Senior AI Platform Engineer
Glint Tech Solutions LLC · New York, NY
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Jul 23, 2026
New York, NY
Jul 26, 2026
What this job asks for AI summary
A senior engineering role focused on standing up and governing AI platforms across a large enterprise, spanning tools from multiple major LLM providers. Day-to-day work covers translating security, risk, and compliance requirements into technical controls, managing token budgets and cost dashboards, and building LLM pipelines and agentic workflows using Python and AWS services. Suits an engineer with a background bridging platform engineering and regulated-environment governance.
Senior level · 6+ years · New York-Newark-Jersey City, NY-NJ-PA
“or” means any one of them counts — you don't need all of them.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
Why we read it this way (9)
The role is placed by a staffing firm (Glint Tech Solutions) on behalf of an unnamed enterprise client; employment type (full-time vs. contract) is not stated.
SOC classification is Medium confidence: the role blends AI platform engineering (software development, IaC, pipelines) with governance/compliance enablement and cost management. 15-1252 Software Developers best fits the primary day-to-day work of building LLM pipelines, agentic workflows, and cloud-native infrastructure via code; 15-1299 is the runner-up given the emerging-tech/AI platform specialization.
The 6+ years overall experience requirement is captured as the overall years minimum; the '1-2+ years in AI/cloud platform' sub-requirement is a narrower qualifier within that gate and is not separately surfaced as a skill.
EC2 and ELB/GLB/NLB appear in the Mandatory Skills AWS list but are standard compute/load-balancing primitives rather than distinct skill gates in this context; they are subsumed under the AWS skill to avoid over-fragmenting the list.
MCP (Model Context Protocol) integrations are mentioned in responsibilities and mandatory skills but name no specific product; it is captured under Agentic AI rather than emitted as a standalone skill.
Graph/RAG architectures are split: RAG is emitted as its own skill; graph database tooling is captured via Neo4j/Neptune (vector/graph databases section).
QuickSight and Tableau appear only under the 'Nice-to-Have Skills' section and are marked preferred accordingly.
Financial markets domain knowledge appears only under Nice-to-Have and names no concrete technology, so it is omitted per the generic-concept rule.
No compensation range is advertised.
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