As a GenAI Enterprise Architect, you will be responsible for defining the AI architecture vision, building scalable ML systems, and guiding cross-functional teams in delivering impactful, production-grade AI solutions. You will work closely with business leaders, data scientists, and engineering teams to translate complex requirements into robust, future-ready architectures.
Requirements
Key Responsibilities
Define and implement enterprise-level architecture for Generative AI and Machine Learning platforms.
Lead the design and deployment of scalable ML pipelines, LLM-based applications, and AI-driven systems.
Collaborate with stakeholders to identify high-impact AI use cases and align them with business objectives.
Establish best practices for model development, evaluation, deployment, and monitoring (MLOps).
Drive architectural decisions around data infrastructure, model serving, API design, and cloud ecosystems.
Mentor and manage engineering teams, fostering a culture of innovation, ownership, and technical excellence.
Ensure compliance with data governance, security, and ethical AI standards.
Stay updated with advancements in GenAI, LLMs, and ML frameworks, and guide adoption where relevant.
Required Skills & Qualifications
10-20 years of experience in software engineering, with a strong focus on Machine Learning and AI systems.
Proven experience in an Engineering Manager or technical leadership role, managing high-performing teams.
Deep understanding of Machine Learning algorithms, deep learning, NLP, and Generative AI models (e.g., LLMs, diffusion models).
Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or similar.
Strong expertise in designing distributed systems, microservices architecture, and cloud platforms (AWS, Azure, or GCP).
Experience with MLOps tools and practices, including CI/CD for ML, model versioning, and monitoring.
Proficiency in programming languages such as Python, Java, or Scala.
Excellent problem-solving skills and the ability to operate in a fast-paced, evolving environment.
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