Responsibilities • 6+ years in application/platform engineering or analytics; MVPs in AI/ML projects. • 4+ years architecting and managing AWS/GCP cloud environments. • Generative AI and Agent Experience will be must. • Proven track record in ambiguous, fast-paced settings, driving AI/ML and Gen-AI initiatives end-to-end. • Provide strategic guidance on GenAI solution architecture with the latest design patterns. • Develop and solution architect and scale GenAI applications, focusing on LLMs for innovation. • Serve as GenAI infrastructure advisor for AI-centric applications. • Stay updated with LLM application design patterns for scalability and efficiency. • Lead educational initiatives on GenAI and LLM technologies and perform POC. Qualifications • 6+ years of experience within the field of application/platform engineering or related technical work including business intelligence, analytics. • 6+ years of experience with AWS Senior Cloud Data Engineering, management, maintenance, or architecting, implementing best practices and industry standards. Required Skills • Generative AI & Agents: Deep understanding of LLMs, embeddings, vector stores, fine-tuning, and multi-agent orchestration. • MLOps: Hands-on experience with training pipelines, model registries, A/B testing, canary deployments, and monitoring. • Data Platforms: Kafka, Spark, feature stores, and data lakes. • Datastores & Warehousing: Vectorstores, SQL, noSQL, Redis, Snowflake. • Cloud Infrastructure: IAM, VPC, security groups, PaaS/SaaS performance tuning, and governance. • IaC & CI/CD: Terraform, CloudFormation, GitHub Actions. • Containers & Orchestration: Docker, Kubernetes, AWS Fargate. • Scripting & Automation: Python, Javascript & Typescript, PowerShell, Bash. • UI Frameworks: Streamlit for building interactive prototypes and dashboards. • Strong knowledge and established experience with AWS services including but not limited to: S3, EC2, RDS, Lambda, Cloud Formation, Kinesis, Data Pipelines, EMR, Step Functions, VPC, IAM, and Security Groups. • Experience with data warehousing platforms such as Snowflake, Redshift or similar. • Experience with DB technologies, programming and scripting (e.g., SQL, Python, PostgreSQL, AWS Aurora, AWS RDS, MongoDB, Redis). • Experience with DevOps practices and CI/CD tools, pipelines, and scripting for automation (GitLab, AWS Code Pipeline tools, Cloud formation and Terraform). • High degree of knowledge in IAM Roles and Policies. • Strong knowledge configuring AWS cloud monitoring and alerts for cloud resource availability. • Strong scripting experience using PowerShell and/or Python. • High degree of knowledge in PaaS and SaaS application performance. • Understand enterprise level application architecture diagrams and IT security requirements. • Diagnose and resolve complex cloud issues to maintain high service levels. • Offer persistent technical support and advice to development teams. Preferred Skills • Experience designing and building scalable and robust data pipelines to enable data-driven decisions for the business. • Experience with large scale enterprise streaming services such as Kafka. • Experience with Kubernetes and Docker containers or AWS Fargate. • Experience implementing applications with both Windows and Linux server OS. • Experience with networking, security groups, or policy management in relation to Cloud resources across multiple operating systems, including UNIX, Linux, or Windows. • Demonstrate ability to troubleshoot technical problems and issues. • Experience planning and executing on-premises to AWS migrations.