Senior AI Platform Engineer

Title: Senior AI Platform Engineer


Client: CPPIB


Location: Hybrid - New York City, NY


Visa: USC/GC Only


Duration: 6+ Months


Interview: Video and In-person


Rate: $65-70/hr. C2C


Note: Candidate must have to include a summary of why he/she is a good fit for the role.


Must have

• 6+ years of progressive engineering experience, including 1-2+ years in AI platform, cloud platform, or emerging-tech enablement roles.
• Demonstrated experience working with InfoSec, Risk, and Compliance teams to define, review, and implement technical controls in regulated environments.
• Hands-on experience implementing controls through configuration and code: IAM/access policies, guardrails, logging and audit trails, quota/rate limiting, and network/data-protection controls.
• Gen AI models (GPT, Claude, Gemini, LLaMA) and prompt engineering techniques.
• Agentic AI, MCP, and Graph/RAG architectures, including building and supporting agents, skills, and MCP servers.
• Gen AI frameworks and LLM gateway/proxy patterns.
• AWS cloud services (AgentCore, Bedrock, EC2, ELB/GLB/NLB, EKS, Fargate, Lambda, Athena, Glue, Lake Formation), including cost management and usage/credit monitoring.
• Infrastructure as Code (Terraform, Puppet, Docker) and containerized deployments.
• Python programming (NumPy, Pandas, Boto3) for automation, tooling, and platform services.
• Vector/Graph databases (Weaviate, Milvus, PGVector, Neo4j, Neptune) and query optimization.
• Automated testing and evaluation frameworks (Ragas, Playwright, Selenium, Zephyr).
• Familiarity with SDLC best practices, DevSecOps, Agile Scrum/Kanban, and work management tools (JIRA, Confluence, JIRA Align).
• Strong stakeholder management and ability to broker agreements across security, risk, compliance, and engineering teams.
• Clear written and verbal communication, including translating technical controls into business language and vice versa.
• Customer-service mindset for user support, with the ability to triage, prioritize, and resolve technical issues efficiently.

• Experience with BI tools (QuickSight, Tableau) for usage and cost reporting.
• Knowledge of financial markets and enterprise data systems.