About the role

What will you do at Glint Tech Solutions?

Job Title: Senior AI Platform Engineer

Location: New York (Hybrid – 4 days/week onsite)

Interview Process: Onsite interview required

Company Overview

Glint Tech Solutions is a women-owned global IT staffing and recruiting firm serving clients across the USA and Canada. We connect top-tier technical talent with leading enterprise organizations.

Project Description

Our client, a leading enterprise organization, is seeking a Senior AI Platform Engineer to drive AI platform enablement across the enterprise. This role sits at the intersection of engineering, governance, and user enablement, working closely with Information Security, Risk, Legal, and Compliance teams to define platform controls and implement them through configuration and code. The engineer will also manage enterprise AI cost — ensuring tokens, credits, and platform spend are tracked and optimized.

Key Responsibilities

Lead AI platform enablement across enterprise AI tools (OpenAI, Gemini, Anthropic, Amazon Bedrock, LLM gateways, agentic frameworks)
Coordinate with Security, Risk, Compliance, and Legal to review and agree on platform controls and guardrails
Translate agreed compliance/security requirements into technical controls (IAM policies, guardrails, content filters, logging, rate limits, data-access controls)
Document controls and maintain audit/compliance evidence
Manage token budgets, usage quotas, and rate limits across providers; build cost dashboards and anomaly alerting
Provide user support on credit/usage limits, quota management, and AI usage best practices
Troubleshoot issues related to skills, agents, MCP integrations, and API usage
Design and maintain LLM pipelines, agentic workflows, and Graph/RAG architectures using Python and AWS-native tooling
Implement cloud-native solutions (EKS, Lambda, Fargate, Glue, Athena)
Automate provisioning and cost guardrails using Infrastructure as Code
Own end-to-end delivery of platform initiatives using Agile (Scrum/Kanban)
Mandatory Skills
6+ years progressive engineering experience, including 1-2+ years in AI/cloud platform or emerging-tech enablement
Experience partnering with InfoSec, Risk, and Compliance teams to implement technical controls in regulated environments
Hands-on experience with IAM/access policies, guardrails, audit logging, and quota/rate limiting
GenAI models (GPT, Claude, Gemini, LLaMA) and prompt engineering
Agentic AI, MCP, and Graph/RAG architectures
AWS services: Bedrock, EC2, ELB/GLB/NLB, EKS, Fargate, Lambda, Athena, Glue, Lake Formation
Infrastructure as Code (Terraform, Puppet, Docker) and containerized deployments
Python (NumPy, Pandas, Boto3) for automation and platform tooling
Vector/Graph databases (Weaviate, Milvus, PGVector, Neo4j, Neptune)
Automated testing/evaluation frameworks (Ragas, Playwright, Selenium, Zephyr)
SDLC, DevSecOps, Agile Scrum/Kanban, JIRA/Confluence/JIRA Align
Strong stakeholder management and communication across technical and business teams
Nice-to-Have Skills
BI tools (QuickSight, Tableau) for usage/cost reporting
Knowledge of financial markets and enterprise data systems

Which skills does this role require?

AI Platform EnablementAWS BedrockPythonInfrastructure as CodeIAM PoliciesGenAI ModelsAgentic AIGraph/RAG ArchitecturesTerraformDockerEKSVector DatabasesDevSecOpsAgile ScrumStakeholder ManagementPrompt EngineeringOpenAIGeminiAnthropicAmazon BedrockLLM GatewaysAgentic FrameworksIAMContent FiltersRate LimitsNumPyPandasBoto3PuppetLambdaFargateGlueAthenaLake FormationWeaviateMilvusPGVectorNeo4jNeptuneRagasAWSLLMsAgileJira

Make your next move

Build a shortlist and prepare

Identify the requirements you can demonstrate, then choose examples from your work to discuss with the hiring team.

Build a focused shortlist before you applyCompare role requirements with your experience and give each application a clear reason.
Backend engineering jobsCompare current openings and review what to look for in this role.
Platform engineering jobsCompare current openings and review what to look for in this role.
Practice explaining your experience in an interviewRehearse your answers before meeting the hiring team.

Review the responsibilities and requirements before adding an opening to your shortlist.