Job Description:

Experience
10+ years overall experience in software engineering, data, AI/ML, or architecture
5+ years designing and delivering AI/ML and Generative AI solutions
Experience leading enterprise-scale AI programs

Role Summary

Lead the architecture, governance, and delivery of enterprise AI solutions spanning Machine Learning, Predictive Analytics, Deep Learning, Generative AI, and Agentic AI. Define scalable, secure, and business-aligned AI platforms, applications, and standards.

Key Responsibilities

AI Architecture
Design end-to-end AI/ML and GenAI solution architectures.
Define AI reference architectures, standards, and best practices.
Architect AI-powered applications using ML models, LLMs, RAG, copilots, and AI agents.

AI Platforms & Engineering
Design AI platforms supporting MLOps, LLMOps, model deployment, monitoring, and governance.
Establish reusable AI services, APIs, accelerators, and frameworks.
Drive scalability,



reliability, security, and cost optimization.

Data & Cloud
Architect cloud-native AI solutions on AWS, Azure, or GCP.
Design data pipelines, lakehouse, feature store, and vector database architectures.
Integrate AI solutions with enterprise systems and business applications.

Governance & Leadership
Define Responsible AI, security, compliance, and governance frameworks.
Lead architecture reviews and mentor AI engineering teams.
Partner with business stakeholders to identify and prioritize AI prospects.

Required Skills
Machine Learning, Deep Learning, NLP, Predictive Analytics
LLMs, RAG, AI Agents, Prompt Engineering, Vector Databases
Python, TensorFlow/PyTorch, LangChain/LangGraph, MLflow
MLOps, LLMOps, Docker, Kubernetes, CI/CD
AWS, Azure, or GCP

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