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
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