Description

You will define and drive the AI/ML architecture strategy across the organization, owning end-to-end system design for GenAI, LLMs, and traditional ML models.

This role is hybrid.

Responsibilities

• Design scalable data pipelines and real-time streaming systems to support AI workloads.
• Establish and implement MLOps practices for model versioning, deployment, and monitoring.
• Collaborate with AI and Data teams to define best practices in AI system design.
• Ensure adherence to AI governance and compliance standards in all architectural decisions.

Required Skills

• 12+ years in software engineering or data science, with 3–5+ years in AI/ML architecture roles.
• Expertise in RAG (Retrieval-Augmented Generation) and hands-on experience with LLMs (e.g., GPT, Llama).
• Proficiency in Python and frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Strong experience with cloud platforms (AWS, Azure, or GCP AI services).
• Deep knowledge of data engineering, including ETL pipelines, data lakes, and streaming.
• Experience with MLOps tools like MLflow, Kubeflow, SageMaker, or Vertex AI.
• Understanding of vector databases, APIs, microservices, and distributed systems.
• Experience with DevOps and CI/CD pipelines for ML.
• Bachelor's degree in a relevant field.

Preferred Skills

• Exposure to AI governance and compliance frameworks.

Key Skills

Education

Bachelor's degree