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AI Software Architect - Leuwint
Software Architect
Lead the design and delivery of enterprise‑scale AI, Machine Learning, and Generative AI solutions, building cloud‑native platforms, LLM‑based applications, and end‑to‑end MLOps pipelines on AWS, Azure, or GCP.
About the role
Key Responsibilities
- Design and implement end‑to‑end AI/ML and Generative AI architectures, including LLMs, Retrieval‑Augmented Generation, AI agents, and predictive analytics.
- Build scalable, cloud‑native AI platforms that support model training, deployment, monitoring, and governance using MLOps and LLMOps best practices.
- Architect AI‑powered applications such as copilots, recommendation engines, and automated decision systems.
- Select and integrate appropriate cloud services across AWS, Azure, and GCP to meet performance, security, and cost requirements.
- Collaborate with data engineers, product owners, and senior leadership to translate business goals into technical solutions.
Requirements
- 10+ years of software engineering, data, or solution architecture experience, with at least 5 years focused on AI/ML and Generative AI solution design.
- Deep expertise in Python and modern ML frameworks (e.g., TensorFlow, PyTorch) and hands‑on experience with large language models.
- Proven track record building and operating MLOps/LLMOps pipelines, including CI/CD, model versioning, monitoring, and governance.
- Strong knowledge of cloud platforms (AWS, Azure, GCP) and container orchestration (Kubernetes, Docker) for AI workloads.
- Excellent communication skills and ability to lead cross‑functional teams in a fast‑paced, enterprise environment.
Skills
pythonmachine learninggenerative aiawsazuregcpmlops