AI/ML Architect

AI/ML 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 solutions. In this role, you will define our next-generation AI strategies, leveraging the latest AWS native services—like Amazon Bedrock, Amazon Bedrock AgentCore, and Amazon Q—alongside Databricks for unified data analytics and AI.

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

Key Responsibilities

• 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.

Required Qualifications & Skills

• 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.

Required Certification

• AWS Certified Solutions Architect – Associate

Preferred Certifications

• 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