Description

 Key Responsibilities: · AI/ML Strategy: Design the architectural framework for scaling Artificial Intelligence and Machine Learning models. This includes building pipelines for LLMs, Generative AI, and predictive analytics. · AWS Cloud Governance: Act as the lead architect for AWS environments, ensuring best practices in VPC design, serverless architectures (Lambda), and cost optimization (FinOps). · Data Mesh & Analytics: Overhaul legacy data silos into a modern Data Lakehouse or Data Mesh architecture to support real-time business intelligence and data-driven decision-making. · AI Ethics & Security: Establish guardrails for data privacy in AI models and ensure AWS security protocols (IAM, GuardDuty) are strictly followed.

Required Skills: · Cloud Platform: Proficiency in AWS Ecosystem (S3, SageMaker, Redshift, Glue, Bedrock, and EKS). · Data Frameworks: Experience with Snowflake, Databricks, or Apache Spark for large-scale data processing. · AI Frameworks: Familiarity with PyTorch, TensorFlow, or LangChain for integrating AI into enterprise workflows. · Automation: Strong background in IaC (Infrastructure as Code) using Terraform or AWS CloudFormation.

Preferred Qualifications: · AWS Certifications: Highly preferred (e.g., AWS Certified Solutions Architect – Professional or AWS Certified Data Engineer). · Analytics Background: Proven track record of designing platforms that handle Petabyte-scale data and complex ETL/ELT processes. · AI Integration: Experience moving AI projects from "Proof of Concept" (PoC) to full-scale enterprise production

Key Skills

Education

Any Gradute