AI Platform Engineer

Job summary

Drive enterprise AI platform enablement by integrating GenAI engineering with cloud technology and governance. The role involves hands-on development of LLM applications, agentic AI, and RAG architectures within an AWS environment.

Job details

Our client requires an experienced AI Platform Engineer to help drive enterprise AI platform enablement at the intersection of GenAI engineering, cloud technology, governance, and user enablement. ***This is a hands-on role for someone who combines strong software engineering fundamentals with practical experience in GenAI platforms, LLM applications, AWS, Agentic AI, MCP, and RAG architectures. Required: 6+ years of engineering experience, including 1–2+ years in AI platform, cloud platform, or emerging-tech enablement Enterprise level environments and project work Hands-on experience with GenAI models (GPT, Claude, Gemini, LLaMA), prompt engineering, Agentic AI, MCP, Graph/RAG, and LLM gateway/proxy patterns Strong Python skills, including NumPy, Pandas, and Boto3 Strong AWS experience across services including AgentCore, Bedrock, EC2, ELB/GLB/NLB, EKS, Fargate, Lambda, Athena, Glue, and Lake Formation Experience implementing enterprise security and governance controls in partnership with InfoSec, Risk, and Compliance Experience with Terraform, Puppet, Docker, Infrastructure as Code, and containerized deployments Experience with Vector/Graph databases such as Weaviate, Milvus, PGVector, Neo4j, and Neptune Experience with automated testing/evaluation tools including Ragas, Playwright, Selenium, and Zephyr Strong knowledge of DevSecOps, SDLC, Agile Scrum/Kanban, JIRA, Confluence, and JIRA Align Strong stakeholder management, communication, and user-support skills Nice to have: *Experience with QuickSight or Tableau for usage and cost reporting, along with knowledge of financial markets and enterprise data systems. *Experience in banking/financial services

What you’ll do

Drive enterprise AI platform enablement by integrating GenAI engineering with cloud technology and governance. The role involves hands-on development of LLM applications, agentic AI, and RAG architectures within an AWS environment.

Requirements

Requires 6+ years of engineering experience, including 1-2 years in AI or cloud platforms, with strong proficiency in Python and AWS services. Candidates must have experience with vector databases, containerized deployments, and implementing enterprise security controls.

Listed skills

• Docker · Preferred
• Amazon Web Services · Preferred
• prompt engineering · Preferred
• Terraform · Preferred
• Stakeholder Management · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• GenAI
• LLM
• AWS
• Agentic AI
• MCP
• RAG
• Python
• Terraform
• Docker
• Vector Databases
• Graph Databases
• DevSecOps
• Prompt Engineering
• Infrastructure as Code
• Software Engineering
• Stakeholder Management

Job areas

• Software
• Technology
• Engineering
• Data & Analytics
• Consulting