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
