with product, software, and business teams, you will help shape AI-first solutions that create measurable impact.

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

• Lead the design and development of production-grade LLM applications and AI-powered enterprise system
• Architect scalable AI system components, including data pipelines, model integration, orchestration layers, evaluation workflows, and deployment infrastructure
• Collaborate with product, software, and business teams to translate enterprise needs into reliable AI solutions
• Design and orchestrate LLM-based workflows using modern frameworks, tools, and cloud-native architectures
• Drive proof-of-concept initiatives and turn promising ideas into scalable production solutions
• Adapt, fine-tune, and optimize machine learning and generative AI models where needed
• Implement and improve MLOps practices using containerization, Kubernetes, MLflow, cloud services, and CI/CD pipelines
• Evaluate AI applications in terms of quality, reliability, latency, cost, safety, and business impact
• Mentor engineers on AI engineering best practices, code quality, and production readiness
• Follow emerging AI techniques and share insights through prototypes, technical documentation, and internal knowledge-sharing
• Advocate for responsible AI principles, ensuring fairness, transparency, privacy, and security

BSc, MSc, or PhD in Computer Science, Engineering, or a related field

Strong hands-on experience with Python and modern machine learning frameworks such as PyTorch or TensorFlow

Proven experience designing, building, and deploying production-grade AI, ML, or LLM-based systems

Solid understanding of transformer-based architectures and generative AI systems

Experience adapting, fine-tuning, or optimizing generative models, including open-source LLMs

Strong understanding of modern LLM system design patterns, including retrieval, tool use, context engineering, evaluation, and agentic workflow orchestration

Experience with containerization, Docker, Kubernetes, cloud platforms, and CI/CD pipelines

Experience with at least one orchestration framework or platform for building LLM-based applications

Familiarity with MLOps practices, including model monitoring, experiment tracking, evaluation pipelines, and production model lifecycle management

Ability to make sound technical decisions considering scalability, reliability, performance, security, and cost

Comfortable working with AI-assisted software development workflows and using modern coding agents to accelerate planning, implementation, testing, and iteration

Strong collaboration and communication skills, with the ability to work effectively across product, engineering, and business teams

Contributions to open-source AI projects

Expertise in LLM evaluation, guardrails, observability, and performance-cost optimization

Experience with frameworks such as LangGraph, GoogleADK, or similar tools

Experience with multimodal AI, graph-based AI systems, reinforcement learning, or other advanced AI domains

Experience designing AI systems for enterprise-scale use cases

Active engagement in AI communities such as Kaggle, Hugging Face, or similar platforms

Experience mentoring engineers or leading technical initiatives in AI/ML teams