Distributed Cloud - GenAI Engineer

Responsibilities

• Design and build scalable backend systems in Python (APIs, services, pipelines).
• Integrate LLMs into production systems (RAG, workflows, agents when justified).
• Define cloud-native, cloud-agnostic architectures.
• Ensure quality, testability, observability, and control of cost and latency.
• Lead technical decisions, code reviews, and mentor engineers.
• Build scalable MLOps pipelines for the deployment, monitoring, and continuous improvement of GenAI models in production environments.
• Ensure the ethical, secure, and responsible deployment of generative models, managing risks related to bias and data privacy.
• 10+ years of professional software engineering experience.
• Strong backend development experience with Python.
• Proven experience delivering Generative AI systems to production.
• Solid understanding of software architecture and distributed systems.
• Hands-on experience with cloud platforms (Azure, AWS, or GCP).
• Experience with CI/CD and modern deployment practices.

Requirements

• Experience with RAG, vector search, and data platforms (e.g. Databricks).
• Familiarity with cloud AI and search services (e.g. Azure AI Search or equivalents).
• Experience with containerized and cloud-native architectures.
• Strong technical leadership and mentoring skills.

Additional Information

We design and build enterprise-grade Generative AI solutions that run in production. LLMs are treated as software components within robust, scalable, and observable systems, not as experimental tools. Our solutions are cloud-agnostic by design, and can be deployed on Azure, AWS, or GCP, while selectively leveraging managed services when they add real value (e.g. search, AI, or data platforms). Your mission is to own the technical design and implementation of end-to-end Generative AI solutions, ensuring strong software engineering practices, sound architectural decisions, and reliable integration of LLM-based components into real-world systems. This role is hands-on and technical, with responsibility for technical leadership, mentoring, and architectural decision-making.

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Company Intel

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