Senior AI/ML Engineer

About the Project:
• We are looking for a Senior AI/ML Engineer to join a product AI team developing an AI-powered CRM system.
• The product includes an AI assistant that performs user-requested tasks within the CRM.
• Its architecture includes proprietary LLM APIs, a personalized RAG/context system for each user, agentic workflows and scheduled agents.
• A major focus of the project is optimizing the AI system, controlling token usage and costs, and ensuring reliable production performance.
About the Role:
• This is a hands-on role covering the full LLM stack.
• The engineer will work with LLM application engineering, agentic systems, RAG, context management, fine-tuning, model deployment and production MLOps.
• The role goes beyond prompt engineering or simple LLM API integration.
• The person should be able to make technical decisions independently and take AI functionality from an idea to production.
Responsibilities:
• Design and improve agentic workflows and AI systems.
• Work with LLM APIs and the existing AI architecture.
• Develop RAG and context systems to personalize the user experience.
• Optimize token usage and AI-related costs.
• Fine-tune or adapt models when necessary.
• Participate in deployment, monitoring and production support of AI systems.
• Improve the quality, stability and scalability of AI solutions.
• Make architectural decisions and independently drive tasks from idea to implementation.
Requirements:
• Senior-level experience in AI/ML and LLM projects.
• Proven experience building and deploying AI systems, not only prototypes or experiments.
• Experience with agentic systems, RAG or other LLM-based solutions.
• Understanding of fine-tuning, model adaptation and model evaluation.
• Experience with production deployment and MLOps.
• Strong software engineering and architectural skills.
• High level of autonomy and ownership.
Candidate Profiles:
• We are open to both strong ML/research engineers with productionization experience and production-focused LLM engineers with deep experience building, optimizing and operating AI systems.
• In either case, senior-level ownership and hands-on experience are essential.
Nice to Have:
• Experience with multi-agent systems and scheduled agents.
• Experience optimizing the cost and performance of LLM systems.
• Experience with self-hosted models, GPU inference or model serving.
• Experience working on AI products and complex user workflows.
• Experience processing different data formats and working with text-based AI systems.