AIML Architect

We are seeking a visionary AI/ML Architect with deep expertise in the AWS ecosystem and modern data platforms to lead the design deployment and scaling of our enterprise AI this role you will define our next-generation AI strategies leveraging the latest AWS native serviceslike Amazon Bedrock Amazon Bedrock AgentCore and Amazon Qalongside Databricks for unified data analytics and AI.

You will bridge the gap between cutting-edge Generative AI research and production-ready secure enterprise applications.

• Enterprise AI Architecture: Design deploy and govern scalable highly available Machine Learning and Generative AI architectures across the AWS ecosystem and Databricks Lakehouse platform.
• Agentic System Design: Architect autonomous AI agents and multi-agent workflows using Amazon Bedrock AgentCore. Leverage its modular services to move complex agents from proof-of-concept to production scale.
• Unified Data & ML Pipelines: Build orchestrate and optimize end-to-end data and machine learning pipelines using Databricks (Apache Spark MLflow) seamlessly integrated with AWS infrastructure.
• Framework Integration: Integrate AWS Bedrock AgentCore and Databricks Model Serving with open-source agentic frameworks such as LangGraph and CrewAI ensuring seamless tool discovery and interoperability.
• GenAI & BI Synergy: Integrate Amazon Q and Amazon QuickSight Generative BI capabilities into enterprise applications to enable natural language data querying and automated dynamic insight generation.
• MLOps & Governance: Establish robust MLOps pipelines using Databricks MLflow and Amazon SageMaker to ensure standardized telemetry model registry management trace routing and strict compliance with enterprise guardrails.
• Cross-Functional Leadership: Mentor engineering teams collaborate directly with product stakeholders and serve as the central technical authority on AWS and Databricks deployment patterns.

• Experience: 7 years of experience in software engineering data architecture or cloud infrastructure with at least 3 years specifically driving Cloud AI/ML and Generative AI solutions.
• AWS Native AI: Deep hands-on experience with Amazon Bedrock including provisioning fine-tuning prompting foundation models and traditional ML lifecycle tooling.
• Databricks Ecosystem: Proven experience with the Databricks Data Intelligence Platform including Spark SQL Delta Lake Databricks Model Serving and MLflow for tracking experiments and deploying models.
• Agentic Frameworks: Proven experience building stateful conversational AI systems managing serverless agent runtimes and handling multi-tenant session isolation.
• Coding & Infrastructure: Strong programming skills in Python or TypeScript. Experience using Infrastructure as Code (IaC) tools such as AWS CDK or Terraform to deploy modular AI/Data services.

• AWS Certified Solutions Architect Associate

• AWS Certified Solutions Architect Professional (SAP-C02) Highly Preferred
• Databricks Certified Machine Learning Professional or Data Engineer Professional
• AWS Certified Machine Learning Specialty
• AWS Certified AI Practitioner