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!
Responsibilities
- 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
Qualifications
- 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
Nice to Have
- 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
Skills Required
- BSc, MSc, or PhD in Computer Science, Engineering, or related field
- Strong hands-on experience with Python
- Experience with modern ML 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, and optimizing generative models, including open-source LLMs
- Knowledge of modern LLM system design patterns (retrieval, tool use, context engineering, evaluation, agentic orchestration)
- Experience with containerization and Docker
- Experience with Kubernetes
- Experience with cloud platforms
- Experience with CI/CD pipelines
- Experience with MLflow or experiment tracking and MLOps practices (model monitoring, evaluation pipelines, lifecycle management)
- Experience with at least one orchestration framework/platform for building LLM-based applications
- Ability to make sound technical decisions considering scalability, reliability, performance, security, and cost
- Strong collaboration and communication skills
- Comfortable using AI-assisted development workflows and modern coding agents
- Contributions to open-source AI projects
- Expertise in LLM evaluation, guardrails, observability, and performance-cost optimization
- Experience with frameworks such as LangGraph or GoogleADK (or similar)
- Experience with multimodal AI, graph-based AI systems, reinforcement learning, or other advanced AI domains
- Active engagement in AI communities such as Kaggle or Hugging Face
- Experience mentoring engineers or leading technical initiatives in AI/ML teams
What We Do
Commencis has more than two decades of expertise in the world of experience design, software engineering and cloud technologies. We enable enterprises to design and build digital experiences, create stronger relationships with their customers, and bring agility and scalability with cloud solutions. Our products and solutions are used by leading brands in financial services, insurance, airlines and retail in more than 20 countries. We help our clients around the globe to commence their next evolution and pave the way for a thriving digital society
