Senior AI/ML Engineer

Job description

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.