Senior Generative AI & Agentic Systems Engineer

Introduction & Summary:

The Senior Generative AI & Agentic Systems Engineer will play a pivotal role in advancing the design and production of cutting-edge applications utilizing LLM technologies. The ideal candidate will possess a profound expertise in programming, machine learning, and cloud deployment, enabling them to deliver transformative solutions while ensuring robustness and scalability.

Main Responsibilities:

The core responsibilities of this role include:

• Designing and building LLM-powered applications and workflows.
• Implementing Retrieval-Augmented Generation (RAG) at scale using high-accuracy retrieval pipelines.
• Managing agent orchestration and tool integration through advanced frameworks.
• Establishing LLMOps & CI/CD for efficient prompts and agents.
• Integrating safety, security, and governance measures into AI systems.
• Optimizing inference performance and overall operational costs.
• Conducting automated testing and evaluation to measure system effectiveness.
• Curating enterprise data and developing feature stores for agent usage.
• Maintaining observability and reliability through comprehensive monitoring techniques.
• Transitioning research findings into production-ready applications.

Key Requirements:

• BSc/MSc/PhD in Computer Science, Data Science, or related field.
• 5+ years of experience building cloud-based ML/AI systems in production.
• 8+ years of hands-on Python experience for AI/ML applications.
• 3+ years of experience in deploying LLM or Generative AI applications.
• Proficiency with agent frameworks such as LangGraph, Semantic Kernel, and OpenAI Assistants.
• Practical experience with cloud-based GenAI stacks (Azure, AWS, Google).
• Strong collaboration skills with a product-oriented mindset.

Nice to Have:

• Experience with observability tools like LangSmith, W&B, OpenTelemetry.
• Knowledge of serving and scaling infrastructure, including vLLM and Triton.
• Expertise in orchestration tools such as Airflow or Kubeflow.
• Familiarity with reinforcement learning techniques and multi-agent systems.
• Experience in building enterprise assistants integrated with business systems.

Other Details:

This role offers the opportunity to work in a dynamic and innovative environment focused on the development of advanced AI solutions. The position may involve remote work, fostering a flexible work-life balance while contributing to impactful projects.