AWS AI Platform Engineer

Job Title: AWS AI Platform Engineer (Generative AI & RAG)

Location: Raleigh, NC (Onsite)
Experience: 10-15 Years

Job Summary

We are seeking a Senior AWS AI Platform Engineer to lead the design, integration, and deployment of enterprise-scale Generative AI solutions on AWS. The ideal candidate will have deep expertise in AWS cloud services, Amazon Bedrock, RAG architectures, AI agents, and cloud-native platform engineering. This role will serve as the technical bridge between Cloud Infrastructure, AI Platform, Security, Data Engineering, and Application Development teams to accelerate enterprise AI adoption while ensuring scalability, security, governance, and operational excellence.

Required Skills

AWS Cloud Platform

• 10-15 years of experience in Cloud Engineering, Platform Engineering, or Enterprise Architecture
• Strong expertise with AWS services:
  • EC2
  • ECS
  • EKS
  • Lambda
  • S3
  • API Gateway
  • VPC
  • IAM
  • CloudFormation
  • CloudWatch
  • EventBridge
  • SNS/SQS
  • Step Functions
  • KMS
  • Secrets Manager
  • Terraform
  • OpenSearch
  • Cost Optimization & Budgeting

AWS AI Services

• Hands-on experience with:
  • Amazon Bedrock
  • Bedrock Agents
  • Bedrock Guardrails
  • SageMaker AI
  • Amazon Knowledge Bases
  • Amazon Titan
  • Amazon OpenSearch
  • Textract
  • Comprehend
  • Transcribe
  • Rekognition
  • Neptune

Generative AI & RAG

• 4+ years of experience designing and implementing AI/ML and Generative AI solutions
• 2+ years building enterprise RAG solutions
• Strong expertise in:
  • Retrieval-Augmented Generation (RAG)
  • Agentic AI
  • Multi-Agent Systems
  • MCP (Model Context Protocol)
  • Prompt Engineering
  • Context Engineering
  • Vector Databases
  • Embeddings
  • Semantic Search
  • AI Evaluation Frameworks
  • Hallucination Mitigation
  • Responsible AI
  • AI Governance

AI Frameworks

• LangChain
• LangGraph
• LlamaIndex
• Anthropic Claude
• Claude Code

Programming

• Python
• Java
• REST APIs
• SDK Integration
• Git
• CI/CD

Data Engineering

• SQL
• NoSQL
• Document Processing
• Data Chunking
• Metadata Management
• Data Ingestion Pipelines

Leadership

• Technical Leadership
• Architecture Governance
• Cross-Functional Collaboration
• Executive Communication
• Stakeholder Management
• Enterprise Solution Design

Key Responsibilities

• Design and implement enterprise AI platform integration patterns using AWS native services
• Lead onboarding of business applications onto the enterprise AI platform
• Architect scalable Retrieval-Augmented Generation (RAG) solutions and enterprise knowledge retrieval systems
• Design and develop AI agents and multi-agent workflows using LangChain, LangGraph, MCP, and AWS Bedrock
• Build reusable AI APIs, orchestration components, and reference architectures
• Integrate enterprise data sources into AI knowledge bases and semantic search platforms
• Design cloud-native AI solutions leveraging AWS services including Bedrock, SageMaker, Lambda, ECS, and EKS
• Implement infrastructure automation using Terraform and CI/CD pipelines
• Collaborate with Cloud Infrastructure, Security, Networking, Data Engineering, Application Development, and Enterprise Architecture teams
• Lead technical workshops, architecture reviews, and AI platform adoption initiatives
• Implement AI governance, security controls, guardrails, monitoring, and Responsible AI best practices
• Optimize AI platform performance, scalability, availability, and operational excellence

Preferred Qualifications

• AWS Certified Solutions Architect - Professional
• AWS Certified Machine Learning - Specialty
• Experience in enterprise AI platform engineering
• Financial services or large enterprise experience
• Knowledge of MLOps, Kubernetes, Docker, and DevSecOps
• Experience with AI observability and production monitoring