Description

Design and govern the enterprise AI platform architecture, spanning LLM API gateways, GPU compute pools, security automation, and multi-agent orchestration.

This role is on-site.

Responsibilities

• Architect multi-agent systems using LangGraph, LangChain, and Model Context Protocol (MCP) for complex workflow orchestration and planning.
• Define infrastructure standards for Amazon Bedrock, SageMaker, and native AWS services (EKS, Lambda, API Gateway) using CDK and Terraform.
• Establish security guardrails for token metering, rate limiting, DLP, and SAST/DAST embedded in CI/CD pipelines.
• Design and optimize RAG systems, embedding strategies, and semantic search across structured and unstructured enterprise data.
• Integrate AI capabilities with Salesforce Agentforce, Einstein, and Data Cloud, managing license governance and data exchange patterns.

Required Skills

• 20+ years of software engineering experience with a focus on AI/ML architecture.
• Expert proficiency with LangGraph, LangChain, and agent orchestration frameworks.
• Deep experience with Amazon Bedrock, SageMaker, Amazon Q, Bedrock Agents, and Knowledge Bases.
• Hands-on experience with Model Context Protocol (MCP), function calling, tool use, and structured output patterns.
• Strong command of prompt engineering, evaluation harnesses, fine-tuning, and model optimization.
• Proficiency in AWS services including EKS, Lambda, ECS Fargate, S3, DynamoDB, Aurora, Redshift, Athena, OpenSearch, Kendra, EventBridge, SNS/SQS, and Kinesis.
• Experience with CloudFormation, AWS CDK, Terraform, and CI/CD practices.
• Working knowledge of transformer architectures, attention mechanisms, and multi-modal systems.

Preferred Skills

• Experience with Salesforce integration patterns (Apex, Flow, Platform Events) and SaaS AI license governance.
• Knowledge of NIST AI RMF, AWS Well-Architected Framework, and enterprise compliance baselines.

Key Skills

Education

Bachelor's or Master's degrees