Generative AI Engineer – Distributed Cloud

About the role

We design and build enterprise‑grade Generative AI solutions that run in production, treating large language models as software components within robust, scalable, and observable systems. The role is hands‑on, responsible for technical design, implementation, and leadership of end‑to‑end GenAI solutions across cloud‑agnostic platforms.

Key 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 and ensure quality, testability, observability, cost and latency control.
• Lead technical decisions, conduct code reviews, and mentor engineers.
• Build scalable MLOps pipelines for deployment, monitoring, and continuous improvement of GenAI models.
• Ensure ethical, secure, and responsible deployment of generative models, managing bias and data privacy risks.

Required profile

• 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.

Required skills

• Python
• Azure
• AWS
• GCP
• CI/CD
• MLOps
• Generative AI
• LLM integration